ObjectiveTo explore the differences in attention to the sub-dimensions of satisfaction with the quality of assistive devices among people with different self-care abilities in China, identify the key driving factors, and provide a basis for the precision design and service provision of assistive devices. MethodsBased on the 2023 national survey data, involving 14 030 people with functional impairments, self-care ability was taken as the core independent variable, eight sub-dimensions of satisfaction as dependent variables, and variables such as gender, age, educational level and residential type were controlled. Univariate analysis was performed using Chi-square test with Bonferroni correction, and a binary Logistic regression model was constructed to identify influencing factors. Meanwhile, reliability and validity tests, endogeneity tests (instrumental variable method and propensity score matching) and heterogeneity tests were conducted. ResultsAmong the eight satisfaction sub-dimensions, six presented significant inter-group differences, with Bonferroni correction (threshold = 0.00625). Following binary Logistic regression and endogeneity correction, significant inter-group heterogeneity was confirmed in dimensions such as size and shape. For the affordability dimension, the main effect of self-care ability was not statistically significant, yet prominent urban-rural heterogeneity was observed. Specifically, taking the fully independent (self-care) group as the reference, the fully dependent group attached significantly greater importance to safety (B = 0.253, P < 0.001), comfort (B = 0.153, P = 0.001) and ease of use (B = 0.316, P < 0.001); the partially dependent group showed the highest level of attention to lightweight (B = 0.094, P = 0.027) and durability (B = 0.254, P < 0.001); and the fully independent group demonstrated a relatively stronger preference for aesthetics. ConclusionStratified functional demands, driven by self-care ability, exist in the satisfaction of individuals with functional impairments with assistive devices in China. The policy formulation and product design of assistive devices should shift to a precision-oriented paradigm: prioritize the guarantee of safety, comfort and ease of use for fully dependent groups, optimize lightweight performance and durability for partially dependent groups, enhance aesthetics and social acceptance for fully independent groups, roll out price subsidy policies for urban price-sensitive groups, and strengthen the supply of core functional services for rural groups. This approach will comprehensively improve the adaptation effectiveness of assistive devices and the well-being of users.

ObjectiveThe biosynthesis of heterophyllin B （HB）， a cyclopeptide from Pseudostellaria heterophylla， is regulated by various abiotic stresses. Elucidating the transcriptional regulatory mechanism underlying HB biosynthesis is of great guiding significance for the directional improvement of P. heterophylla varieties and the enhancement of HB content. MethodsBased on transcriptome data from different tissues of P. heterophylla， transcription factors （TFs） specifically upregulated and highly expressed in the phloem of tuberous roots were screened through a combination of Mfuzz time-series clustering， transcription factor family prediction， and correlation analysis. Quantitative real-time polymerase chain reaction （Real-time PCR） was employed to analyze expression patterns of candidate TFs under abscisic acid （ABA） induction， and the dual-luciferase reporter assay was applied to verify their regulatory effects on HB precursor genes. ResultsContent determination showed that HB accumulated at the highest in the phloem of P. heterophylla tuberous roots （34 μg·g^-1 fresh weight）. Transcriptome analysis identified 15 868 up-regulated differentially expressed genes （DEGs）， among which 4 375 were specifically up-regulated in the phloem. From these， 25 TFs highly expressed in the phloem were screened. Correlation analysis revealed that the expression level of WRKY70 was significantly positively correlated with HB content， the expression of precursor genes prePhHB， and PhPOP1. Additionally， WRKY70 expression was significantly upregulated under ABA induction. Dual-luciferase reporter assay confirmed that WRKY70 specifically activated the transcriptional activity of the prePhHB promoter （Pro-prePhHB）. ConclusionHB is mainly accumulated in the phloem of P. heterophylla tuberous roots. WRKY70 positively regulates HB biosynthesis by directly activating the promoter activity of prePhHB. This study clarifies the key role of WRKY70 in the regulation of HB biosynthesis and provides an important theoretical basis for the in-depth analysis of the molecular regulatory mechanism underlying HB biosynthesis.

ObjectiveTo construct a scale for the diagnosis of chronic atrophic gastritis （CAG） with turbid toxin accumulating in the stomach. MethodsFirst， a research group was established to construct the scale framework. Relevant literature of CAG with syndrome of turbid toxin accumulating in the stomach was searched in CNKI， Wanfang Database （WF）， and VIP Database （CQVIP） from April 1， 2003 to April 1， 2023， and items were preliminarily selected after standardization of terms. Through clinical investigation， the discrete trend method， correlation coefficient method， Cronbach's coefficient method， and factor analysis method were used to screen symptom items， and the frequency method was used to screen signs， tongue coating， and pulse conditions. Three rounds of Delphi expert consultation were conducted to determine the items of the scale. The weight of each item was obtained by the analytic hierarchy process. ResultsA total of 49 articles were included， and 45 items were obtained after primary screening， including 28 symptoms， 2 signs， 10 tongue coatings， and 5 pulse conditions. After clinical investigation， 15 symptoms were retained， and 8 signs and pulse conditions of tongue coating were retained. The positive coefficients of experts in three rounds of Delphi expert consultation were 100%， 96.67%， and 100%， respectively. The expert authority coefficients were 0.86， 0.87， and 0.87， respectively， and the coordination coefficients were 0.18， 0.25， and 0.30. After core group discussion， Delphi method investigation， and AHP weight assignment， the diagnostic scale items of CAG with turbid toxin accumulating in stomach syndrome were finally established， namely， dark red or purplish tongue proper with yellow greasy （or dry） coating （30 points）， epigastric stuffiness and fullness or pain （15 points）， sticky and unsmooth defecation （10 points）， taste disturbance （sticky mouth， fetid breath， bitter taste， 7 points）， heartburn or acid regurgitation （6 points）， dizziness and clouding （5 points）， general heaviness and fatigue （5 points）， slippery， string‑slippery， or slippery‑rapid pulse （5 points）， dysuria （or yellow or deep yellow urine， 4 points）， poor appetite （4 points）， dull complexion （3 points）， sticky， greasy， and fetid secretions （3 points）， and poor sleep （3 points）. ConclusionBased on the establishment， screening， confirmation， and weighting of an item pool， combined with subjective and objective approaches as well as qualitative and quantitative methods， a diagnostic scale for CAG with the syndrome of turbid toxin accumulating in the stomach was successfully constructed.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Objective To investigate the distribution characteristics of Oncomelania hupensis snails in Yunnan Province fol-lowing interruption of schistosomiasis transmission, so as to provide the evidence for assessing the risk of schistosomiasis transmission and scientifically formulating the schistosomiasis surveillance program. Methods According to the requirements of the National Schistosomiasis Surveillance Scheme (2020 Edition), O. hupensis snail surveillance data were collected from 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province from 2020 to 2024, including area of snail survey, area of snail habitats, area of re-emerging snail habitats, number of frames surveyed, number of frames with O. hupensis snails, number of O. hupensis snails captured, and number of living snails, and the occurrence of frames with snails and mean density of living snails were calculated. Changes in snail status over the 5-year period from 2020 to 2024 and the differences in snail distributions specified by epidemic intensity, environmental type, and vegetation type were analyzed. Results The areas of snail survey increased from 1 727.96 hm² in 2020 to 3 894.45 hm² in 2024 (peak) across 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province during the period from 2020 through 2024. The areas of snail habitats increased from 70.36 hm² in 2020 to a peak in 2023 (172.04 hm²), followed by a reduction to 132.36 hm² in 2024, and the areas of re-emerging snail habitats increased from 42.71 hm² in 2020 to a peak in 2022 (78.43 hm²), followed by a reduction to 40.21 hm² in 2024. The occurrence of frames with snails and mean density of living snails increased from 1.24% (3 025/244 404) and (0.033 2 ± 0.038 7) snails/0.1 m² in 2020 to peaks at 2.03% (6 231/307 563) and (0.066 9 ± 0.068 4) snails/0.1 m² in 2023, followed by reductions to 1.04% (5 829/559 941) and (0.032 6 ± 0.057 7) snails/0.1 m² in 2024, respectively. There was a significant difference in the occurrence of frames with snails over the 5-year study period (χ² = 1 962.95, P < 0.05), and the occurrence of frames with snails reduced by 48.71% in 2024 relative to in 2023 (χ² = 1 411.05, P < 0.005); however, there was no significant difference in the mean density of living snails over the 5 years (H = 5.310, P > 0.05). There were significant differences in the occurrence of frames with snails (χ² = 481.27, P < 0.05) and mean density of living snails (H = 6.872, P < 0.05) in schistosomiasis-endemic areas with different epidemic intensities. The occurrence of frames with snails (χ² = 25.32 and 38.70, both P values < 0.017) and mean density of living snails (Z = 28.55 and 49.96, both P values < 0.017) were higher in schistosomiasis transmission-interrupted and eliminated areas with snails than in schistosomiasis-eliminated areas without snails, and the occurrence of frames with snails (χ² = 453.54, P < 0.017) and mean density of living snails (Z = −56.97, P < 0.017) were higher in schistosomiasis-eliminated areas with snails than in schistosomiasis transmission-interrupted areas with snails. O. hupensis snails were mainly distributed in paddy fields, dry farmlands and ditches; however, the occurrence of frames with snails (13.40%, 424/3 164) and mean density of living snails [(0.252 8 ± 0.158 7) snails/0.1 m²] were higher in ponds/weirs than in other types of environments (both P values < 0.05). Rice, dry farmland crops and weeds were main vegetations in which O. hupensis snails were distributed, and the occurrence of frames with snails (2.29%, 7 111/310 140) and mean density of living snails [(0.072 3 ± 0.018 9) snails/0.1 m²] were higher in weeds than in other types of environments (both P values < 0.05). Conclusions O. hupensis snails have been effectively controlled in Yunnan Province following implementation of integrated schistosomiasis control measures; however, there are still risk factors for schistosomiasis transmission, including reduced attention to schistosomiasis control and snail re-emergence. Improved control efforts and surveillance system construction and timely identification of risk factors of snail status and timely management are recommended to ensure the achievement of the target of schistosomiasis elimination as scheduled.

Hereditary carotid body tumor (HCBT) is a rare neuroendocrine tumor mainly caused by germline mutations of the SDHx gene. Its multifocality, familial aggregation, and potential malignant risk pose unique challenges to diagnosis and treatment. This review systematically expounds the molecular mechanism of HCBT, pointing out that SDHx mutations drive tumorigenesis through the “pseudo-hypoxia” pathway and are regulated by epigenetic and somatic mutations. In terms of diagnosis, we emphasize the crucial role of ⁶⁸Ga-DOTATATE PET/CT and SDHB immunohistochemistry and advocate for multigene panel sequencing for patients with high-risk characteristics (such as early-onset, multifocal, family history or malignant signs) to clarify the genetic background. On the basis of existing evidence, we recommend conducting baseline biochemical tests for all newly diagnosed patients and actively suggest genetic screening for high-risk individuals such as those who are young, have multifocal tumors, or have a family history. In terms of treatment, surgery is the main treatment method for HCBT. Nevertheless, individualized strategies still need to be formulated based on tumor classification and patient’s overall condition and genetic background. Comprehensive management measures such as targeted therapy, radionuclide therapy, and standardized family management are crucial for improving the prognosis of patients.

Objective To explore the correlation between alterations in intestinal microbiota composition and abnormal cytokine expression in patients with gastric cancer. Methods Fecal and peripheral blood samples were collected from 81 patients with gastric cancer (gastric cancer group) and 85 healthy subjects (healthy control group). Fecal bacterial DNA was sequenced through 16S rRNA gene amplicon sequencing, and the serum levels of 17 cytokines were measured with the AimPlex multiplex assay technology: IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-15, IL-17A, TNF-α, TNF-β, GM-CSF, G-CSF, IFN-γ, IP-10, MCP-1, and VEGF-A. Results In the gastric cancer group, the abundances of 11 butyrate-producing bacteria, including certain genera of the Lachnospiraceae family (such as Lachnospira and Roseburia) and Faecalibacterium, considerably decreased. By contrast, the abundances of nine bacterial taxa, including Escherichia–Shigella, Streptococcus, Veillonella, and Parabacteroides, significantly increased. Correlation analysis showed that the decrease in the abundance of butyrate-producing bacteria were significantly negatively correlated with the high expression levels of pro-angiogenic and immunosuppressive cytokines in the gastric cancer group, including IP-10, IL-10, MCP-1, IL-8, IL-6, and VEGF-A. However, the decrease was significantly positively correlated with the downregulation of antitumor immune-related cytokines, including IL-2, IL-17A, IL-1β, TNF-β, and GM-CSF. Conversely, the enriched bacterial taxa exhibited opposite correlation patterns with these cytokines. Conclusion A close correlation is observed between intestinal microbiota dysbiosis and abnormal cytokine expression in patients with gastric cancer. The findings suggest that restoring the intestinal microbiota through fecal microbiota transplantation is a promising strategy for regulating cytokines and is a potential research direction for the adjuvant therapy of gastric cancer.

Objective: To assess the association of family food environment with dietary and nutrition literacy among junior and senior high school students, providing a basis for nutritional health education and adolescent nutritional improvement. Methods: From January 9 to February 10, 2025, a total of 1 473 junior and senior high school students aged 12-20 were recruited by using a cluster random sampling method combined with convenient sampling from 15 provinces (municipalities and autonomous regions) across China. Data on basic demographic characteristics, home food environment, and dietary and nutrition literacy were collected by using the Food and Nutritional Literacy Questionnaire for Chinese School age Children. Multiple linear regression and Logistic regression models were employed to analyze the association of the home food environment on adolescent dietary and nutrition literacy. Results: The total score of dietary and nutrition literacy among junior and senior high school students was (65.28±9.03). The score in the cognitive domain (67.59±10.56) was higher than that in the skill domain (60.74±9.15), and the score for food preparation skills (56.60±14.28) was the lowest. Students aged 16-20, senior high school students, those for only children, non boarding students, those with urban household registration, those from wealthier families, those whose primary caregivers were parents with higher education levels, and those who previously received nutrition and health education had significantly higher dietary and nutrition literacy scores compared to their respective counterpart groups ( t/F =-8.32, -8.14, 4.76, -2.70, 7.15, 18.29, 10.68, 11.66 , all P <0.05). Multiple linear regression analysis revealed that family food environment was associated with dietary and nutrition literacy, and the model was statistically significant ( R 2=0.20, F=20.54, P <0.05). Lower availability of fruits at home in the past month and lower frequency of family communication regarding dietary and nutrition were associated with lower dietary nutrition literacy scores among junior and senior high school students ( β =-1.35, -1.67, both P <0.01). Among junior and senior high school students, lower frequency of dining out with the family, watching videos during family meals, and being urged by parents to eat more food in the past month were associated with higher scores on dietary nutrition literacy ( β =1.35, 1.13, 0.71, all P <0.01). Logistic regression model results indicated that watching videos during family meals ( OR =1.70) and family communication regarding dietary and nutrition ( OR =0.51) were significantly associated with dietary and nutrition literacy levels (both P <0.05). Conclusions The score of dietary and nutrition literacy among junior and senior high school students is relatively low, and the family food environment is a key factor. It is recommended that nutrition education and improvement initiatives for junior and senior high school students prioritize attention on children and adolescents from households with less favorable food environments.

Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.