Objective: To identify research priorities on physical and mental comorbidity among children and adolescents in Zhejiang Province, so as to provide a theoretical base for improving their physical and mental health. Methods: In May 2025, 77 experts in the fields of health and education from 11 cities in Zhejiang Province were selected by convenient sampling method to participate in the first round of expert consultation. In June, 2025, snowball sampling was used to expand to 194 experts for the second round of consultation, and it was convenient to select 21 students from primary schools to high schools in Zhejiang Province and 29 parents to empower the evaluation criteria. It applied the Child Health and Nutrition Research Initiative (CHNRI) method in a structured process, which encompassed the definition of the research field, generation of research ideas, scoring, and quantitative ranking of priorities. Research ideas were evaluated against 6 predefined criteria: effectiveness, safety, answerability, feasibility, sustainability, and scientific significance. Results: After 2 rounds of structured consultations, 81 research ideas on physical and mental comorbidity among children and adolescents were established and classified into 7 subthemes: epidemiological characteristics and influencing factors, optimization of primary service systems and policies, comprehensive intervention strategies for physical and mental comorbidity, biological mechanisms and clinical research, the impact of education and environment on physical and mental health, special populations and social support, and digital and technology driven disease prevention and intervention. The top 10 research priorities primarily centered on the subdomain of "epidemiological characteristics and influencing factors" (5 items). The top 3 research priorities were "the association between outdoor activity duration and the incidence of common diseases (including mental disorders) among children and adolescents" "the impact of outdoor activity duration on the physical and mental health of adolescents" "comprehensive intervention strategies for myopia, obesity, and their comorbidities among children and adolescents". Conclusion The framework of priority issues in the field of psychosomatic comorbidity of children and adolescents in Zhejiang Province based on CHNRI method provides a reference for optimizing the allocation of provincial research resources.

ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

Objective To investigate the current status of cognitive impairment and its influencing factors in patients with Alzheimer's disease (AD) and to explore effective intervention strategies. Methods A total of 380 patients with AD diagnosed in the Qingdao Central Hospital were retrospectively enrolled between January 2023 and January 2025. According to scores of Montreal Cognitive Assessment (MoCA), the patients were divided into a mild cognitive impairment group (21-25 points) and a moderate to severe impairment group (<21 points). The general clinical data in the two groups were collected. The influencing factors of moderate to severe cognitive impairment were analyzed by univariate and multivariate logistic regression analysis. Results Among the 380 AD patients, 157 cases (41.32%) had mild cognitive impairment, and 223 cases (58.68%) had moderate to severe cognitive impairment. Compared with the mild cognitive impairment group, the moderate to severe cognitive impairment group had a higher proportion of patients who were aged ≥ 75 years, engaged in physical labor, had a disease course of ≥5 years, and had moderate to severe atrophy on head CT examination (P < 0.05). Age ≥75 years, disease course ≥5 years, and moderate to severe atrophy on head CT were independent risk factors of moderate to severe cognitive impairment in AD patients (P<0.05). Conclusion Cognitive impairment is closely related to age, disease course and head CT manifestations in AD patients. Interventions targeting these key factors are expected to delay cognitive decline and improve patients' quality of life.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveTo understand the mental health literacy levels and influencing factors among middle school students in Minhang District, Shanghai, and to provide a basis for formulating mental health promotion strategies. MethodsA multi-stage stratified cluster sampling method was adopted. From September to October 2023, middle school students (including junior and senior high school) from 14 streets, towns, and industrial zones in Minhang District, Shanghai, were recruited to participate in a questionnaire survey. The survey collected demographic information and employed the Adolescent Mental Health Literacy Assessment Scale. This scale comprises four dimensions (knowledge, recognition ability, attitude, and behavior) with a total of 22 items, using a Likert 5-point scale (1‒5 points), giving a maximum total score of 110 points. Reverse-scored items were inverted, and the sum of all item scores constituted the total scale score, with higher scores indicating better mental health literacy. A total score of ≥88 points was defined as having adequate mental health literacy. Multiple linear regression was used to analyze the factors influencing mental health literacy. ResultsThe average mental health literacy score of the 3 963 middle school students in Minhang District of Shanghai City was (85.42±11.27) points, with 45.22% of students having adequate mental health literacy. Univariate analyses showed that female students, junior high school students, and those without stressful events or physical illnesses in the past three months had higher total scores of mental health literacy. Statistically significant differences in total scores were also observed among students with different family economic statuses, parental education levels, frequency of physical exercise, parental relationships, father‑child relationships, and mother‑child relationships (all P<0.05). Multiple linear regression analyses showed that middle school students who were female, had better family economic conditions, higher maternal education levels (university degree or above), and harmonious mother-child relationships had higher mental health literacy scores. In contrast, high school students and those middle school students who participated in less physical activity had lower mental health literacy scores. Multivariate logistic regression analyses indicated that students who were female (OR=1.336, 95%CI: 1.174‒1.520), had superior family economic status (OR=2.000, 95%CI: 1.101‒3.725), had mothers with a university education level (OR=1.501, 95%CI: 1.217‒1.856), had lost one parent (OR=2.189, 95%CI: 1.176~4.158), or reported harmonious mother‑child relationships (OR=2.052, 95%CI: 1.432‒2.987) were more likely to meet the criteria for mental health literacy, whereas those who rarely engaged in physical exercise (OR=0.502, 95%CI: 0.358‒0.694) were less likely to have adequate mental health literacy. Stratified analyses showed that mental health literacy levels among junior high school students were positively correlated with being female, having a mother with a university education level, and having a mother‑child relationship that was average or harmonious and having a harmonious father‑child relationship, and negatively correlated with occasional or rare participation in physical exercise. Among senior high school students, mental health literacy levels were positively correlated with being female, having good or superior family economic status, having a mother with a university education level or above, and having a harmonious mother‑child relationship. ConclusionThe rate of adequate mental health literacy among middle school students in Minhang District, Shanghai, was approximately 45.22%. Gender, grade level, family economic status, maternal education level, physical activity participation, and mother-child relationship are independent factors associated with the level of mental health literacy among middle school students. Mother-child relationship and physical activity are potential intervention entry points. It is recommended to implement targeted health promotion initiatives focusing on key groups, such as high school boys, students from economically disadvantaged families, and those with insufficient physical activity.

Definitive treatment of lung cancer with radiotherapy is challenging, as respiratory motion and anatomical changes can increase the risk of severe off-target effects during radiotherapy. Online adaptive radiotherapy (ART) is an evolving approach that enables timely modification of a treatment plan during the interfraction of radiotherapy, in response to physiologic or anatomic variations, aiming to improve the dose distribution for precise targeting and delivery in lung cancer patients. The effectiveness of online ART depends on the seamless integration of multiple components: sufficient quality of linear accelerator-integrated imaging guidance, deformable image registration, automatic recontouring, and efficient quality assurance and workflow. This review summarizes the present status of online ART for lung cancer, including key technologies, as well as the challenges and areas of active research in this field.
Humans ; Lung Neoplasms/radiotherapy* ; Radiotherapy Planning, Computer-Assisted/methods*