Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

Objective To explore the potential pathogenesis of SLE and SS based on GEO database with screening differential expression genes common in systemic lupus erythematosus (SLE) and Sjogren's syndrome (SS),analyzing their functions and identifing their expression levels. Methods The gene expression datasets of SLE and SS whole blood samples were retrieved from GEO database. Differential expression genes in peripheral blood cells of SLE and SS were screened using gene expression datasets GSE50772,GSE81622,GSE84844 and GSE48378,respectively,and the shared differential expression genes of SLE and SS were screened. Functional analysis of differentially expressed genes was performed using Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Peripheral blood from SLE and SS patients and healthy controls were collected from March 2024 to April 2024,recruited from the Second Affiliated Hospital of Air Force Medical University. Quantitative fluorescence real-time PCR (qRT-PCR) was used to identify the expression levels of 11 genes with the most significant differences in expression. Results 232 and 110 differentially expressed genes were screened for SLE and SS,respectively,among which 32 genes shared by SLE and SS were up-regulated in expression levels. Functional analysis showed that the 32 differentially expressed genes were mainly enriched in biological processes related to interferon (IFN) signaling pathways,defense response to viruses,response to viruses,negative regulation of viral genome replication,and immune response. KEGG pathway analysis showed that 32 differentialy expressed genes were associated with the process of viral infection. The clinical sample identification results showed that the expression levels of OAS3,IFI44,IFI44L and EPSTI1 were significantly elevated in PBMC of SLE and SS patients. Conclusion This study suggested that changes in biological processes related to IFN signal and viral infection response play important roles in both SLE and SS development,and may be a predisposing factor and potential biomarker for SLE and SS.

Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases. Accurately predicting microbe-disease interactions (MDIs) offers critical insights for disease intervention and pharmaceutical research. Current advanced AI-based technologies automatically generate robust representations of microbes and diseases, enabling effective MDI predictions. However, these models continue to face significant challenges. A major issue is their reliance on complex feature extractors and classifiers, which substantially diminishes the models' generalizability. To address this, we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer potential MDIs. Initially, we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation. Secondly, we employ decoupled representation learning technology, compelling the graph neural network (GNN) to independently learn the weights for each feature subspace, thus enhancing its expressive power. Finally, we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN, reducing information loss due to occlusion. Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models. This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research. Code and data are accessible at: https://github.com/shmildsj/MDI-IFDRL.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Objective:To construct a sizeable naive human Fab phage display antibody library to screen high-affinity specific antibodies in vitro. Methods:Total RNA was extracted from peripheral blood mononuclear cells (PBMCs) of 126 healthy individuals, subsequently reverse-transcribed into cDNA, and used as a template. PCR amplification was performed to obtain the V H from IgG, IgM and light chain κ, λ, separately, with the initial PCR products serving as templates for a second round of PCR. Overlap extension PCR was employed to generate fragments of the κ and λ light chains. These fragments were ligated with the phage vector pNC3, which harbors the variable region 1 of the heavy chain, to construct a recombinant phage plasmid. This plasmid was then electroporated into competent Escherichia Coli TG1 cells to establish a naive human Fab phage display antibody library. One hundred clones were randomly selected for identification and sequencing, and antibody gene polymorphisms were analyzed using the IMGT database and MAFFT software. Recombinant α-hemolysin from Staphylococcus aureus was utilized to screen Fab antibody fragments through biopanning of the antibody library, followed by random selection of phage ELISA-identified clones. The positive clones (antigen A450∶blank control A450≥2.1) were sequenced. Results:Two large naive Fab phage display antibody libraries were successfully constructed, in which the capacity of κ and λ chain antibody libraries were 1.25×10 11 and 1.54×10 11, respectively. The titers for two antibody libraries were 6.04×10 13 CFU/ml and 3.50×10 13 CFU/ml. The positive transformation insertion rates for κ and λ chain antibody libraries were 96% (96/100) and 100% (100/100), respectively. Sequence analysis revealed that all antibody sequences were unique. The amino acid sequences in the skeletal region were relatively conserved. In contrast, significant variations in the length of the complementarity determining region (CDR) were found, and the diversity of amino acid sequence of the complementary determining region was high, especially the CDR3. Analysis using the IMGT database indicated that the sequences exhibited a broad distribution across variable-diversity-joining gene families. After six rounds of panning, specific phage antibodies enrichment targeting α-hemolysin were achieved. A total of 142 monoclonal antibodies were sequenced, yielding 8 distinct Fab antibody sequences. Conclusion:This study successfully constructed two naive human Fab phage display antibody libraries with large capacity and good diversity, which can be used for screening human antibodies for serum epidemiology.

Pancreatic cancer is a highly malignant tumor of the digestive system and has an extremely poor prognosis.Due to its insidious onset and rapid progression,major surrounding vessels are frequently invaded at the time of diagnosis.Consequently,resection and reconstruction of the portal vein and/or superior mesenteric vein are often required during pancreatectomy.Various methods of venous resection and reconstruction have been developed,each with its own advantages,limitations,and specific applicability.Compared with open surgery,laparoscopic pancreatectomy requires higher technical proficiency and more precise intraoperative decision-making.To promote the advancement of venous reconstruction techniques in laparoscopic pancreatectomy,in this article,we summarize and evaluate our team's practical experience and relevant literature,focusing on graft selection,technical difficulty,operative risk,and short-and long-term patency.Special emphasis was placed on the applicability of different approaches and materials.In addition,regarding postoperative reconstruction of venous patency,we introduced the"Cross-sectional Area Algorithm",a method simulating the evaluation mode of coronary artery patency,to accurately quantify postoperative venous patency.The evaluation method was first proposed by the team but has not yet been externally validated.By reviewing the current status of venous reconstruction strategies and the prognosis of laparoscopic pancreatic surgery,we aim to inform the development of standardized technical guidelines,enable individualized assessment of venous patency after surgery,and ultimately improve minimally invasive pancreatic surgery and the long-term prognosis of patients.

Liver transplantation is an effective treatment method for many end-stage liver diseases; however, the shortage of donor livers is one of the main obstacles affecting its development. Thus, xenotransplantation is expected to be a potential way to solve the shortage of organs. Gene editing technology has been used to improve animal genes so they can enhance their physiological compatibility with humans, and new immunosuppressive drugs are combined to reduce the occurrence of rejection so as to prolong the survival time of grafts. Liver xenotransplantation is more prominent than that of the heart or kidney transplants, and the related molecular mechanisms, such as xenogeneic rejection and coagulation disorders after surgery, need to be further studied due to the more complex structure and physiological functions of the liver. This paper reviews the historical development, current main problems, and clinical applications based on the latest research progress at home and abroad, with aim to improve clinicians' understanding of liver xenotransplantation.

Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases.Accurately predicting microbe-disease interactions(MDIs)offers critical insights for disease intervention and pharmaceutical research.Current advanced AI-based technologies automatically generate robust representations of microbes and diseases,enabling effec-tive MDI predictions.However,these models continue to face significant challenges.A major issue is their reliance on complex feature extractors and classifiers,which substantially diminishes the models' generalizability.To address this,we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer po-tential MDIs.Initially,we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation.Secondly,we employ decoupled representation learning technology,compelling the graph neural network(GNN)to independently learn the weights for each feature subspace,thus enhancing its expressive power.Finally,we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN,reducing information loss due to occlusion.Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models.This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research.Code and data are accessible at:https://github.com/shmildsj/MDI-IFDRL.

To summarize the nursing experience of a patient with anthrax meningoencephalitis caused by cerebrospinal fluid rhinorrhea post-trauma.Nursing points include strict implementation of isolation and hospital infection prevention and control measures;to standardize the use of antibiotics throughout the process to prevent and manage antimicrobial-related diarrhea;to pay attention to the nutritional status of patients and develop individualized nutritional support programs based on evidence;to implement refined airway care to prevent pulmonary complications;to strengthen disease observation,identify intracranial hemorrhage in time;to provide patient and family-centered psychological empowerment in the whole process.After 66 days of careful treatment and nursing care,the patient recovered and was discharged.A follow-up visit after 2 months of discharge showed a good recovery.

OBJECTIVE: To evaluate the effect of biodegradable magnesium alloy materials in promoting tendon-bone healing during rotator cuff tear repair and to investigate their potential underlying biological mechanisms. METHODS: Forty-eight 8-week-old Sprague Dawley rats were taken and randomly divided into groups A, B, and C. Rotator cuff tear models were created and repaired using magnesium alloy sutures in group A and Vicryl Plus 4-0 absorbable sutures in group B, while only subcutaneous incisions and sutures were performed in group C. Organ samples of groups A and B were taken for HE staining at 1 and 2 weeks after operation to evaluate the safety of magnesium alloy, and specimens from the supraspinatus tendon and proximal humerus were harvested at 2, 4, 8, and 12 weeks after operation. The specimens were observed macroscopically at 4 and 12 weeks after operation. Biomechanical tests were performed at 4, 8, and 12 weeks to test the ultimate load and stiffness of the healing sites in groups A and B. At 2, 4, and 12 weeks, the specimens were subjected to the following tests: Micro-CT to evaluate the formation of bone tunnels in groups A and B, HE staining and Masson staining to observe the regeneration of fibrocartilage at the tendon-bone interface after decalcification and sectioning, and Goldner trichrome staining to evaluate the calcification. Immunohistochemical staining was performed to detect the expressions of angiogenic factors, including vascular endothelial growth factor (VEGF) and bone morphogenetic protein 2 (BMP-2), as well as osteogenic factors at the tendon-bone interface. Additionally, immunofluorescence staining was used to examine the expressions of Arginase 1 and Integrin beta-2 to assess M1 and M2 macrophage polarization at the tendon-bone interface. The role of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway in tendon-bone healing was further analyzed using real-time fluorescence quantitative PCR. RESULTS: Analysis of visceral sections revealed that magnesium ions released during the degradation of magnesium alloys did not cause significant toxic effects on organs such as the heart, liver, spleen, lungs, and kidneys, indicating good biosafety. Histological analysis further demonstrated that fibrocartilage regeneration at the tendon-bone interface in group A occurred earlier, and the amount of fibrocartilage was significantly greater compared to group B, suggesting a positive effect of magnesium alloy material on tendon-bone interface repair. Additionally, Micro-CT analysis results revealed that bone tunnel formation occurred more rapidly in group A compared to group B, further supporting the beneficial effect of magnesium alloy on bone healing. Biomechanical testing showed that the ultimate load in group A was consistently higher than in group B, and the stiffness of group A was also greater than that of group B at 4 weeks, indicating stronger tissue-carrying capacity following tendon-bone interface repair and highlighting the potential of magnesium alloy in enhancing tendon-bone healing. Immunohistochemical staining results indicated that the expressions of VEGF and BMP-2 were significantly upregulated during the early stages of healing, suggesting that magnesium alloy effectively promoted angiogenesis and bone formation, thereby accelerating the tendon-bone healing process. Immunofluorescence staining further revealed that magnesium ions exerted significant anti-inflammatory effects by regulating macrophage polarization, promoting their shift toward the M2 phenotype. Real-time fluorescence quantitative PCR results demonstrated that magnesium ions could facilitate tendon-bone healing by modulating the PI3K/AKT signaling pathway. CONCLUSION Biodegradable magnesium alloy material accelerated fibrocartilage regeneration and calcification at the tendon-bone interface in rat rotator cuff tear repair by regulating the PI3K/AKT signaling pathway, thereby significantly enhancing tendon-bone healing.
Animals ; Rotator Cuff Injuries/metabolism* ; Rats, Sprague-Dawley ; Signal Transduction ; Wound Healing/drug effects* ; Alloys/pharmacology* ; Rats ; Proto-Oncogene Proteins c-akt/metabolism* ; Rotator Cuff/metabolism* ; Macrophages/metabolism* ; Magnesium/pharmacology* ; Phosphatidylinositol 3-Kinases/metabolism* ; Vascular Endothelial Growth Factor A/metabolism* ; Male ; Biocompatible Materials ; Bone Morphogenetic Protein 2/metabolism*