OBJECTIVE To investigate the effect of Huangqin decoction （HQD）-based self-assembled nanoparticles （SAN） co-loaded with terbinafine （TBF） （TBF-HQD-SAN NPs） on the transdermal absorption of TBF. METHODS High-speed centrifugation combined with dialysis was used to separate HQD-SAN， and TBF-HQD-SAN NPs were obtained by loading TBF using the ultrasound magnetic stirring method； the particle size distribution， Zeta potential and polydispersity index （PDI） of the nanoparticle were characterized， and the encapsulation efficiency （EE） and drug loading （DL） of TBF were determined； using in vitro and in vivo transdermal experiments， the differences in transdermal performance between TBF-HQD-SAN NPs and TBF raw materials， as well as TBF and HQD-SAN physical mixture （TBF-HQD-SAN PM）， were compared and analyzed. RESULTS TBF- HQD-SAN NPs were spherical with a particle size of （177.60±2.57） nm， a PDI of 0.197 4±0.007 9， and a Zeta potential of （－14.63±0.85） mV. The EE and DL of TBF were （99.49±0.71）% and （3.22±0.10）% ， respectively. In vitro transdermal experiments， compared with TBF raw materials， the steady-state permeation rate （Jss） and skin retention of TBF-HQD-SAN NPs increased by 3.34 times and 27.56 times， respectively （P＜0.05）； compared with TBF-HQD-SAN PM， its Jss and skinretention were increased by 2.04 times and 7.44 times， respectively （P＜0.05）. In vivo transdermal experiments 69号） showed that， the area under the drug-time curve and the maximum concentration of TBF-HQD-SAN NPs increased by 2.13 times and 2.06 times respectively compared to TBF raw materials， and increased by 1.59 times and 1.65 times respectively compared to TBF-HQD-SAN PM （P＜0.05）. CONCLUSIONS TBF-HQD-SAN NPs can significantly enhance the in vitro and in vivo transdermal absorption efficiency and skin retention of TBF.

Periodontitis is a common oral disease caused by bacteria coupled with an excessive host immune response. Stem cell therapy can be a promising treatment strategy for periodontitis, but the relevant mechanism is complicated. This study aimed to explore the therapeutic potential of mitochondria from human embryonic stem cell-derived mesenchymal stem cells (hESC-MSCs) for the treatment of periodontitis. The gingival tissues of periodontitis patients are characterized by abnormal mitochondrial structure. Human gingival fibroblasts (HGFs) were exposed to 5 μg/mL lipopolysaccharide (LPS) for 24 h to establish a cell injury model. When treated with hESC-MSCs or mitochondria derived from hESC-MSCs, HGFs showed reduced expression of inflammatory genes, increased adenosine triphosphate (ATP) level, decreased reactive oxygen species (ROS) production, and enhanced mitochondrial function compared to the control. The average efficiency of isolated mitochondrial transfer by hESC-MSCs was determined to be 8.93%. Besides, a therapy of local mitochondrial injection in mice with LPS-induced periodontitis showed a reduction in inflammatory gene expression, as well as an increase in both the mitochondrial number and the aspect ratio in gingival tissues. In conclusion, our results indicate that mitochondria derived from hESC-MSCs can reduce the inflammatory response and improve mitochondrial function in HGFs, suggesting that the transfer of mitochondria between hESC-MSCs and HGFs serves as a potential mechanism underlying the therapeutic effect of stem cells.
Humans ; Gingiva/cytology* ; Fibroblasts/metabolism* ; Mitochondria/physiology* ; Mesenchymal Stem Cells/cytology* ; Animals ; Periodontitis/therapy* ; Mice ; Reactive Oxygen Species/metabolism* ; Inflammation ; Lipopolysaccharides ; Human Embryonic Stem Cells/cytology* ; Cells, Cultured ; Adenosine Triphosphate/metabolism* ; Male

Despite therapy with potent antiviral agents, chronic hepatitis B (CHB) patients remain at high risk of hepatocellular carcinoma (HCC). While metabolites have been rediscovered as active drivers of biological processes including carcinogenesis, the specific metabolites modulating HCC risk in CHB patients are largely unknown. Here, we demonstrate that baseline plasma from CHB patients who later developed HCC during follow-up exhibits growth-promoting properties in a case-control design nested within a large-scale, prospective cohort. Metabolomics analysis reveals a reduction in long-chain acylcarnitines (LCACs) in the baseline plasma of patients with HCC development. LCACs preferentially inhibit the proliferation of HCC cells in vitro at a physiological concentration and prevent the occurrence of HCC in vivo without hepatorenal toxicity. Uptake and metabolism of circulating LCACs increase the intracellular level of acetyl coenzyme A, which upregulates histone H3 Lys14 acetylation at the promoter region of KLF6 gene and thereby activates KLF6/p21 pathway. Indeed, blocking LCAC metabolism attenuates the difference in KLF6/p21 expression induced by baseline plasma of HCC/non-HCC patients. The deficiency of circulating LCACs represents a driver of HCC in CHB patients with viral control. These insights provide a promising direction for developing therapeutic strategies to reduce HCC risk further in the antiviral era.

Obesity usually exacerbates the immunosuppressive tumor microenvironment (ITME), hindering CD8⁺ T cell infiltration and function, which further represents a significant barrier to the efficacy of immunotherapy. Herein, a multifunctional liposomal system (CR-Lip) for encapsulating celastrol (CEL) was utilized to remodel obesity-related ITME and improve cancer immunotherapy, wherein Ginsenoside Rg3 (Rg3) was detected interspersed in the phospholipid bilayer and its glycosyl exposed on the surface of the liposome. CR-Lip had a relatively uniform size (116.5 nm), facilitating favorable tumor tissue accumulation through the interaction between Rg3 and glucose transporter 1 overexpressed in obese tumor cells. Upon reaching the tumor region, CR-Lip was found to induce the immunogenic cell death (ICD) of HFD tumor cells. Notably, the level of PHD3 in HFD tumor cells was effectively boosted by CR-Lip to effectively block metabolic reprogramming and increase the availability of major free fatty acids fuel sources. In vivo, experiments studies revealed that the easy-obtained nano platform stimulated enhanced the production of various cytokines in tumor tissues, DC maturation, CD8⁺ T-cell infiltration, and synergistic anticancer therapeutic potency with aPD-1 (tumor inhibition rate = 82.1%) towards obesity-related melanoma. Consequently, this study presented an efficacious approach to tumor immunotherapy in obese mice by encompassing tumor eradication, inducing ICD, and reprogramming metabolism. Furthermore, it offered a unique insight into a valuable attempt at the immunotherapy of obesity-associated related tumors.

The interest in covalent drugs has resurged in recent decades, spurring the development of numerous specialized computational docking tools to facilitate covalent ligand design and screening. Herein, we present CarsiDock-Cov, a new paradigm distinguishing itself as the first deep learning (DL)-guided approach for covalent docking. CarsiDock-Cov retains the core components of its non-covalent predecessor, leveraging a DL model pretrained on millions of docking complexes to predict protein-ligand distance matrices, along with a dedicated-designed geometric optimization procedure to convert these distances into refined binding poses. Additionally, it incorporates several key enhancements specifically tailored to optimize the protocol for covalent docking applications. Our approach has been extensively validated on multiple public datasets regarding the docking and screening of covalent ligands, and the results indicate that our approach not only achieves comparably improved applicability compared to its non-covalent predecessor, but also exhibits competitive performance against various state-of-the-art covalent docking tools. Collectively, our approach represents a significant advance in covalent docking methodology, offering an automated and efficient solution that shows considerable promise for accelerating covalent drug discovery and design.

OBJECTIVE: To explore the preventive effect of transcutaneous phrenic nerve stimulation on ventilator-induced diaphragmatic dysfunction (VIDD) in patients requiring invasive mechanical ventilation. METHODS: A randomized controlled trial was conducted. The patients requiring invasive mechanical ventilation admitted to the intensive care unit (ICU) of Jiaxing First Hospital from November 2022 to December 2023 were enrolled. Participants were randomized into the control group and the observation group using a random number table. The control group was given ICU standardized nursing intervention, including turning over and slapping the back, raising the head of the bed, sputum aspiration on demand, aerosol inhalation, oral care, and monitoring of airbag pressure and gastric retention, the observation group was given additional transcutaneous phrenic nerve stimulation intervention on the basis of ICU standardized nursing intervention. The stimulation intensity was set to 10 U, the pulse frequency was set to 40 Hz, and the stimulation frequency was set to 12 times/min. Transcutaneous phrenic nerve stimulation was administered once a day for 30 minutes each time, for a total of 5 days. Diaphragm thickening fraction (DTF) and arterial blood gas parameters on days 1, 3, and 5 of intervention were compared between the two groups. After 5 days of intervention, other parameters including the incidence of VIDD, duration of mechanical ventilation, and length of ICU stay were compared. RESULTS: A total of 120 patients requiring invasive mechanical ventilation were enrolled, with 16 dropouts (dropout rate was 13.33%). Ultimately, 51 patients in the control group and 53 patients in the observation group were analyzed. Baseline characteristics, including gender, age, body mass index (BMI), acute physiology and chronic health evaluation II (APACHE II) score, albumin (Alb), hemoglobin (Hb), and disease type, showed no significant differences between the two groups. DTF in both groups gradually increased over duration of intervention [DTF on days 1, 3, and 5 in the control group was (20.83±2.33)%, (21.92±1.27)%, and (23.93±2.33)%, respectively, and that in the observation group was (20.89±1.96)%, (22.56±1.64)%, and (25.34±2.38)%, respectively], with more significant changes in DTF in the observation group, showing time effects (F_time = 105.975, P < 0.001), intervention effects (F_intervention = 7.378, P = 0.008), and interaction effects (F_interaction = 3.322, P = 0.038). Arterial blood gas parameters did not differ significantly before intervention between the groups, but after 5 days of intervention, arterial partial pressure of oxygen (PaO₂) in the observation group was significantly higher than that in the control group [mmHg (1 mmHg≈0.133 kPa): 100.72±15.75 vs. 93.62±15.54, P < 0.05], and arterial partial pressure of carbon dioxide (PaCO₂) was significantly lower than that in the control group (mmHg: 36.53±3.10 vs. 37.69±2.02, P < 0.05). At 5 days of intervention, the incidence of VIDD in the observation group was significantly lower than that in the control group [15.09% (8/53) vs. 37.25% (19/51), P < 0.05], and both duration of mechanical ventilation and length of ICU stay were significantly shorter than those in the control group [duration of mechanical ventilation (days): 7.93±2.06 vs. 8.77±1.76, length of ICU stay (days): 9.64±2.35 vs. 11.01±2.01, both P < 0.05]. CONCLUSIONS Transcutaneous phrenic nerve stimulation can improve diaphragmatic and respiratory function in patients receiving invasive mechanical ventilation, reduce the incidence of VIDD, and shorten the duration of mechanical ventilation and length of ICU stay.
Humans ; Transcutaneous Electric Nerve Stimulation ; Respiration, Artificial/adverse effects* ; Diaphragm/physiopathology* ; Phrenic Nerve ; Intensive Care Units ; Male ; Female ; Middle Aged

Objective To explore the application of the DeepSeek large languagemodel in assessing prescription ration-ality and evaluating its implementation effectiveness.Methods A random sample of 5 099 outpatient and emergency prescrip-tion records from our hospital in a specific month of 2024 was collected.The DeepSeeK large language model employs vector data-base technology for prescription review.An evaluation metrics analysis was conducted between the DeepSeeK's reviews and phar-macist evaluations.Performance metrics including accuracy,precision,recall,specificity,and F1 were systematically calculated.Error pattern analysis encompassed false positive rate,false negative rate,and categorical comparison of discrepant prescriptions.Statistical deviation assessments were performed using x2 and Kappa coefficient to quantify inter-rater consistency.Results This study contains a total of 5 099 data,pharmacist group's review results are reasonable for 4 879 cases and unreasonable for 220 cases.In contrast,The Deepseek model's review results in the AI group are reasonable for 4904 cases and unreasonable for 195 cases.The evaluation accuracy rate of the DeepSeeK model is approximately 93.82%,the precision rate is approximately 25.64%,the recall rate is approximately 22.73%,the specificity is approximately 97.03%,and the F1 value of the model is ap-proximately 24.13%.Conclusion With rapid advancements in artificial intelligence,large language models like DeepSeek,leveraging their superior language comprehension and knowledge reasoning capabilities,can effectively assist pharmacists in pre-scription review,offering new technical support for clinical medication safety.

Objective To explore the application of the DeepSeek large languagemodel in assessing prescription ration-ality and evaluating its implementation effectiveness.Methods A random sample of 5 099 outpatient and emergency prescrip-tion records from our hospital in a specific month of 2024 was collected.The DeepSeeK large language model employs vector data-base technology for prescription review.An evaluation metrics analysis was conducted between the DeepSeeK's reviews and phar-macist evaluations.Performance metrics including accuracy,precision,recall,specificity,and F1 were systematically calculated.Error pattern analysis encompassed false positive rate,false negative rate,and categorical comparison of discrepant prescriptions.Statistical deviation assessments were performed using x2 and Kappa coefficient to quantify inter-rater consistency.Results This study contains a total of 5 099 data,pharmacist group's review results are reasonable for 4 879 cases and unreasonable for 220 cases.In contrast,The Deepseek model's review results in the AI group are reasonable for 4904 cases and unreasonable for 195 cases.The evaluation accuracy rate of the DeepSeeK model is approximately 93.82%,the precision rate is approximately 25.64%,the recall rate is approximately 22.73%,the specificity is approximately 97.03%,and the F1 value of the model is ap-proximately 24.13%.Conclusion With rapid advancements in artificial intelligence,large language models like DeepSeek,leveraging their superior language comprehension and knowledge reasoning capabilities,can effectively assist pharmacists in pre-scription review,offering new technical support for clinical medication safety.

Autism spectrum disorder (ASD) is a range of neurodevelopmental diseases characterized by social dysfunction and stereotypic behaviors. The etiology of ASD remains largely unexplored, resulting in a diverse array of described clinical manifestations and varying degrees of severity. Currently, there are no drugs approved by a supervisory organization that can effectively treat the core symptoms of ASD. Childhood and adolescence are crucial stages for making significant achievements in ASD treatment, necessitating the development of drugs specifically for these periods. Based on the drug targets and mechanisms of action, it can be found that atypical psychotropic medications, anti-inflammatory and antioxidant medications, hormonal medications, ion channel medications, and gastrointestinal medications have shown significant improvement in treating the core symptoms of ASD in both children and adolescents. In addition, comparisons of drugs within the same category regarding efficacy and safety have been made to identify better alternatives and promote drug development. While further evaluation of the effectiveness and safety of these medications is needed, they hold great potential for widespread application in the clinical treatment of the principal symptoms of ASD.
Humans ; Autism Spectrum Disorder/drug therapy* ; Child ; Adolescent ; Psychotropic Drugs/therapeutic use* ; Antioxidants/therapeutic use* ; Anti-Inflammatory Agents/therapeutic use* ; Gastrointestinal Agents/therapeutic use*

Over the past decade, research has increasingly identified unique dysregulations in lipid metabolism within the tumor microenvironment (TME). Lipids, diverse biomolecules, not only constitute biological membranes but also function as signaling molecules and energy sources. Enhanced synthesis or uptake of lipids in the TME significantly promotes tumorigenesis and proliferation. Moreover, lipids secreted into the TME influence tumor-resident immune cells (TRICs), thereby aiding tumor survival against chemotherapy and immunotherapy. This review aims to highlight recent advancements in understanding lipid metabolism in both tumor cells and TRICs, with a particular emphasis on exogenous lipid uptake and endogenous lipid de novo synthesis. Targeting lipid metabolism for intervention in anticancer therapies offers a promising therapeutic avenue for cancer treatment. Nano-drug delivery systems (NDDSs) have emerged as a means to maximize anti-tumor effects by rewiring tumor metabolism. This review provides a comprehensive overview of recent literature on the development of NDDSs targeting tumor lipid metabolism, particularly in the context of tumor immunotherapy. It covers four key aspects: reprogramming lipid uptake, reprogramming lipolysis, reshaping fatty acid oxidation (FAO), and reshuffling lipid composition on the cell membrane. The review concludes with a discussion of future prospects and challenges in this burgeoning field of research.