Pancreatic adenocarcinoma (PAAD) remains highly lethal because of chemotherapy resistance and immunosuppressive microenvironments. Tertiary lymphoid structures (TLSs) were analysed in PAAD to develop personalised therapeutic strategies. Nine TLS‐related genes ( CCR6 , CD1d , CD79B , CETP , EIF1AY , LAT , PTGDS , RBP5 and SKAP1 ) were selected for integrative analysis of TLS status in relation to clinical outcomes, immune cell infiltration, tumour mutational burden (TMB) and drug resistance. High TLS scores (TLS_H) were associated with improved overall survival (OS) and progression‐free survival (PFS), independent of age or tumour grade. Twelve immune cell types differed across TLSs. Single‐cell RNA‐seq analysis revealed that the 9 TLS‐related genes were enriched in distinct immune cell populations. Combining TLS and TMB improved survival prediction. Notably, the TLS_H group demonstrated enhanced sensitivity to chemotherapeutics including AZD8055, axitinib, vorinostat, nilotinib, camptothecin and paclitaxel. Real‐time fluorescent quantitative PCR (RT‐qPCR) validation in Mia PaCa2 and Jurkat cells indicated that LAT , RBP5 and SKAP1 may play important roles in modulating sensitivity to these chemotherapeutics. These findings establish TLS as a potential biomarker for PAAD, enabling personalised chemotherapy selection by integrating immune contexture and genomic drivers to improve clinical outcomes.

Pontocerebellar Hypoplasia (PCH) is a rare autosomal recessive hereditary neurological degenerative disease. To elaborate upon the clinical phenotypes of PCH and explore the correlation between TOE1 gene mutations and clinical phenotype, we analyze the clinical and genetic features of a Chinese infant afflicted with pontocerebellar dysplasia accompanied by gender reversal with bioinformatics methods. The main clinical features of this infant with TOE1 gene mutation included progressive lateral ventricle widening, hydrocephalus, severe postnatal growth retardation, and hypotonia, and simultaneously being accompanied by 46, XY female sex reversal. Whole exome sequencing revealed a compound heterozygous mutation in the TOE1 gene (c.299T > G, c.1414T > G), with the protein homology modeling-generated structure predicting a pathogenic variation, which is closely related to the clinical manifestations in the patient. The new mutation sites, c.299T > G and c.1414T > G, in the TOE1 gene are pathogenic variants of pontocerebellar hypoplasia type 7.

Background: Non-alcoholic steatohepatitis (NASH), a prominent driver of hepatocellular carcinoma (HCC) besides virus and alcohol, induces a series of complex liver structural and immune microenvironment changes, which make the early diagnosis and treatment of NASH-associated HCC (NASH-HCC) more challenging. This study aims to identify signature genes and explore the role of immune cell infiltration in NASH-HCC to improve early detection and prognosis assessment. Methods: Differential gene and immune cell infiltration are important indicators for predicting the progress of oncology and responsiveness of tumor patients to immunotherapy, usually confirmed through biopsy tests with poor patient compliance. To obtain a highly correlated signature gene set and validate immune cell infiltration status, the GSE164760 and GSE102079 datasets from the Gene Expression Omnibus (GEO) database were analyzed using machine learning algorithms. Feature genes were identified based on differentially expressed genes and key modular genes identified by weighted gene co-expression network analysis (WGCNA). The signature genes were screened using the least absolute shrinkage and selection operator (LASSO), random forest, and support vector machine recursive feature elimination (SVM-RFE) machine learning algorithms. Subsequently, the signature genes were subjected to diagnostic efficacy tests, gene set enrichment analysis, immune cell infiltration assessment and real-time reverse transcription polymerase chain reaction (RT-qPCR) validation. Results: Six signature genes were identified, including C-C motif chemokine ligand 14 (CCL14), C-type lectin domain family 4 member G (CLEC4G), ficolin-2 (L-ficolin, FCN2), insulin-like growth factor binding protein 3 (IGFBP3), C-X-C motif chemokine ligand 14 (CXCL14), and vasoactive intestinal polypeptide type I receptor (VIPR1). The area under the receiver operating characteristic (ROC) curve for the six signature genes was between 0.927–0.958, and the calibration curves also indicated that they had high prediction accuracy. Six signature genes were positively associated with NASH pathological process pathways including butyric acid metabolism and fatty acid degradation. The infiltration of immune cells such as M2-type macrophages was significantly positively correlated with the signature genes. RT-qPCR revealed a significant decrease in the expression of CLEC4G and IGFBP3 in the NASH-HCC model. Conclusions: CLEC4G and IGFBP3 hold potential as biomarkers for clinical surveillance, offering new insights for early detection and prognosis evaluation.

In this study, a green and efficient extraction methodology was developed by leveraging the unique properties of chitosan—namely its non-toxicity, biocompatibility, and adhesive nature—to enhance the recovery of bioactive ingredients from Forsythia suspensa leaves. The core mechanism involves the formation of complexes between chitosan and the target bioactive ingredients, which significantly boosts their extraction efficiency. To substantiate this mechanism, comprehensive characterization was performed using Powder X-ray Diffraction (PXRD), Fourier Transform Infrared Spectroscopy (FT-IR), Differential Scanning Calorimetry (DSC), Scanning Electron Microscopy (SEM), and molecular docking analyses. The results provided robust evidence of a strong interaction between chitosan and the bioactive ingredients, leading to a marked enhancement in both the stability and aqueous solubility of the target compounds. For process optimization, a multi-objective approach was implemented using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to simultaneously maximize the extraction yields of phillyrin and forsythoside A. The algorithm identified the optimal parameters as a leaf-to-chitosan mass ratio of 10:11.75, a solid-to-liquid ratio of 1:52 g/mL, a temperature of 80 °C, and a duration of 120 min. Under these optimized conditions, the corresponding extraction yields for phillyrin and forsythoside A were 1.68 ± 0.16% and 3.23 ± 0.27%, respectively. These findings collectively indicate that chitosan-assisted extraction represents a highly promising and advanced technology for the sustainable and effective extraction of bioactive ingredients from botanical sources.

Titanium-based implants are predominantly adopted in orthopedic and dental applications, yet their clinical performance is constrained by enduring challenges such as stress shielding, infection susceptibility, and inadequate osseointegration. To address these hurdles, recent advances have shifted titanium implant design from static biomimetic models toward dynamic, bioadaptive systems capable of actively modifying their architectural, mechanical, and surface properties after implantation. These systems can respond adaptively to specific pathophysiological microenvironments or be activated by external energy sources (e.g., light, ultrasound, electricity, or magnetism), thus providing on-demand biofunctionalities, such as antibacterial, pro-angiogenic, osteogenic, and immune/metabolic regulatory effects, ultimately mitigating complications (e.g., infection, inflammation) while accelerating osteoregeneration and osteointegration. In this Perspective, we propose a strategic framework to guide the design and development of next-generation titanium implants aligned with this trend. It highlights the emerging need to converge a deeper understanding of implant-biology interplays with synergistic advances from materials science (e.g., metamaterial and stimuli-responsive interface design) and cutting-edge bone biology (e.g., immunometabolic and neuro-osseous engineering). This interdisciplinary integration is aimed at enabling expedited, robust, bioadaptive regeneration regimens, particularly for challenging bone defects such as infected, osteoporotic, or diabetic conditions.