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Chinese medicine resources are the crystallization of traditional Chinese culture, and more and more people are choosing Chinese medicine services for their health. To address the problems of pluralistic heterogeneity, waste of service resources, and lagging demand response in the resource allocation model for traditional Chinese medicine (TCM) services, a deep reinforcement learning-based resource allocation method for TCM services is proposed. To address the fragmentation of TCM service resources, this paper presents a TCM service resource association method based on improved spectral clustering and establishes a good resource-demand matching model. For the problem of TCM service resource allocation after resource association, we establish a TCM service resource allocation model and collaboratively solve the TCM service resource allocation problem via the deep reinforcement learning method. The results show that the proposed solution can accelerate the demand response of TCM service resources, effectively reduce the cost of TCM services for patients, improve the quality of TCM services, and satisfy the demand for TCM services for patients. [ABSTRACT FROM AUTHOR]

Background: Lip behaviors can lead to maxillofacial developmental disorders such as anterior open bite, posterior crossbite, increased overjet, and a higher risk of developing a Class II malocclusion. However, lip-sucking, a behavior often underreported and overlooked, may adversely affect the periodontal health of permanent teeth in adolescents under extreme conditions if not promptly identified and managed. Case presentation: We report a unique case of an 11-year-old boy with a severe periodontal-endodontic lesion on tooth 32, caused by prolonged, high-frequency, and high-intensity lip sucking. Initial clinical examination revealed gingival recession, Grade III mobility, deep periodontal pocket, and alveolar bone loss without obvious pathogenesis. The therapeutic schedule encompassed behavioral modification, the repeated application of various dental splints due to splint breakage caused by strong lip-sucking habits, and root canal therapy. The periodontal condition and tooth stability were improved through collaborative management. At the 18-month follow-up, improvements in dental stability, alveolar bone density, and reduced periodontal pocket depth were observed. Conclusions: This is the first case report exploring the complex relationship between lip-sucking and dental health, emphasizing that severe oral habits can lead to serious dental consequences. Timely identification and intervention in managing oral habits can halt disease progression and ensure favorable outcomes. Additionally, this report offers treatment guidelines and recommendations for severe dental diseases caused by detrimental oral habits. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the most common intracranial malignancy, but current treatment options are limited. Super-enhancers (SEs) have been found to drive the expression of key oncogenes in GBM. However, the role of SE-associated long non-coding RNAs (lncRNAs) in GBM remains poorly understood. Here, we screened for an up-regulated lncRNA-SLCO4A1-AS1 expressed in GBM by analyzing data from GSE54791, GSE4536 and TCGA. We systematically analyzed its relationship with clinical characteristics, prognosis, epigenetics, tumor microenvironment (TME), biological functions, and transcription factors. We found that SE-driven SLCO4A1-AS1 was significantly upregulated in GBM and correlated with poor prognosis. Knockdown of SLCO4A1-AS1 decreased glioma cell proliferation, invasive ability, self-renewal ability, and increased apoptosis. Epigenetic analysis revealed that SOX2 and SE could drive SLCO4A1-AS1 expression. In vitro experiments further demonstrated that GBM cells with high SLCO4A1-AS1 expression were more sensitive to VX-11e, and overexpression of SLCO4A1-AS1 could reverse the inhibitory effect of VX-11e on GBM cells. In conclusion, this study revealed that SE-driven SLCO4A1-AS1 may be a potential therapeutic target in GBM. [ABSTRACT FROM AUTHOR]

Background: Glioma is the most common intracranial malignancy, and the available treatment options are poor. Long noncoding RNAs (lncRNAs) have been reported to be involved in the malignant progression of glioma. The role of ZNF503-AS2 in glioma has not been reported. Methods: We screened ZNF503-AS2 with upregulated expression in glioblastoma (GBM) by analyzing the TCGA, CGGA and GTEx databases. Single sample gene set enrichment analysis (ssGSEA) was used to calculate the enrichment of immune cells and signaling pathways in glioma samples. Single-cell datasets were used to analyze the distribution of ZNF503-AS2. In vitro experiments were used to investigate the biological function of ZNF503-AS2. Results: ZNF503-AS2 was highly expressed in glioma and was associated with poor prognosis, malignant progression and infiltration of immunosuppressive cells. Single-cell transcriptomic analysis showed that ZNF503-AS2 was mainly expressed in macrophages and tumor cells. Further analysis revealed that immunotherapy may have better efficacy in patients with low ZNF503-AS2 expression. In vitro experiments showed that knockdown of ZNF503-AS2 reduced the proliferation, invasion and migration ability of glioma cells, induced G2/M cell cycle arrest and promoted apoptosis. Conclusions: ZNF503-AS2 might be a valuable biomarker for predicting the prognosis of glioma patients and a potential target for glioma therapy. [ABSTRACT FROM AUTHOR]

The increasing frequency and severity of drought, driven by global climate change, has emerged as a critical factor constraining the growth of landscaping trees in urban ecosystems. The local or non-local status of tree species is an important driver of plant function traits, which regulate plant performance. However, the differential impact of varying drought intensities on the functional traits of both non-local and local trees remains poorly understood. This study investigated the responses of leaf and root traits of seven typical tropical landscaping tree seedlings (three local species and four non-local species) to simulated drought conditions in a year-long greenhouse experiment. The results showed that drought significantly increased the specific leaf area, leaf thickness, and root exudate rate, while reducing root nitrogen content and leaf dry matter content, with differences observed between local and non-local species. The non-local species exhibited pronounced fluctuations in leaf and root traits between control and drought conditions. Local species tended to enhance the relationship between leaves and roots under drought, while non-local species showed a weakening of this relationship. Principal component analysis revealed that local species adopted a more conservative strategy under control conditions and a more acquisitive strategy under drought, while root strategies remained stable across conditions. The subordination function method in fuzzy mathematics identified Terminalia neotaliala (non-local) as the most drought-resistant species and Artocarpus heterophyllus (non-local) as the least drought-resistant species. Non-local species demonstrated greater drought resistance in leaf traits compared to local species, but the opposite was observed for root traits. These results underscore the importance of understanding the species-specific responses of local and non-local trees to drought stress. These findings provide a scientific basis for developing effective screening and management protocols for drought-resistant landscaping tree species. [ABSTRACT FROM AUTHOR]