Objective: To enhance the ability of nanoparticles to target and bind tumor cells by constructing a neutrophil hitchhiking system based on hyaluronic acid (HA)-modified dual-drug loaded lipid nanoparticles. Methods: Lipid nanoparticles (LNPs) were prepared using microfluidic technology, and the nitrogen/phosphate (N/P) ratio, flow rate ratio, and drug-to-lipid ratio were optimized. HA-modified LNPs (HA-LNPs) were prepared and characterized. The interaction between the nanoparticles and tumor cells was evaluated through in vitro cell experiments. Results: The optimal preparation conditions for LNPs are N/P=8, flow rate ratio=5, and drug-to-lipid ratio=1∶30 (w∶w). HA-LNPs has a particle size of (177.28±2.41) nm, a polydispersity index (PDI) of 0.198±0.10, and an siRNA encapsulation efficiency of (91.37±0.47)%. The optimal binding rate with neutrophils was (98.64±2.34)%. Conclusion: An HA-modified dual-drug loaded lipid nanoparticle-neutrophil hitchhiking system was successfully constructed, enhancing the synergistic anti-tumor activity of the nanomedicine and the uptake of nanoparticles by tumor cells, providing a novel delivery strategy for targeted therapy of bone marrow tumors.

Background With the progression of industrialization, an increasing number of emerging contaminants are entering aquatic environments, posing significant threats to the safety of drinking water. Therefore, establishing a system for identifying unknown hazardous factors and implementing safety warning mechanisms for drinking water is of paramount importance. Among these efforts, non-target screening plays a critical role, but its effectiveness is largely constrained by the scope of coverage of sample pre-treatment methods. Objective To integrate modern chromatography/mass spectrometry techniques with advanced data mining methods to develop a non-discriminatory sample pre-treatment method for comprehensive enrichment of unknown contaminants in drinking water, laying a technical foundation for the discovery and identification of unknown organic hazardous factors in drinking water. Methods A non-discriminatory pre-treatment method based on supramolecular and solid-phase extraction was developed. The final target compounds including 333 pesticides, 194 pharmaceuticals and personal care products (PPCPs), and 59 per- and polyfluoroalkyl substances (PFASs) were used for optimizing the pre-treatment method, confirming its coverage. The impacts of different eluents on the absolute recovery rates of target compounds were compared to select the conditions with the highest recovery for sample pre-treatment. The effects of different supramolecular solvents and salt concentrations on target compound recovery were also evaluated to determine the most suitable solvent and salt concentration. Results The solid-phase extraction elution solvents, supramolecular extraction solvents, and salt concentrations were optimized based on the target compound recovery rates. The optimal recovery conditions were achieved using 2 mL methanol, 2 mL methanol (containing 1% formic acid), 2 mL ethyl acetate, 2 mL dichloromethane, hexanediol supramolecular solvent, and 426 mg salt. The detection method developed based on these conditions showed a good linear relationship for all target compounds in the range of 0.1-100.0 ng·mL⁻¹, with R² > 0.99. The method’s limit of detection ranged from 0.01 ng⁻¹ to 0.95 ng⁻¹, and 95% of target compounds were recovered in the range of 20%-120%, with relative standard deviation (RSD) less than 30%, indicating good precision. Conclusion The combined pre-treatment method of solid-phase extraction and supramolecular solvent extraction can effectively enrich contaminants in drinking water across low, medium, and high polarities, enabling broad-spectrum enrichment of diverse trace contaminants in drinking water. It provides technical support for broad-spectrum, high-throughput screening and identification of organic pollutants in drinking water, and also serves as a reference for establishing urban drinking water public safety warning systems.

BACKGROUND: Death burden of stroke is severe with over one-third rural residents in China, but there is still a lack of specific national and high-quality reports on the urban-rural differences in stroke burden, especially for subtypes. We aimed to update the understanding of urban-rural differences in stroke deaths. METHODS: This is a descriptive observational study. Data from the national mortality surveillance system, which covers 323.8 million with 605 disease surveillance points (DSPs) across all 31 provinces, municipalities, and autonomous regions in China. All deaths from stroke as the underlying cause from 2015 to 2020 according to DSPs. Crude mortality rate and age-standardized mortality rate (ASMR) were estimated through DSPs. Average annual percentage change was used to explain the change in mortality rate. RESULTS: From 2015 to 2020, the majority of deaths from all stroke subtypes occurred in rural areas. There were significant differences between the changes of urban and rural ASMRs. On the whole, the changes in urban areas were evidently better, and the ASMR differences were basically expanding. Stroke ASMR in urban China decreased by 15.5%. The rural ASMR of ischemic stroke increased by 12.9%. The rural and urban ASMRs of intracerebral hemorrhage decreased by 24.9% and 27.4%, and those of subarachnoid hemorrhage decreased by 29.5% and 40.4%, respectively. The highest ASMRs of all stroke subtypes and the increasing trend of ischemic stroke ASMR make rural males the focus of stroke management. CONCLUSIONS The death burden of stroke varies greatly between urban and rural China. Rural residents face unique challenges.
Humans ; China/epidemiology* ; Stroke/mortality* ; Rural Population/statistics & numerical data* ; Male ; Female ; Urban Population/statistics & numerical data* ; Middle Aged ; Aged ; Aged, 80 and over ; Adult

OBJECTIVE: To investigate the effect of stretch on long non-coding RNA taurine upregulated gene 1 (TUG1)-mediated miR-545-3p/cannbinoida receptor 2 (CNR2) pathway regulating bone regeneration in the distraction area of rats during distraction osteogenesis. METHODS: Thirty-six 10-week-old male Sprague Dawley rats were randomly divided into 3 groups ( n=12 in each group): group A (femoral fracture+injection of interfering RNA), group B (distraction osteogenesis+injection of interfering RNA), and group C (distraction osteogenesis+injection of TUG1). Groups A and B were injected with 60 μg of interfering RNA at the beginning of incubation period (immediate after operation), the beginning of distraction phase (7 days after operation), and the end of distraction phase (21 days after operation), and group C was injected with 60 μg of synthetic TUG1 in vivo interfering sequence at the same time. The general situation of rats in each group was observed during the experiment. The mineralization of fracture space or distraction area was observed by X-ray films at 21, 35, and 49 days after operation. At 49 days after operation, the samples of the distraction area were taken for HE staining to observe the mineralization, and real-time fluorescence quantitative PCR (qRT-PCR) was used to detect the expressions of osteoblast-related genes such as TUG1, miR-545-3p, CNR2, alkaline phosphatase (ALP), osteocalcin (OCN), and osteopontin (OPN). Blood samples were collected from the abdominal aorta of the rats, and the expressions of ALP and C terminal telopeptide of type Ⅰ (CTX-Ⅰ) protein were detected by ELISA assay. RESULTS: The results of X-ray film and HE staining observations showed that osteogenesis in group C was superior to groups A and B at the same time point. The results of qRT-PCR showed that the relative mRNA expressions of TUG1, CNR2, ALP, OCN, and OPN in group C were significantly higher than those in group A and group B, and the relative mRNA expression of miR-545-3p in group C was significantly lower than that in group A and group B ( P<0.05). The relative mRNA expressions of TUG1 and ALP in group B were significantly higher than those in group A, and the relative mRNA expression of miR-545-3p in group B was significantly lower than that in group A ( P<0.05). There was no significant difference in the relative mRNA expressions of CNR2, OCN, and OPN between group A and group B ( P>0.05). The results of ELISA showed that the expressions of ALP and CTX-Ⅰ protein were significantly higher in group C than in group A and group B, and in group B than in group A ( P<0.05). CONCLUSION Under the action of stretch, the expression of TUG1 in the femoral distraction area of rats increases, which promotes the expression of CNR2 by inhibiting the expression of miR-545-3P, which is helpful to the mineralization of the extension area and osteogenesis.
Animals ; MicroRNAs/genetics* ; Rats, Sprague-Dawley ; Male ; Osteogenesis, Distraction/methods* ; Rats ; RNA, Long Noncoding/metabolism* ; Osteopontin/genetics* ; Osteogenesis ; Bone Regeneration ; RNA, Small Interfering/genetics* ; Osteocalcin/genetics* ; Alkaline Phosphatase/metabolism* ; Osteoblasts/cytology* ; Signal Transduction ; Femoral Fractures/surgery*

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Objective To investigate the factors affecting the distribution of Pomacea and project the trends in the spread of suitable distribution areas of Pomacea in 2050 and 2070 in Dali Bai Autonomous Prefecture, so as to provide insights into Pomacea control in the prefecture. Methods The longitudes and latitudes of Pomacea sampling sites were captured based on Pomacea field survey data in 12 cities (counties) of Dali Bai Autonomous Prefecture from 2023 to 2024. A total of 19 climatic factors (annual mean temperature, mean diurnal range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest month, mean temperature of the coldest month, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, mean temperature of the warmest quarter, and mean temperature of the coldest quarter) and representative concentration pathways (RCPs) were retrieved from the world climate database (www.worldclim.org). All climatic variables were employed to create a maximum entropy (MaxEnt) model. The predictive accuracy of the model was assessed with the area under the receiver operating characteristic (ROC) curve (AUC), and the contributions of these 19 climatic factors to the distribution of Pomacea were analyzed in Dali Bai Autonomous Prefecture using Jackknife test. In addition, the suitable distribution areas of Pomacea were predicted with the MaxEnt model in Dali Bai Autonomous Prefecture in 2024 and in 2050 and 2070 under RCP4.5. Results Data pertaining to 91 Pomacea sampling sites were captured. ROC analysis revealed the MaxEnt model had an AUC value of 0.885 ± 0.088 for predicting the suitable distribution areas of Pomacea in Dali Bai Autonomous Prefecture. Of the 19 climatic factors, the maximum temperature of the warmest month had the highest contribution to the distribution of Pomacea in Dali Bai Autonomous Prefecture, followed by mean temperature of the driest quarter, mean temperature of the wettest quarter and minimum temperature of the coldest month. The suitable distribution area of Pomacea was predicted to be 14 555.69 km² in Dali Bai Autonomous Prefecture in 2024, and would expand gradually to the southeastern part of the prefecture in the future due to climatic factors. The suitable distribution areas of Pomacea were projected to expand to 21 475.61 km² in 2050 and 25 782.52 km² in 2070 in Dali Bai Autonomous Prefecture, respectively. Conclusions Temperature is an important contributor to the distribution of Pomacea in Dali Bai Autonomous Prefecture, and the suitable distribution area of Pomacea will gradually expand to the southeastern part of the prefecture in 2050 and 2070.

Objective To identify the multi-dimensional needs of symptom management for oral cancer patients based on the journey map,and provide references for optimizing the symptom management of oral cancer patients.Methods From September 2023 to March 2024,the purposive sampling was used to select 15 perioperative oral cancer patients from a tertiary A general hospital in Zhengzhou for semi-structured interviews.The content analysis method was used to analyze the data and create a patient journey map.Results According to the time axis of diagnosis and treatment,the symptom management of patients with oral cancer was subdivided into 22 themes including identifying abnormal symptoms,clarifying diagnosis,anxiety,fear and uncertainty,guilt,high-risk behavioral inertia solidification,diagnostic trust crisis and so on from 3 dimensions of task,emotion,and pain point,and a journey map was formed.Conclusion The journey of symptom management for patients with oral cancer is long and complex,and the needs of patients'physiological and psychological symptom management are dynamically changing.In the future,the digital intelligence of big data technology can be combined to achieve whole-process,personalized and precise symptom management to improve the quality of life of oral cancer patients.

There is controversy over the specific and non-specific components in the efficacy evaluation of acupuncture therapy.The placebo effect,as a key non-specific factor,needs to be clarified in terms of its mechanism and clinical value.This article reviewed the research progress in the placebo effect of acupuncture from three aspects:cognitive process,influencing factors,and mechanism.It focused on the regulatory effects of patient expectations,doctor-patient interaction,and individual differences on the effect,summarized key mechanisms such as endogenous opioid system,dopamine reward pathway,and neural projection of rostral anterior cingulate cortex to pontine nucleus,and pointed out the methodological limitations of current comfort acupuncture designs,in order to provide theoretical basis for the optimization of acupuncture clinical research models and the deepening of the effect mechanism.

OBJECTIVES: This study aimed to analyze the influence of drug factors on the efficacy of bisphosphonate for chronic nonbacterial osteomyelitis to provide a reference for clinical treatment and promote clinical rational drug use by evaluation of effectiveness and safety of bisphosphonate treatment of chronic nonbacterial osteomyelitis. METHODS: Literature on the treatment of chronic nonbacterial osteomyelitis by using bisphosphonate was collected and analyzed from PubMed, Medline, Embase, Cochrane, ISI Web of Knowledge, CNKI, VIP, and Wanfang databases. RESULTS: A total of 489 cases were collected, with an average complete response rate of clinical presentation, laboratory tests and imaging findings of 80.37%, 80.56% and 79.22%, respectively. Except for opadronate, risedronate, ibandronate, pamidronate, alendronate, neidronate and zoledronate showed good efficacy, and the average complete response rates were 100%, 100%, 81.64%, 87.50%, 69.23% and 69.23%, respectively.The study found that in the pamidronate group, the average complete response rate of 0.5-1 mg/kg (maximum single dose≤60 mg) subgroup and the frequency of administration once every 3 months subgroup were better than other subgroups. CONCLUSIONS Bisphosphonate could be used to treat chronic nonbacterial osteomyelitis, which of efficacy were affected by different drug types, dose and frequency of administration. The optimal dose and frequency of administration of pamidronate were 0.5-1 mg/kg (maximum single dose≤60 mg) and once every 3 months, respectively.
Osteomyelitis/drug therapy* ; Humans ; Diphosphonates/administration & dosage* ; Chronic Disease ; Bone Density Conservation Agents/administration & dosage* ; Female ; Pamidronate ; Middle Aged ; Male