Skeletal muscle dysfunction is a common extrapulmonary comorbidity of chronic obstructive pulmonary disease (COPD) and is associated with decreased quality-of-life and survival in patients. The autophagy lysosome pathway is one of the proteolytic systems that significantly affect skeletal muscle structure and function. Intriguingly, both promoting and inhibiting autophagy have been observed to improve COPD skeletal muscle dysfunction, yet the mechanism is unclear. This paper first reviewed the effects of macroautophagy and mitophagy on the structure and function of skeletal muscle in COPD, and then explored the mechanism of autophagy mediating the dysfunction of skeletal muscle in COPD. The results showed that macroautophagy- and mitophagy-related proteins were significantly increased in COPD skeletal muscle. Promoting macroautophagy in COPD improves myogenesis and replication capacity of muscle satellite cells, while inhibiting macroautophagy in COPD myotubes increases their diameters. Mitophagy helps to maintain mitochondrial homeostasis by removing impaired mitochondria in COPD. Autophagy is a promising target for improving COPD skeletal muscle dysfunction, and further research should be conducted to elucidate the specific mechanisms by which autophagy mediates COPD skeletal muscle dysfunction, with the aim of enhancing our understanding in this field.
Pulmonary Disease, Chronic Obstructive/physiopathology* ; Autophagy/physiology* ; Humans ; Muscle, Skeletal/pathology* ; Mitophagy ; Animals ; Mitochondria/metabolism* ; Lysosomes

As the intricate interplay between microbiota and the host garners increasing research attention, a significant parallel surge has emerged in the investigation of intestinal bacterial extracellular vesicles (BEVs). Most intestinal bacteria secrete BEVs, which harbor specific cargo molecules and exhibit diverse functions, encompassing interactions among bacteria themselves and between bacteria and the host. These interactions can either bolster host health or contribute to various pathologies. By integrating the characteristics of BEVs, we summarized the current research landscape, delving into the intricate interplay between BEVs and different diseases. Furthermore, we offer a succinct overview of the challenges faced in BEVs-based research, encompassing separation, detection, engineering for drug purposes, clinical diagnostics, safety, and future study. In essence, these summaries may serve as invaluable guides for BEVs as communication tools between the gut microbiome and host, ultimately propelling the discovery of novel studies and drug discovery.

This article reports a diagnostically and therapeutically challenging case of small intestinal marginal zone lymphoma. The patient presented with recurrent abdominal pain as the chief complaint, and imaging revealed multifocal small bowel wall thickening with high uptake, multisegmental luminal stenosis, and proximal dilation. Initial diagnostic workup, including gastroscopy, colonoscopy, and enteroscopy with biopsy, failed to establish a definitive diagnosis. Empirical anti-tuberculosis therapy was ineffective. A repeat enteroscopic biopsy performed over eight months after symptom onset eventually confirmed the diagnosis of mucosa-associated lymphoid tissue (MALT) extranodal marginal zone lymphoma. Despite three different chemotherapy regimens, the patient's intestinal obstruction symptoms persisted, with imaging still showing multifocal bowel wall thickening and hypermetabolic activity. A critical diagnostic dilemma arose regarding whether the PET/CT-positive lesions represented residual lymphoma or fibrotic scarring, whether further chemotherapy adjustments were warranted, and whether surgical resection was necessary. Multidisciplinary discussion concluded that imaging had limited discriminatory value in this scenario and that surgical intervention should be pursued if feasible. The patient successfully underwent partial small bowel resection, with postoperative pathology confirming no residual lymphoma but significant fibrotic changes. The patient has since resumed a normal diet, with body weight nearly restored to pre-illness levels. This case highlights that fibrotic transformation is a common sequela of treated marginal zone lymphoma and that PET/CT may misleadingly suggest residual disease, potentially leading to unnecessary chemotherapy. Timely surgical intervention is crucial in such scenarios.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

Objective:To develop an artificial intelligence（AI）-based sequential ultrasound-magnetic resonance imaging（US-MRI）diagnostic strategy to optimize the imaging workflow for ovarian masses.Methods:A total of 1 120 patients with pathologically confirmed ovarian masses who underwent both preoperative pelvic ultrasound and MRI between January 2021 and December 2023 at Women's Hospital，Zhejiang University School of Medicine were retrospectively included. Patients were randomly divided into the training（ n=672）and internal test set（ n=448）at a ratio of 6∶4. An external test set（ n=128）was established at the Forth Affiliated Hospital of School of Medicine. Deep learning was used for automated segmentation of MRI lesions，followed by radiomic feature extraction and machine learning classification to construct both a US-MRI multimodal model and sequential US-MRI strategy. Diagnostic performance and potential healthcare cost-saving effects were evaluated across strategies. Results:In the internal test set（ n=448），the AI-based sequential US-MRI strategy achieved a F1 score of 0.863 and a diagnostic accuracy of 82.14%，with no significant difference compared to the US-MRI multi-modal model（ P>0.05）. The sequential strategy identified 82 cases（18.30%，82/448）of patients as low-risk true negatives during initial ultrasound screening，suggesting a potential to reduce the need for MRI examinations in future clinical practice. In the external test set（ n=128），the strategy achieved an F1 score of 0.800 and a confirmed diagnosis rate of 85.94%，with a theoretical reduction of 26.56%（34 cases）in MRI utilization while maintaining a diagnostic accuracy rate higher than that of the multi-modal model（82.18%）. Conclusions:The AI-based US-MRI sequential diagnostic strategy demonstrates favorable diagnostic accuracy while offering the potential to optimize MRI utilization. This approach may enhance the efficiency of imaging resource allocation and reduce healthcare burden in the management of ovarian masses.

Objective To analyze the structural and phylogenetic characteristics of the mitochondrial genome from Bulinus globosus, so as to provide a theoretical basis for classification and identification of species within the Bulinus genus, and to provide insights into understanding of Bulinus-schistosomes interactions and the mechanisms of parasite transmission. Methods B. globosus samples were collected from the Ruya River basin in Zimbabwe. Mitochondrial DNA was extracted from B. globosus samples and the corresponding libraries were constructed for high-throughput sequencing on the Illumina NovaSeq 6000 platform. After raw sequencing data were subjected to quality control using the fastp software, genome assembly was performed using the A5-miseq and SPAdes tools, and genome annotation was conducted using the MITOS online server. Circular maps and sequence plots of the mitochondrial genome were generated using the CGView and OGDRAW software, and the protein conservation motifs and structures were analyzed using the TBtools software. Base composition and codon usage bias were analyzed and visualized using the software MEGA X and the ggplot2 package in the R software. In addition, a phylogenetic tree was created in the software MEGA X after sequence alignment with the software MAFFT 7, and visualized using the software iTOL. Results The mitochondrial genome of B. globosus was a 13 730 bp double-stranded circular molecule, containing 2 ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and 13 protein-coding genes, with a marked AT preference. The mitochondrial genome composition of B. globosus was similar to that of other species within the Bulinus genus. Phylogenetic analysis revealed that the complete mitochondrial genome sequence of B. globosus was clustered with B. truncatus, B. nasutus, and B. ugandae into the same evolutionary clade, and gene superfamily analysis showed that the metabolism-related proteins of B. globosus were highly conserved, notably the cytochrome c oxidase family, which showed a significant consistency. Conclusions This is the first whole mitochondrial genome sequencing to decode the compositional features of the mitochondrial genome of B. globosus from Zimbabwe and its evolutionary relationship within the Bulinus genus, which provides important insights for further understanding of the phylogeny and mitochondrial genome characteristics of the Bulinus genus.

There is significant inter-individual variation of pharmacokinetics and pharmacody-namics in patients receiving tacrolimus(TAC)for an-ti-rejection therapy,which cause the rejection or toxic action.Based on results of therapeutic drug monitoring and pathophysiological index of trans-plant patients,the individualized dosing regimen can be designed and adjusted by using model in-formed precision dosing(MIPD).The patients'clini-cal outcome can be improved.In the consensus,the different methods of MIPD used for patients re-ceived TAC for anti-rejection therapy were intro-duced,which can be used for the designing and ad-justing doing regimen,predicting adverse drug reac-tion,improving medication adherence and econom-ics during therapy.

To investigate the clinical value of cardiac magnetic resonance feature tracking (CMR-FT) technology in the assessment of the right ventricle function in patients with immune checkpoint inhibitor (ICIs)-related myocarditis.

Supratentorial cerebral hemorrhage complicated by brain herniation has high disability and mortality rates,and surgical treatment can improve cerebral perfusion,brain tissue metabolism,and hematoma clearance and promote neurological function recov-ery,with the main surgical procedures of craniotomy,endoscopic surgery,and stereotactic surgery.Different treatment methods have a certain value in the treatment of patients with supratentorial cerebral hemorrhage and brain herniation,and in recent years,an increas-ing number of studies have focused on the comparison of the impact of different treatment methods on prognosis.This article reviews re-lated research advances and compares thedifferent treatment methods for patients with supratentorial cerebral hemorrhage and brain herniation,in order to provide a reference for clinical diagnosis and treatment.

Objective:To evaluate clinical outcomes of occlusion-guided vascularized folded fibula flap reconstruction with delayed implant restoration for mandibular defects after benign tumor resection.Methods:A total of 12 patients with benign mandibular tumors underwent free folded fibula flap reconstruction at the First Affiliated Hospital of Bengbu Medical University between January 2020 and December 2023, including 7 males and 5 females, aged 21-52 years. Six months after mandibular reconstruction, the internal fixation titanium plates were removed, and dental implants were placed using a preoperatively fabricated occlusal guide, followed by second-stage implant surgery and prosthetic restoration. Mandibular CT scans were obtained 6 months after reconstruction to compare the fitting accuracy between the preoperative virtual design and the actual reconstructed mandible. The implant stability quotient (ISQ) was measured 3 months after implant placement. Masticatory efficiency and Enneking lower limb function scores were evaluated at the following time points: before tumor surgery (T1), before implant placement (T2), 6 months (T3) and 9 months (T4) after implant crown restoration. One-way repeated measures ANOVA was used to analyze the masticatory efficiency and lower limb function scores.Results:The free folded fibula grafts were successfully performed via an intraoral approach in all 12 patients, with a 100% of survival rate. Mandibular defects included Brown class I in 6 cases, class II in 2 cases, and class III in 4 cases. A total of 42 implants were placed with successful osseointegration. The ISQ measured at 3 months post-placement was 64.10±4.18. At 6 months postoperatively, morphological analysis comparing the preoperative virtual surgical design with the actual postoperative reconstructed mandible revealed a reconstruction accuracy of 84.27%±4.23%. Significant differences were observed in Enneking scores and masticatory efficiency across all four time points (all P<0.001). Masticatory function showed significant improvement at T4 compared that at T2 [(88.06±3.66)% vs. (65.44±3.82)%, P<0.05]. Conclusion:Occlusal function-guided mandibular reconstruction with vascularized folded fibula flap after removal of benign mandibular tumors is a reliable method, which is associated with minimal donor-site morbidity and enables patients to restore precise occlusion and to achieve favorable masticatory efficiency.