Liaoning Medical University

Background Percutaneous endoscopic lumbar discectomy (PELD) is effective for far lateral lumbar disk herniation (FLLDH), requiring precise puncture. This study assessed 3D reconstruction combined with body-surface meshing for preoperative planning. Methods This prospective randomized controlled trial enrolled 53 FLLDH patients (L4-5/L5-S1) from 2023 to 2024, who were randomized to Group A (n = 29; CT-based 3D-planning with surface grids) or Group B (n = 24; conventional X-ray planning). Outcomes included puncture time, operative time, fluoroscopy frequency, and Oswestry Dysfunction Index (ODI). Results Baseline data were comparable (p > .05). Group A showed shorter puncture time (7.7 ± 2.1 min, 95% CI: 6.9–8.5 vs. 10.5 ± 3.8 min, 95% CI: 9.0–12.0), reduced operative time (48.7 ± 7.2 min, 95% CI: 46.2–51.2 vs. 55.2 ± 10.3 min, 95% CI: 51.0–59.4), and fewer fluoroscopy exposures (5.1 ± 1.9, 95% CI: 4.4–5.8 vs. 14.8 ± 3.9, 95% CI: 13.3–16.3; all p < .05). Both groups had improved ODI/VAS postoperatively (p < .05), with no intergroup clinical difference (p > .05). Conclusions 3D reconstruction enhances puncture precision and reduces intraoperative fluoroscopy reduction in FLLDH-PELD, with clinical outcomes comparable to those of conventional methods.

This study aimed to assess the association between intraoperative methylprednisolone administration and postoperative pulmonary function in patients undergoing minimally invasive cardiac surgery via a right axillary incision under ultra-fast-track anesthesia. Clinical data from 238 patients who underwent minimally invasive cardiac surgery through a right axillary incision under ultra-fast-track anesthesia at Zhejiang Provincial People’s Hospital between January 2022 and July 2023 were retrospectively analyzed. Participants were assigned to either the methylprednisolone group (Group M, n = 119) or the control group (Group C, n = 119) according to whether methylprednisolone was administered after anesthesia induction. Pulmonary function was assessed using the oxygenation index (OI = PaO2/FiO2), respiratory index (RI = PA-aO2/PaO2), and incidence of pulmonary atelectasis and pulmonary edema. Measurements were obtained preoperatively (T0) and at 1 h (T1), 6 h (T2), 12 h (T3), and 24 h (T4) postoperatively. In both groups, OI values from T1 to T4 were significantly lower than those at T0 but demonstrated a gradual postoperative increase. Group M exhibited higher OI values than Group C across all postoperative time points (T1–T4) (p < 0.05). RI values in both groups increased from T1 to T4 compared with T0 but presented a decreasing trend over time; RI values in Group M were significantly lower than those in Group C at all postoperative intervals (p < 0.05). At T2, hypersensitive C-reactive protein levels were significantly lower in Group M than in Group C (p < 0.05). No significant differences were observed between groups in the incidence of pulmonary atelectasis or pulmonary edema (p > 0.05). Intraoperative administration of methylprednisolone at a dose of 1–4 mg/kg following induction of ultra-fast-track anesthesia for minimally invasive cardiac surgery via a right axillary incision was associated with improved gas exchange and oxygenation during the first 24 postoperative hours. These findings indicate a potential protective effect of methylprednisolone on pulmonary function in the early postoperative period following cardiopulmonary bypass.

To enhance the success rate and osseointegration of medical implants, it is crucial to develop multifunctional titanium alloys with antibacterial and osteogenic properties. Novel medium entropy alloys (MEAs) are developed by introducing hafnium (Hf) and copper (Cu) into non-equiatomic MEAs (TiMoHfCux, x = 0, 5, 10), guided by d-electron alloy design theory and phase diagram calculations. Due to the sluggish diffusion effect in MEAs, nanoscale acicular (Ti, Hf)2Cu precipitates with a coherent interface are observed in TiMoHfCu5 and TiMoHfCu10, alongside a β phase. Elastic modulus values decrease by 39, 31, and 20GPa, respectively, for x = 0, 5, 10, compared to CP-Ti, as Hf mitigates the adverse effects of Cu. TiMoHfCu5 exhibits superior corrosion resistance and hydrophilicity. With an increase in Cu content to 10 at.%, the MEA demonstrates a 97% antibacterial rate against Escherichia coli, and superior osteogenesis in rat femoral condyles. (Ti, Hf)2Cu exhibits excellent antibacterial properties. Additionally, antibacterial and osteogenic properties are associated with the micro-area potential difference (MAPD). By modifying the morphology of (Ti, Hf)2Cu through the combined addition of Hf and Cu, TiMoHfCu10 leads to a combination of desirable mechanical properties, antibacterial characteristics, and osteogenic properties, highlighting its potential for biomedical applications.

Cervical cancer (CC) is a prevalent form of malignant tumor that impacts the female reproductive system. Its pathogenesis is complex beyond the persistence of high-risk human papillomavirus infection (HR-HPVs). YES1 is a non-receptor tyrosine kinase, yet its specific impact on CC progression remains unclear. We investigated the association with YES1 expression and the malignant biological properties of CC and further explored the potential pathogenic mechanisms mediated by YES1. This offers a possible theoretical basis for the diagnosis, prognostic assessment, and therapeutic targets for CC. The YES1 expression levels in CC were analyzed and detected utilizing the TCGA database, immunohistochemistry (IHC), and Western blot. Small interfering RNA was then used to inhibit YES1 expression successfully. Based on this, the functional role of YES1 in CC was explored using a combination of CCK-8 assay, clone formation assay, wound healing assay, Transwell migration and invasion assay, and flow cytometry. The effects of YES1 on proteins implicated in cellular autophagy, apoptosis, and the signaling pathways associated with these processes were investigated using Western blot analysis. YES1 knockdown reduced cells' ability to proliferate, migrate, and invade, as well as the expression of p62, Bcl-2, PCNA, and PIK3/AKT pathway proteins. Meanwhile, LCII/I, Beclin-1, Bax, Cleaved Caspase-3, and apoptosis rates increased. Our study demonstrated the suppressive impact of YES1 knockdown on CC, which provides a theoretical basis for targeting therapy for CC.

ABSTRACTNanozymes, by mimicking the catalytic sites of natural enzymes, have emerged as effective substitutes for traditional natural enzymes. However, the relationship between the physicochemical properties and activity of nanozymes is complex and nonlinear. Traditional laboratory screening and theoretical calculations struggle to handle large‐scale samples and multidimensional parameters, resulting in inefficiency and high costs in the pursuit of high performance nanozymes. Efficiently screening and designing nanozymes with desirable properties remain a significant challenge. Machine learning (ML) technology can capture the complex nonlinear relationship between the physicochemical properties and activity of nanozymes, allowing for the simultaneous processing of multidimensional input variables, thereby achieving more accurate and efficient performance prediction. This study adopts a data‐driven approach to propose an ensemble enzymatic activity prediction model, utilizing ML algorithms to understand the particle–activity relationship, thereby enabling the efficient screening of nanozymes with high peroxidase (POD)‐like activity. The ensemble model integrates five sub‐models, significantly improving prediction accuracy and enhancing generalization compared to single models, achieving an accuracy of 82.4%. External experimental validation results indicate that the model's activity screening outcomes for four nanozymes outside the dataset are consistent with the results of enzymatic activity assays. Further in vitro and in vivo experiments substantiate the effectiveness of the model‐selected nanozymes with POD activity in tumor treatment. This study offers a promising strategy for screening antitumor nanozymes with the desired POD activity and demonstrates the potential of ML in the field of materials science.

In recent years, immune checkpoint inhibitors (ICI) have revolutionized the treatment landscape of renal cell carcinoma (RCC), significantly enhanced patient outcomes and expanded therapeutic options beyond traditional surgical and targeted approaches. In this review, we provide a comprehensive review of the current applications of ICI in RCC therapy, elucidating their mechanisms of action, clinical efficacy across both clear cell and non-clear cell subtypes, and safety profiles. We compare the effectiveness of monotherapy versus combination therapies, demonstrating how synergistic approaches can improve efficacy and durability of responses. Furthermore, we explore the integration of multi-omics technologies, such as single-cell RNA sequencing and spatial transcriptomics, which are pivotal in predicting ICI response and addressing resistance mechanisms. Our discussion also addresses the critical challenges in RCC immunotherapy, including primary and acquired resistance, economic and ethical barriers, and the management of immune-related adverse events. By synthesizing current research and clinical findings, this review aims to provide valuable insights for optimizing RCC immunotherapy, fostering the development of more effective and individualized treatment protocols, and ultimately improving patient survival and quality of life.

To explore the potential roles of mitochondrial dysfunction in the initiation of inflammation in periodontal macrophages and to determine the mechanism underlying the involvement of dynamin-related protein 1 (Drp1) in macrophage inflammatory responses through its interaction with hexokinase 1 (HK1). Gingival tissues were collected from patients diagnosed with periodontitis or from healthy volunteers. Drp1 tetramer formation and phosphorylation were analysed using western blot. THP-1 macrophages and RAW264.7 cells were stimulated with Porphyromonas gingivalis (Pg) or Pg lipopolysaccharide (Pg LPS), respectively. Alterations in proteins associated with mitochondrial dynamics were scrutinized via western blot. Immunofluorescence was used to evaluate mitochondrial damage and mitochondrial permeability transition pore (mPTP) opening. Western blot was used to examine the inflammatory markers NLRP3, caspase-1, IL-1β and GSDMD. Protein interactions involving Drp1 were verified through immunoprecipitation. In periodontitis patient samples, Pg LPS-treated RAW264.7 cells, and Pg-stimulated THP-1 macrophages, over-activated Drp1 was able to drive NLRP3 inflammasome activation and the subsequent release of inflammatory factors. A direct interaction between Drp1 and HK1 was observed, facilitating excessive mPTP opening and subsequent mitochondrial dysfunction. In the inflammatory milieu of periodontal tissues, Drp1 hyperactivation in the macrophages is implicated in inflammation induction. Modulation of the inflammatory response in periodontal macrophages by Drp1 appears to facilitate mPTP opening.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.