ObjectiveTo investigate the effect and underlying mechanism of the Wulao Qisun prescription on pathological new bone formation in ankylosing spondylitis （AS）. MethodsSynovial fibroblasts were isolated from the hip joints of AS patients and observed under a microscope to assess cell morphology. The cells were identified using immunofluorescence staining. The isolated AS fibroblasts were divided into blank group， low drug-containing serum group， medium drug-containing serum group， high drug-containing serum group， and positive drug group. After drug intervention， cell proliferation was measured using the cell counting kit-8 （CCK-8） assay to observe fibroblast growth and determine the optimal intervention time. Alkaline phosphatase （ALP） activity was measured using the alkaline phosphatase assay. Protein expression of osteocalcin （OCN）， osteopontin （OPN）， and runt-related transcription factor 2 （Runx2） was detected by Western blot. The mRNA expression levels of Wnt5a， β-catenin， and Dickkopf-1 （DKK-1） were measured by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsCompared with the blank group， each drug-containing serum group of Wulao Qisun prescription and the positive drug group inhibited the proliferation of AS fibroblasts and reduced ALP expression （P<0.01）. Compared with the blank group， the low drug-containing serum group of Wulao Qisun prescription downregulated β-catenin mRNA expression （P<0.05）. The medium and high drug-containing serum groups and the positive drug group significantly downregulated Wnt5a and β-catenin mRNA expression （P<0.05， P<0.01）， with the positive drug group showing the most pronounced effect （P<0.01）. The high drug-containing serum group and the positive drug group significantly upregulated DKK-1 mRNA expression （P<0.01）. Compared with the blank group， the low drug-containing serum group of Wulao Qisun prescription inhibited the expression of OPN and Runx2 proteins （P<0.05， P<0.01）， while the medium and high drug-containing serum groups and the positive drug group inhibited the expression of OCN， OPN， and Runx2 proteins （P<0.05， P<0.01）. ConclusionThe Wulao Qisun prescription can inhibit the proliferation and osteogenic differentiation of AS fibroblasts， thereby delaying the formation of pathological new bone in AS. The possible mechanism involves the regulation of Wnt/β-catenin-related gene expression， further inhibiting the transcription of downstream target genes.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

The Expert Consensus on the Deployment of DeepSeek in Medical Institutions serves as a detailed guideline for the deployment of DeepSeek in medical institutions. It was developed by experts in the fields of healthcare， hospital management， medical information， health policy， law， and medical ethics from nearly 30 leading domestic medical and academic research institutions， based on relevant domestic and international laws and regulations as well as the practices of medical institutions. It aims to provide medical institutions with a scientific， standardized， and secure deployment guideline to ensure that the application of artificial intelligence （AI） technologies in healthcare， including but not limited to DeepSeek， conforms to the unique characteristics of the healthcare industry and effectively promotes the improvement of medical service levels. From the three aspects of pre-deployment evaluation， deployment implementation， and post-deployment management and monitoring， the key factors that medical institutions should consider when introducing DeepSeek were elaborated in detail， including medical demand compatibility， technical capabilities and infrastructure， legal and ethical risks， data preparation and management， model selection and optimization， system integration and training， performance monitoring and continuous optimization， risk management and emergency response， as well as compliance review and evaluation. This provides a comprehensive deployment framework for medical institutions to ensure the safety and effectiveness of technology applications.