Plant-derived exosome-like nanovesicles (PELNs), characterized by a natural lipid bilayer membrane, have rapidly emerged as a prominent research frontier in medicine owing to their unique biological properties and robust therapeutic potential. This review comprehensively examines the biological profiles, mechanistic functions, and recent engineering advancements of PELNs. In terms of composition, PELNs are uniquely enriched in plant-specific glycolipids, phosphatidylserine, secondary metabolites, and highly stable 2'-O-methylated miRNAs. This distinct molecular makeup endows them with exceptional biocompatibility, negligible immunogenicity, and the capacity for cross-species molecular communication. Mechanistically, PELNs demonstrate profound anti-inflammatory efficacy by suppressing the NF-κB and NLRP3 inflammasome pathways. They also serve as potent immune modulators, driving macrophage M1/M2 polarization and regulating T cell activity. Additionally, PELNs exhibit promising antitumor capabilities, targeting malignancies via reactive oxygen species (ROS) induction, TRAIL pathway activation, and tumor microenvironment remodeling. Crucially, the plant miRNAs encapsulated within PELNs remain highly stable in the gastrointestinal tract, allowing them to selectively alter gene expression in specific gut microbiota communities. This interaction deeply influences host immunity and metabolism, highlighting the vital role in cross-species regulation. Advancements in bioengineering have further expanded the clinical utility of PELNs. Targeted delivery efficiency can be significantly amplified via surface functionalization (e.g., folate and RGD sequences) and state-of-the-art drug loading technologies such as sonication and electroporation. Consequently, engineered PELNs surpass traditional synthetic nanocarriers in penetrating natural physiological barriers, particularly for oral and transdermal drug administration. Despite these advantages, clinical translation is currently hindered by the lack of standardized isolation protocols, challenges in scalable manufacturing, and the need for robust quality control frameworks. Looking forward, the integration of multi-omics approaches and AI-driven “molecular fingerprinting”—coupled with the design of synthetic biomimetic vesicles—will be instrumental in overcoming these bottlenecks, ultimately establishing PELNs as a next-generation platform for precision medicine and targeted nanotherapeutic delivery.

Risk prediction models for postoperative pulmonary complications (PPCs) can assist healthcare professionals in assessing the likelihood of PPCs occurring after surgery, thereby supporting rapid decision-making. This study evaluated the merits, limitations, and challenges of these models, focusing on model types, construction methods, performance, and clinical applications. The findings indicate that current risk prediction models for PPCs following lung cancer surgery demonstrate a certain level of predictive effectiveness. However, there are notable deficiencies in study design, clinical implementation, and reporting transparency. Future research should prioritize large-scale, prospective, multi-center studies that utilize multiomics approaches to ensure robust data for accurate predictions, ultimately facilitating clinical translation, adoption, and promotion.

Purpose: Coronavirus disease 2019 (COVID-19) infection may affect serum hormones levels and male sexual function. This study aims to provide evidence for the causal relationship between COVID-19 infection, serum testosterone levels and the risk of erectile dysfunction (ED) using a two-sample Mendelian randomization (MR) approach. Materials and Methods: Summary-level data for serum testosterone levels (199,569 samples and 12,321,875 single nucleotide polymorphisms [SNPs]) were obtained from Rebecca’s study, while data for ED (6,175 cases and 217,630 controls) were sourced from Bovijn’s study. Genetic variations linked to COVID-19 were used as instrumental variables (IVs) in meta-analyses of genome-wide association studies (GWASs) involving 6,406 cases and 902,088 controls from the COVID-19 Host Genetics Initiative.The inverse-variance weighted (IVW) method was primarily employed to evaluate the potential associations between COVID-19 infection, serum testosterone levels, and the risk of ED. The weighted mode, weighted-median and simple-median method were employed to evaluate the sensitivity. Heterogeneity and pleiotropic outlier were assessed using Cochran’s Q test and MREgger regression. Results: The MR analysis demonstrated that COVID-19 infection was associated with reduced serum testosterone levels (odds ratio [OR] 0.966, 95% confidence interval [CI] 0.938–0.993, p=0.016) and an increased risk of ED (OR 1.205, 95% CI 1.063–1.367, p=0.004) when using IVW methods. Sensitivity analyses utilizing various IV sets and MR approach remained consistent. Conclusions COVID-19 infection is associated with a decrease in serum testosterone levels and an increased risk of ED. Male patients recovering from COVID-19 need to pay special attention to their sex hormone levels and sexual health.

Objective To investigate the analgesic effect of ultrasound-guided quadratus lumborum block combined with patient-controlled intravenous analgesia after lower abdominal surgery.Methods A total of 134 patients who underwent lower abdominal surgery in General Hospital of Central Theater Command from April 2021 to April 2024 were prospectively selected and randomly divided into the observation group and the control group,with 67 patients in each group.Patients in the observation group received ultrasound-guided quadratus lumborum block combined with patient-controlled intravenous analgesia.Patients in the control group underwent only patient-controlled intravenous analgesia.The number of analgesic pump compressions and the cumulative sufentanil consumption 4 hours,6 hours,12 hours,and 24 hours after surgery,the visual analogue score(VAS)of pain at rest and exercise,and the incidence of adverse reactions during postoperative analgesia were compared between the two groups.Results Compared with the control group,the number of analgesic pump compressions and the cumulative sufentanil consumption of patients were fewer/less at 6 hours,12 hours and 24 hours after surgery in the observation group(P<0.05).The VAS scores of patients at exercise 4 hours,6 hours,12 hours and 24 hours after surgery in the observation group were significantly lower than those in the control group(P<0.05).The incidence of nausea,vomiting and vertigo in the observation group was significantly lower than that in the control group(P<0.05).Conclusion Compared with patient-controlled intravenous analgesia,ultrasound-guided quadratus lumborum block combined with patient-controlled intravenous analgesia can significantly reduce the number of analgesia pump compressions and the cumulative sufentanil consumption in postoperative analgesia of lower abdominal surgery,and has a better effect in relieving exercise pain,it can also reduce the occurrence of adverse reactions such as nausea and vomiting.

Objective:To analyze the therapeutic effect of ganglioside combined with hyperbaric oxygen in the treatment of cerebral hemorrhage. To investigate the effects of ganglioside combined with hyperbaric oxygen therapy on serum inflammatory factors and neural injury markers in patients.Methods:A randomized controlled study was conducted involving 98 patients with cerebral hemorrhage treated at Bayannur Hospital from January 2022 to January 2024. The patients were randomly assigned to either a control group or a combination group, with 49 cases in each group, using a random number table method. All patients received routine treatment. The control group received hyperbaric oxygen therapy, while the combination group received both hyperbaric oxygen therapy and ganglioside therapy. Both groups were treated for 20 days. The volume of cerebral edema, levels of serum inflammatory factors, and neural injury markers were compared between the two groups before and after treatment, and the efficacy of both groups was evaluated.Results:After treatment, the brain edema volume in the combination group [(12.31 ± 1.31) cm3]was significantly lower than that in the control group [(15.36 ± 1.62) cm3, t = 10.25, P < 0.05]. The Glasgow Coma Scale score in the combination group [(13.64 ± 1.37) points] was significantly higher than that in the control group [(11.42 ± 1.24) points, t = -8.41, P < 0.05]. The serum levels of interleukin-1β and interleukin-8 in the combination group were (5.48 ± 0.56) ng/L and (12.29 ± 1.33) ng/L, respectively, both of which were significantly lower than those in the control group [(6.42 ± 0.67) ng/L, (16.85 ± 1.71) ng/L, t = 7.54, 14.74, both P < 0.05]. The levels of soluble protein-100β (S100β) and high mobility group protein-1 in the combination group were (0.62 ± 0.07) μg/L and (4.17 ± 0.42) μg/L, respectively, both of which were significantly lower than those in the control group [(0.81 ± 0.09) μg/L, (5.59 ± 0.56) μg/L, t = 11.67, 14.20, both P < 0.05]. The National Institutes of Health Stroke Scale score in the combination group [(11.47 ± 1.23) points]was significantly lower than that in the control group [(15.31 ± 1.62) points, t = 13.22, P < 0.05]. The Fugl-Meyer Assessment of Motor Recovery after Stroke score in the combination group [(63.58 ± 6.48) points] was significantly higher than that in the control group [(54.64 ± 5.71) points, t = -7.25, P < 0.05]. The total response rate in the combination group was 91.84% (45/49), which was significantly higher than that in the control group [73.47% (36/49), χ2 = 5.76, P < 0.05]. Conclusions:The use of gangliosides in combination with hyperbaric oxygen therapy for the treatment of cerebral hemorrhage can effectively reduce cerebral edema, lessen inflammatory responses, and minimize neural injury. This approach helps restore patients' neurological and motor functions and enhance overall treatment efficacy.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective:To summarize the clinical features, laboratory findings, treatment and prognosis of children confirmed as Mycoplasma pneumoniae-induced rash and mucositis (MIRM) in children. Methods:This retrospective study concluded 6 children diagnosed as MIRM in Department of Gastroenterology and Infectious Diseases, Shanghai Children′s Hospital, School of Medicine, Shanghai Jiao Tong University from August 2023 to April 2024. This paper described the characteristics of MIRM and analyzed the therapeutic strategy and prognosis.Results:A total of 6 children were diagnosed as MIRM including 2 boys and 4 girls with an age of onset was 6.4 (3.1, 7.5) years. Among the 6 patients, 4 patients had oral mucosal involvement among whom 2 showed crusting of the lips. Four patients had ocular involvement manifesting as conjunctival congestion and increased secretion. All patients presented with skin lesions, manifesting as target-shaped damage in 4 cases, herpes herpetiformis in 1 case and purpura-like rash in 1 case. Serological tests for Mycoplasma pneumoniae IgM and Mycoplasma pneumoniae nucleic acid test were positive in all 6 cases. Two cases received intravenous immunogloblin infusion combined with methylprednisolone, monotherapy of methylprednisolone in 4 cases. The course of glucocorticoids was 1-7 weeks, and the initial dose was 2-4 mg/(kg·d), which was gradually reduced according to the rash. The children were followed up for 3 to 9 months, no case suffered from long term ocular or cutaneous complications or recurrence of rash. All cases had good prognosis. Conclusions:Children diagnosed as MIRM present with mild symptoms and usually have good prognosis with early identification and appropriate intervention. Individualized therapy should be applied based on the severity of skin involvement.

Objective:To address large-scale nonlinear programming challenges in optimizing prognosis-guided intensity-modulated radiation therapy (IMRT) plans, to propose gradient-enhanced random contrastive interaction particle swarm optimization (GradRCIPSO). This gradient-enhanced swarm intelligence algorithm aims to enable global optimization of prognostic treatment plans in clinically efficient scenarios.Methods:The core concept of GradRCIPSO lied in achieving rapid global convergence by allowing particles to learn both swarm interaction and gradient information. Specifically, the interaction information was obtained from elite individuals in the swarm, enabling the particles to efficiently search the entire solution space, whereas the gradient information represents the direction of the steepest descent, enabling the particles to quickly explore the current neighborhood. To assess the effectiveness of the methodology, the IMRT plans for 10 cases of non-small cell lung cancer (NSCLC) were selected in this study. They were compared with the GradRCIPSO-generated prognosis-guided IMRT plans. Moreover, the interior-point method, sequential quadratic programming, active set, gradient descent method, and random contrastive interaction particle swarm optimization (RCIPSO) were employed as optimization engines and compared with GradRCIPSO in terms of optimization efficiency and accuracy.Results:GradRCIPSO successfully generated clinically viable prognosis-guided IMRT plans with comparable dosimetric statistics to original plans, while significantly reducing predicted total radiotherapy risk from 1.22(0.84, 1.51) to 0.93(0.80, 1.29) ( z=2.81, P<0.01). It demonstrated superior accuracy over the above four gradient-based method ( z=2.80-2.81, P<0.01) and achieved threefold acceleration versus RCIPSO while maintaining equivalent solution quality( P>0.05). Conclusions:The proposed GradRCIPSO demonstrates high feasibility and performance in optimizing prognosis-guided IMRT plans, laying the technical foundation for the broad clinical application of prognosis-guided IMRT plans for lung cancer.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.