Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

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.

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.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

Objective To describe and analyze the epidemiological characteristics of scrub typhus in Huai'an, Jiangsu Province from 2006 to 2024 and explore the long-term incidence trend and distribution of high-risk areas, and to formulate targeted prevention and control strategies. Methods The scrub typhus case report data of Huai'an from 2006 to 2024 in the Chinese Disease Prevention and Control Information System were extracted for descriptive analysis. Results A total of 898 cases of scrub typhus were reported in Huai'an, with an average annual incidence rate of 0.96 per 100 000 from 2006 to 2024. There was a turning point in the incidence trend of scrub typhus in 2011. From 2006 to 2011, the annual percentage change (APC) was 47.09% (95% CI: 7.53 - 859.39), and the upward trend was statistically significant (P < 0.05). From 2012 to 2024, the APC was -2.12% (95% CI: -29.09 - 3.75), and the downward trend was not statistically significant. October and November were the high-incidence months, and the total concentration from 2006 to 2024 was 0.93, indicating that scrub typhus had strict seasonality. The circular distribution method estimated that the peak period of the epidemic was from October 11th to November 25th, and the peak day of incidence was November 3rd. Jinhu County was a high-incidence area. The ratio of male to female cases was 1.03. The age group with the highest reported incidence was 40 to < 80 years old. The occupation with the highest proportion was farmers, accounting for 78.03%. Conclusion From 2006 to 2024, scrub typhus in Huai'an shows a peak every 3 - 4 years. Middle-aged and elderly farmers are the key population at risk, and Jinhu County is a key area. In the future, targeted health education should be carried out to effectively control the prevalence of scrub typhus.

Aim To study whether intravenous injec-tion of miR-129-3p mimetic(agomir)can resist bone loss caused by hind limb disuse,and to provide new i-deas for preventing bone loss in microgravity environ-ment.Methods Forty-eight C57BL/6J male mice were randomly divided into the control group(CON),tail suspension model group(TS),tail suspension+miR-129-3p agomir administration group(miRNA)and tail suspension+miR-129-3p negative sequence agomir control group(NC).The miRNA group was given 4 mg·kg-1 miR-129-3p agomir by intravenous injection into the medial canthus twice a week.The NC agomir group were consistent with those in the miR-129-3p agomir group,and the CON and TS groups were given only equal volumes of normal saline.After four weeks,all mice were sacrificed and samples were collected.Micro-CT scan of femur,three-point femur bending test,serum bone metabolism index detection,oxidative stress index detection and osteogenesis-related protein expression analysis in bone tissue were per-formed.Results After four weeks,the number of tra-becular bone in the TS group was significantly re-duced,and Tb.BMD,Tb.Th,Tb.N,Tb.BS/TV and Tb.BV/TV were significantly lower than those in the CON group(P＜0.01).While Tb.Sp TS group was significantly higher than the CON group(P＜0.05),the maximum load and flexural strength of the femur significantly decreased(P＜0.01),the content of ser-um bone formation index PINP was significantly lower than that of the CON group(P＜0.01),and the con-tent of bone resorption index CTX-I was significantly higher than that of the CON group(P＜0.01),the content of serum oxidative damage indexes 8-iso-PGF2α and 8-OHdG significantly increased(P＜0.01),and the expression of osteogenesis-related pro-teins in bone tissue markedly decreased(P＜0.01).However,the increase or decrease of all indexes in miRNA group was significantly lower than that in TS group.Conclusions miR-129-3p mimetic can signifi-cantly reduce bone loss caused by hind limb disuse.This experiment provides a new idea and method for preventing bone loss in microgravity environment.

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

Objective:To rapidly and accurately detect volumetric modulated arc therapy (VMAT) plans with potentially inaccurate radiation doses.Methods:The measurement-based dosimetric verification result of 196 VMAT plans obtained using ArcCHECK phantoms were retrospectively collected. Independent dosimetric calculation and verification were conducted for these plans using the ArcherQA system based on a fast Monte Carlo algorithm. The gamma passing rates of dosimetric verification using ArcCHECK phantom and the ArcherQA system were compared, followed by their correlation analysis and linear regression fitting. The ArcherQA system′s gamma passing rate threshold used to detect positive dosimetric verification result obtained using ArcCHECK phantoms, as well as the specificity of the detection, were calculated. Based on this gamma passing rate threshold, another 50 VMAT plans were selected as a test set to assess the ArcherQA system′s ability to detect positive measurement-based dosimetric verification result.Results:The average gamma passing rates for the dosimetric verification of the VMAT plans using the ArcherQA system and ArcCHECK phantoms were 97.28% and 96.57% (3%/3 mm, TH=10%), respectively. Both rates had a correlation coefficient of 0.71 ( P < 0.01) and a linear fitting coefficient of 0.54 ( R2=0.51). When the gamma passing rate for dosimetric verification using ArcCHECK phantoms was set at 90% (3%/2 mm, TH=10%), the gamma passing rate threshold for dosimetric verification using the ArcherQA system should be adjusted to 94.8% to detect all VMAT plans with positive dosimetric verification result obtained using ArcCHECK phantoms, with a specificity of 67.8%. Using this threshold, the ArcherQA system detected all VMAT plans in the test set for which ArcCHECK phantom-based measurement yielded positive dosimetric verification result. Conclusions:By determining an appropriate gamma passing rate threshold, the ArcherQA system can rapidly and accurately detect VMAT plans with potentially inaccurate doses, thus ensuring treatment accuracy and improving work efficiency.

Objective To develop a deep learning-based denoising model for accelerating Monte Carlo(MC)simulation of electronic portal imaging device(EPID)transit dose images.Methods A total of 500 EPID fields were collected from 100 lung cancer patients undergoing 5-field intensity-modulated radiotherapy,with 400 fields randomly selected as training set,50 fields as validation set,and 50 fields as test set.EPID transit dose image datasets with low particle counts(1×107)and high particle counts(1×109)were simulated using the GPU-accelerated MC dose calculation engine ARCHER.A denoising network model named SUNet was constructed based on Swin Transformer and U-Net,and trained using low-particle-count images as input and high-particle-count images as output.Following training,SUNet model was used to denoise low-particle-count EPID images in the test set.Denoising performance was evaluated using structural similarity index(SSIM),peak signal-to-noise ratio(PSNR),and Gamma passing rates(3%/2 mm),and the computational efficiency of MC simulation combined with SUNet model was analyzed.Results Compared with the original low-particle-count images,the SUNet-denoised images showed significantly improved quality,reduced noise points,and smoother dose distribution.When benchmarked against high-particle-count images,the SUNet-denoised images achieved an average SSIM greater than 0.9,an average PSNR higher than 32 dB,and an average gamma passing rate exceeding 90%.The MC simulation combined with SUNet model required only 1.88 s to simulate a single EPID transit dose image,representing an approximate 40-fold improvement in computational efficiency as compared with high-particle-count MC simulation.Conclusion The deep learning-based denoising model substantially accelerates MC simulation of EPID transit dose images while preserving both image quality and dose accuracy,which provides possibilities for EPID-basedin vivodose verification.