Capital University

Precision medicine is increasingly applied in stomatology by enabling personalized diagnosis and treatment tailored to individual patient needs, and fulfilling this promise involves a convergence of medicine and engineering. Laser is a coherent light that functions as a diagnostic tool and provides tailored energy that can be precisely modulated spatially and temporally for direct treatment of diseases and for the production of delicate dental devices. However, reproducible outcomes depend not only on clinical technique but also on system-level factors central to optomechatronics how energy is delivered, sensed, and regulated in the presence of intraoral variability. Stomatology’s complexity and requirement for customized treatment make laser applications attractive across domains such as photobiomodulation, caries removal, and fabrication of dental implants and invisible braces, where accuracy, efficiency, and minimally invasive workflows are often reported. This review synthesizes laser success in oral medicine from both tissue removal and reconstruction perspectives, mapping common modalities to delivery architectures, controllable parameters including spot size, fluence or irradiance, pulse structure, repetition rate, scan speed, and dwell time, and candidate feedback signals. In addition, we highlight the intertwinement of lasers and digitalization, including artificial intelligence–enabled planning, robotic or digitally guided laser treatments, and three-dimensional laser printing of customized devices, with emphasis on integration challenges such as dosimetry reporting consistency, feedback reliability, motion compensation, latency, and safety interlocks.

Abstract Objective To investigate the knowledge, attitudes, and practices (KAP) of the guardians of children and adolescents aged 6–12 years in eight cities across China regarding three myopia control interventions (0.01% atropine eye drops, spectacles, and contact lenses) and analyze the influencing factors. Methods A KAP questionnaire on basic knowledge, attitudes, and practices regarding myopia was developed through a literature review and expert consultation. An online survey was administered to guardians of children aged 6–12 years across eight selected cities, and the data were analyzed using SPSS 27.0. Results Among the 1,509 valid questionnaires collected, 48.1% were from the guardians of myopic children; this group exhibited a significant difference from the guardians of non-myopic children on basic myopia questions (U = 301754.0, W = 564929.0, P < 0.05), with the former (40 (35, 47)) scoring slightly higher than the latter (39 (34, 46)). Knowledge of spectacles and contact lenses was linked to positive attitudes and compliant behaviors ( P < 0.001), with favorable attitudes predicting higher compliance ( P < 0.05). Regarding 0.01% atropine eye drops, knowledge was positively correlated with attitude (r = 0.475, P < 0.001), but neither was significantly correlated with behavior ( P > 0.05). Common pitfalls in the usage of 0.01% atropine eye drops included discontinuing medication and transferring it to others. KAP scores were influenced by the demographics of the guardians, with higher education, urban residence, and an age range of 35–49 years being associated with higher KAP scores. Significant intercity disparities were observed, with Beijing demonstrating the highest adherence to atropine and Changsha exhibiting the poorest spectacle use among the surveyed cities. While clinical consultations remained the predominant information channel, the high valuation of digital media underscores their potential as a scalable complementary strategy to bridge existing knowledge gaps. Conclusion The use of spectacles and contact lenses exhibited robust KAP alignment, whereas the use of 0.01% atropine manifested a critical knowledge-behavior disconnect characterized by prevalent self-discontinuation. Higher education, urban residence, and middle age predicted better KAP scores, whereas significant intercity disparities reflected a "prevalence–awareness paradox" favoring cities whose medical centers were early adopters of 0.01% atropine for myopia control. These findings underscore the necessity of stratified educational interventions—particularly digital health education delivered by ophthalmologists and medical students—to bridge the information gaps and ensure equitable myopia guidance across diverse populations. Trial Registration Not applicable.

Cytotoxic CD8+ T-cells play central roles in tumor immunotherapy. Understanding the mechanisms that regulate development, differentiation, and functions of cytotoxic CD8+ T-cells leads to the development of better immunotherapies. By combining primary T-cell culture and a syngeneic mouse tumor model with both genome-wide and custom CRISPR/Cas9 screenings, we systematically identified genes and pathways that regulate PD-1 expression and functions of CD8+ T-cells. Among them, inactivation of a key enzyme in glycoconjugate biosynthesis, beta 1,4-galactosyltransferase 1 (B4GALT1), leads to significantly enhanced T-cell receptor (TCR) activation and functions of CD8+ T-cell. Interestingly, suppression of B4GALT1 enhances functions of TCR-T-cells, but has no effect on chimeric antigen receptor T (CAR-T) cells. We systematically identified the substrates of B4GALT1 on CD8+ T-cell surface by affinity purification and mass spectrometry analysis, which include protein components in both TCR and its co-receptor complexes. The galactosylation of TCR and CD8 leads to reduced interaction between TCR and CD8 that is essential for TCR activation. Artificially tethering TCR and CD8 by a TCR-CD8 fusion protein could bypass the regulation of B4GALT1 in CD8+ T-cells. Finally, the expression levels of B4GALT1 normalized to tumor-infiltrated CD8+ T-cells in tumor microenvironment are significant and negatively associated with prognosis of human patients. Our results reveal the important roles of protein N-glycosylation in regulating functions of CD8+ T-cells and prove that B4GALT1 is a potential target for tumor immunotherapy.

Anomaly detection (AD) is a fundamental task of critical importance across numerous domains. Current systems increasingly operate in rapidly evolving environments that generate diverse yet interconnected data modalities—such as time series, system logs, and tabular records—as exemplified by modern IT systems. Effective AD methods in such environments must therefore possess two critical capabilities: (1) the ability to handle heterogeneous data formats within a unified framework, allowing the model to process and detect multiple modalities in a consistent manner during anomalous events; (2) a strong generalization ability to quickly adapt to new scenarios without extensive retraining. However, most existing methods fall short of these requirements, as they typically focus on single modalities and lack the flexibility to generalize across domains. To address this gap, we introduce a novel paradigm: In-Context Anomaly Detection (ICAD), where anomalies are defined by their dissimilarity to a relevant reference set of normal samples. Under this paradigm, we propose ICAD-LLM, a unified AD framework leveraging Large Language Models' in-context learning abilities to process heterogeneous data within a single model. Extensive experiments demonstrate that ICAD-LLM achieves competitive performance with task-specific AD methods and exhibits strong generalization to previously unseen tasks, which substantially reduces deployment costs and enables rapid adaptation to new environments. To the best of our knowledge, ICAD-LLM is the first model capable of handling anomaly detection tasks across diverse domains and modalities.

Owing to the rapid advancements in smart agriculture, the importance of developing sensors for agricultural digitization is increasing. Heavy metal ions, as detrimental variables, pose a major hurdle in agricultural development, food safety, and human health. Herein, electrolyte-gated tetraphenylporphyrin (TPP)-functionalized graphene field-effect transistors (GFETs), i.e., G-TPP FETs, were developed for the sensitive and reliable 25 °C detection of heavy metal ions at the solid–liquid interface of the G-TPP FETs. The central nitrogen atoms of the porphyrin skeleton act as ideal pockets for metal ion incorporation, endowing the G-TPP FETs with high sensitivity toward Cd2+, Cu2+, Fe3+, Mn2+, and Ni2+. The G-TPP FET sensitivity toward Fe3+ is more than double that of nonfunctionalized GFETs. Furthermore, the G-TPP FETs exhibit better reproducibility (relative standard deviation = 8.5) and a wide sensing range (1 nM–1 mM) for Cd2+. The sensitivity of the G-TPP FETs to the changes in the gate potential at the Dirac point in various heavy metal ionic solutions was systematically investigated. Moreover, the charge transfer between graphene and TPP or metalated-TPP was validated based on density functional theory simulations. Thus, this study provides a foundation for the development of next-generation agricultural sensors toward enhanced tracing systems of agricultural products to ensure better health and safety.

<title>Abstract</title> <bold>Objective</bold> This study aims to investigate the clinical significance and correlation with pregnancy outcomes of the abnormal pulsatility index (PI) of the fetal middle cerebral artery (MCA) as detected by ultrasonography. <bold>Methods</bold> A total of 41 cases with abnormal fetal MCA-PI (including five deaths) at the Maternal and Child Health Hospital of Haidian District, Beijing, were prospectively collected from July 2021 to July 2024, and 72 cases with normal fetal MCA-PI during the same period were selected as the control group. The differences in blood flow parameters between the two groups were compared, and the correlation between abnormal fetal MCA-PI and fetal pregnancy outcomes was analysed. Finally, the receiver operating characteristic curve was used to evaluate the predictive value of abnormal MCA-PI for adverse pregnancyoutcomes. <bold>Results</bold> Statistically significant differences were observed ( <italic>P</italic> &lt; 0.05) in the comparative analysis of ultrasound parameters (MCA-PI, MCA-resistance index [RI], MCA-systolic-to-diastolic ratio [S/D], umbilical artery [UA]-PI, UA-RI, UA-S/D and cerebroplacental ratio [CPR]) between the abnormal MCA-PI group (n = 36) and the normal MCA-PI group (n = 72). Specifically, MCA-PI, MCA-RI and MCA-S/D were significantly lower and UA-PI, UA-RI and UA-S/D were elevated in the abnormal group relative to in the normal group. CPR in the abnormal group was significantly lower than that in the normal group. The normal and abnormal MCA-PI groups showed statistically significant differences ( <italic>P</italic> &lt; 0.05) in clinical parameters (neonatal birth weight, Apgar score, umbilical cord hypercoiling, placental thickening, eclampsia, fetal distress, fetal growth restriction and preterm birth) but not in the incidence of UA occlusion ( <italic>P</italic> &gt; 0.05). Compared with the normal group, the abnormal MCA-PI group had a significantly higher risk of adverse pregnancy outcomes, with the risk of preterm birth being 5.6 times higher. The proportion of neonates with low birth weight in the abnormal MCA-PIgroup reached 44.4%. Amongst the 41 cases of fetuses with abnormal MCA-PI, statistically significant differences were observed in neonatal birth weight and Apgar scores across different pregnancy outcomes ( <italic>P</italic> &lt; 0.05), whereas no significant difference was found in the gestational week at diagnosis ( <italic>P</italic> &gt; 0.05). Neonatal birth weight and Apgar scores in the abnormal MCA-PI group were significantly lower than those in the normal group, with a trend towards early gestational weeks at ultrasound diagnosis. The area under the curve for predicting adverse pregnancy outcomes using abnormal MCA-PI was 0.743, with a sensitivity of 86. 1%. <bold>Conclusions</bold> Abnormal MCA-PI is a sensitive and effective indicator for evaluating fetal blood oxygen supply and has a high predictive value for adverse pregnancy outcomes.

Mesenchymal stem cells (MSCs) are widely used in regenerative medicine, including the treatment of pulmonary fibrosis. However, implanted MSCs disappear within days, constraining therapeutic efficacy, which is largely attributed to nutrient deprivation. In this study, we established glycogen metabolism engineering strategies in mammalian cells. By expressing a functionally optimized glycogen synthase (GYSmut), MSCs could accumulate large amounts of glycogen rapidly as a reserve substance. Glycogen engineering significantly improved the survival of MSCs during starvation both in vitro and in vivo, enhancing cell viability post-implantation and their therapeutic efficacy in pulmonary fibrosis. Glycogen-engineered MSCs may serve as chassis cells for further applications. Our research highlights the importance of glucose metabolism regulation in cell-based therapy and demonstrates the great potential for the metabolic engineering of MSCs and other therapeutic cells.