Patients with Takayasu arteritis combined with aortic valve disease often have a poor prognosis following surgical valve replacement, frequently encountering complications such as perivalvular leakage, valve detachment, and anastomotic aneurysm. This article presents a high-risk case wherein severe aortic valve insufficiency associated with Takayasu arteritis was successfully managed through transcatheter aortic valve implantation via the transapical approach. The patient had satisfactory valve function with no complications observed during the six-month postoperative follow-up. This case provides a minimally invasive and feasible alternative for the clinical management of such high-risk patients.

ObjectiveTo investigate the functional role and underlying molecular mechanisms of fumarylacetoacetate hydrolase （FAH） in the progression of glioblastoma （GBM）. MethodsDifferential expression analysis was performed on the TCGA-GBM， GSE4290， and GSE116520 datasets. Weighted gene co-expression network analysis （WGCNA） was used to identify key modules， and Cox regression and risk modeling were used to screen prognostic genes. Immune infiltration analysis of prognostic genes was carried out by using single-cell RNA sequencing panels. The clinical expression signature of FAH in GBM was analyzed in the TCGA and HPA databases. The functional role of FAH was validated by in vitro and in vivo experiments， and pathway analysis was performed to explore the underlying mechanisms. ResultsA total of 152 overlapping genes were identified across the three GBM datasets （P<0.05）. WGCNA revealed that the turquoise module was most strongly associated with tumor purity， stromal score， immune score， and ESTIMATE score （P<0.001）. Compared with normal tissues， three prognostic genes （CTSD， FAH， and THBD） were upregulated in GBM and correlated with immune infiltration （P<0.05）. FAH mRNA and protein levels were elevated in GBM tissues relative to normal tissues， and its expression was significantly associated with age stratification and TP53 mutation （P<0.05）. CCK-8 assay results showed that， compared with the shNC group， the proliferative activity of GBM cells in the shFAH group was reduced （P<0.001）. Transwell migration and invasion assays demonstrated that， relative to the shNC group， the numbers of migrated and invaded cells in the shFAH group decreased （P<0.05）. Western blot analysis revealed that the protein expression levels of PI3K， p-AKT， and p-mTOR in the shFAH group decreased compared with those in the shNC group （P<0.05）. In vivo subcutaneous xenograft experiments further confirmed that tumor volume and weight significantly decreased in the shFAH group compared with the shNC group （P<0.001）. ConclusionFAH promotes GBM progression by activating the PI3K/AKT/mTOR signaling pathway and may serve as a potential therapeutic target for GBM.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Metastatic castration-resistant prostate cancer (mCRPC) implies highly heterogeneous molecular tumor behavior, rapid disease progression and poorer prognosis, seriously threatening the lives of patients.Therefore, early identification and treatment are significant.Among the current clinical treatment regimens for mCRPC, abiraterone acetate, enzalutamide and docetaxel have demonstrated improvement in overall survival (OS).Furthermore, patients carrying homologous recombination repair mutation (HRRm) are sensitive to poly ADP-ribose polymerase inhibitors (PARPi).For patients with positive prostate specific membrane antigen (PSMA), Lutetium-177 (177Lu)-PSMA-617 radiation ligand therapy is a new and effective treatment method.Radium-223 has also been used as the first-line treatment for patients with bone pain symptoms.However, due to the rapid updates in the field of mCRPC drug therapy, clinicians find it difficult to keep up with the latest developments in this area.Emerging drugs have great potential, such as immune checkpoint inhibitors (ICIs) and antibody-drug conjugates (ADCs), but more evidence is needed, and molecular markers helping predict the efficacy of these drugs should be explored.This article reviews the advances in the drug therapy of mCRPC, with the aim of providing reference for clinical practice.

Blood transfusion is an important life-support measure in modern medicine. As clinical demand for transfusion continues to rise, blood supply remains under persistent strain, making the efficient utilization of this precious medical resource a critical component of blood management. Accurate prediction of transfusion needs is of great significance for optimizing blood resource allocation and conserving blood products. Traditional transfusion decision-making relies on clinical experience and simplified scoring systems, which are insufficient to meet the demands of precision medicine. Machine learning (ML) technology can integrate multidimensional data—including demographic characteristics, laboratory indicators, surgical information, and dynamic physiological waveforms—to construct high-performance predictive models, offering a new approach to transfusion prediction. This article systematically reviews the application progress of ML in transfusion prediction across clinical scenarios such as trauma, the perioperative period, and obstetrics. In trauma, ML has been applied to early massive transfusion prediction, prehospital transfusion decision-making, and precise prediction in pediatric trauma. In the perioperative field, applications span specialties including traumatic brain injury, orthopedic surgery, cardiovascular and major vascular surgery, and hepatic surgery. In obstetrics, models can effectively predict postpartum hemorrhage and transfusion requirements associated with cesarean section. Studies have shown that algorithms such as random forest, gradient boosting machines, and deep neural networks achieve area under the receiver operating characteristic curve (AUC) values of 0.83-0.98 in massive transfusion prediction, 0.75-0.97 in perioperative scenarios, and 0.80-0.89 in obstetric transfusion prediction—significantly outperforming traditional scoring tools. However, current studies are generally limited by single-center retrospective designs, insufficient external validation, and inadequate reporting standards; limited model interpretability and challenges in clinical integration further constrain practical translation. Future research should focus on constructing multicenter data cohorts, integrating multimodal data, conducting prospective implementation studies, and deeply embedding models within electronic health record systems, thereby advancing the application of ML to optimize clinical transfusion decision-making.

Objective: To explore the effect of relative deprivation on emotional attention among college students from single parent families, so as to provide evidence for psychological crisis prevention and campus mental health services. Methods: From January to June 2023, 478 college students from North China University of Science and Technology were selected by convenience sampling method. Participants with high and low levels of relative deprivation were screened by using the extreme grouping method, and 48 valid participants were finally included. A 2 (single parent/non single parent) ×2 (high/low relative deprivation) design was adopted. One way ANOVA was conducted on four eye tracking indicators, followed by stratified analyses according to family structure. Results: Overall, participants showed attentional bias toward low valence faces, as indicated by first fixation direction ( t = 2.17) and first fixation duration proportion ( t =-4.28) (both P <0.05). Three factor repeated-measures ANOVA showed a significant interaction between family structure and picture type ( F =23.08, P <0.05). Stratified analysis showed that, in the single parent subgroup, the interaction between relative deprivation and picture type was significant ( F =13.28, P <0.01), whereas this interaction was not significant in the non single parent subgroup ( F =2.18, P >0.05). Further interaction analysis showed that relative deprivation had a partial interaction effect between singleparent background and emotional attentional bias ( β =0.14, Bootstrap 95% CI =0.11-0.47, P <0.05). Conclusions College students from single parent families may show enhanced attentional bias toward negative emotional cues through increased relative deprivation. Students with both single parent background and high relative deprivation are a high risk group.

Oral health is closely related to facial aesthetics, mastication, pronunciation, and systemic diseases. Flexible sensors can improve current deficiencies in clinical diagnosis and treatment through oral health monitoring. This paper reviews the research on and application of flexible sensors in oral health monitoring in recent years, providing a reference for the further development of flexible sensors in the oral field. The structural basis of flexible sensors includes a flexible substrate, stretchable electrodes, and an active layer, and each part is designed through material selection to adapt to the oral environment. The sensing mechanisms of sensors involve electricity, optics, electrochemistry, and immunology, among which electro-chemical, biological, and optical sensors are particularly prominent in the oral field. The monitored signals include physical signals such as orthodontic force, bite force, respiratory humidity, and implant temperature; chemical signals such as saliva metabolites and oral gases; and biological signals such as periodontal disease and oral cancer markers. At present, flexible sensors still face many challenges in this special oral environment. Future research directions include improving the biocompatibility, moisture resistance, and flexible fitting ability of sensors in the oral cavity; using temperature-insensitive materials and protective films to improve stability; and introducing artificial receptors and sensor arrays to improve factors such as selectivity. In addition, multi-disciplinary cooperation is crucial for breaking through current bottlenecks and achieving more accurate disease diagnosis and health monitoring. In the field of stomatology, finding specific biomarkers related to corresponding oral diseases is the key to sensor health monitoring. Through these efforts, flexible sensors are expected to gain more extensive applications in the field of oral health monitoring.

Objective: To explore the correlation between traditional Chinese medicine (TCM) constitution and depressive symptom among school aged children and adolescents, so as to provide evidences for informing constitution based regulation and prevention of depressive symptom. Methods: From June to December 2024, a total of 4 729 students aged 6-14 were recruited by cluster random sampling from 10 primary schools in Baoding (Hebei Province), Heze and Liaocheng (Shandong Province). General information, TCM constitution and depressive symptom were collected. Restricted cubic spline (RCS) models were used to analyze related factors and threshold effects of depressive symptom. Binary Logistic regression was applied to examine the association between depressive symptom and TCM constitution, with subgroup analyses conducted. Results: The detection rate of depressive symptom among the included children and adolescents was 25.82%. RCS analyses indicated non linear associations between depressive symptom and age (inflection point at 10 years old), bedtime (inflection point at 22:00), and wake up time (inflection point at 6:30 ) (all P non linearity <0.01). Linear associations were observed with body mass index (BMI) and sleep duration (all P non linearity > 0.05 ). After adjusting for covariates such as age, BMI and sleep status, binary Logistic regression analyses showed that Yin deficient constitution ( OR =1.26, 95% CI =1.09-1.45) and Phlegm-dampness constitution ( OR =1.42, 95% CI =1.11-1.82) were significantly associated with depressive symptom among children and adolescents (all P <0.05). Conclusions Depressive symptom among school aged children and adolescents is primarily associated with Yin deficiency and Phlegm dampness constitutions in TCM constitution. Active attention should be paid to susceptible TCM constitution among children and adolescents. Targeted health guidance and interventions should be implemented to improve TCM constitution health status for preventing the occurrence of depressive symptom.

Objective: To explore the association between mental health and muscle strength among Chinese adolescents aged 13- 18, providing a theoretical foundation and intervention strategies for mental health promotion. Methods: Data were obtained from the 2019 Chinese National Survey on Students Constitution and Health, including 98 631 Chinese adolescents aged 13- 18. Psychological distress was assessed by using the Kessler Psychological Distress Scale (K10), and mental well being was measured with the Warwick-Edinburgh Mental Well being Scale (WEMWBS). Based on the gender and age specific Z scores of various test items [grip strength, standing long jump, pull ups (for males), and sit ups (for females)], muscle strength index (MSI) was constructed to evaluate the comprehensive level of muscle strength in adolescents. According to the Dual factor Model (DFM) of mental health, participants were categorized into four groups:troubled, symptomatic but content, vulnerable, and complete mental health. Gender differences were analyzed by using Chi-square tests, trends were tested with Cochran-Armitage tests, and multinomial Logistic regression models were applied to assess associations between muscle strength and mental health among adolescents. Results: In 2019, 37.4% of Chinese adolescents aged 13-18 were reported of high mental distress, and 59.9% were reported of low mental well being. Boys had significantly lower rates of high mental distress (35.3%) and low mental well being (55.6%) compared to girls (39.4%, 64.3%), and the differences were of statistical significance ( χ 2=176.13, 780.42, both P <0.05). In 2019, the rate of complete mental health among adolescents showed a downward trend with increasing age ( χ 2 trend = 258.47) and a gradual upward trend with increasing muscle strength levels ( χ 2 trend =123.14)，and both boys and girls exhibited similar trends ( χ 2 trend =103.83, 168.46; 57.00 , 67.34) (all P <0.05). The results of the unordered multiclass Logistic regression model showed that after controlling for confounding factors such as age and gender, when the completely pathological group as a reference, for every 1 unit increase in MSI in adolescents, the likelihood of being in a completely mental health state increased by 29% ( OR = 1.29); for every unit increase in the Z-score for pull ups, the likelihood of being in a completely mental health state increased by 6% ( OR =1.06) among boys; for every 1 unit increase in sit up Z score, the likelihood of being in a completely mental health state increased by 19% ( OR =1.19) among girls (all P <0.05). Conclusions The mental health status of Chinese adolescents is not good enough. Muscle strength is positively associated with mental health.

Objective: To investigate the iodine nutrition status of children in water borne iodine excess areas in Hebei Province, so as to provide references for scientific prevention and control of water borne iodine excess hazards. Methods: From March to September each year during 2018 to 2023, a cross sectional survey was conducted in 39 water borne iodine excess counties (measured in 2017) from 5 cities (Cangzhou, Hengshui, Xingtai, Handan and Langfang) in Hebei Province. The survey included the detection of iodine content in residents drinking water, the measurement of thyroid volume in children aged 6-12, the detection of salt iodine and urinary iodine. The iodine nutrition status and water iodine distribution of 6-12 year-old children were evaluated from different perspectives such as years, gender, and age. Kruskal-Wallis H- test, Mann-Whitney U test and Chi square test were used for group comparison. Results: A total of 38 755 children were surveyed from 2018 to 2023, and 1 270 drinking water samples were tested across the province. The mass volume concentration of iodine in water showed a decreasing trend over the years ( Z= -30.87, P <0.01). Among 38 470 salt samples monitored from children s home, 24 790 were not non iodized salt, with a non iodized salt rate of 64.44%. A total of 31 989 urine samples were collected from children aged 8-10 years, with the median urine iodine was 245.94 μg/L. Comparing the results of urinary iodine in children from different years, the median urinary iodine from 2018 to 2023 were 328.0, 339.3, 267.8, 279.1, 291.3, 186.5 μg/L, respectively, with statistically significant differences ( H= 4 138.40 , P <0.01). Further pairwise comparisons showed that the median urinary iodine of children in 2023 was lower than in all other years ( Z =-51.59 to -11.41, all P <0.01). Among children aged 6-12 years, 1 150 cases of goiter were detected and the rate of goiter was 3.0%; and the goiter rates in boys and girls were 2.8% and 3.1%, with no significant difference between the sexes ( χ 2= 2.76, P >0.05). There were significant differences in the rate of goiter among different years and ages ( χ 2=324.02, 191.61, both P <0.05). Conclusions With the progress of water reform in water borne iodine excess areas of Hebei Province, children s iodine nutrition has reduced from excessive state to suitable state. It is necessary to continue to expand the coverage of water based iodine reduction projects, and strengthen the monitoring of iodine nutrition status of key populations in water borne iodine excess areas.