ObjectiveTo investigate the effect of laminin subunit α3 （LAMA3） on the epithelial-mesenchymal transition （EMT）， invasion， and metastasis abilities of pancreatic cancer （PC）. MethodsA comprehensive analysis was performed for tumor- and EMT-related databases to identify the EMT genes associated with PC， especially LAMA3. The methods of qRT-PCR and Western blot were used to measure the expression level of LAMA3 in PC tissue and cell lines； immunofluorescence assay was used to determine the localization of LAMA3 in PANC-1 cells； Transwell assay was used to investigate the effect of LAMA3 on the invasion and migration abilities of PC cells. The t-test was used for comparison of continuous data between groups. ResultsThe analysis of the TCGA database identified 3 EMT-related oncogenes for PC， i.e.， LAMA3， AREG， and SDC1. The LASSO-Cox regression model showed that LAMA3 had the most significant impact on the prognosis of PC （risk score=0.256 1×LAMA3+0.043 1×SDC1+0.071 4×AREG）. The Cox model and nomogram showed that the high expression of LAMA3 was an independent risk factor for the poor prognosis of PC （hazard ratio=1.32， 95% confidence interval： 1.07‍ ‍—‍ 1.62， P<0.01）. Experimental results showed that there was a significant increase in the expression of LAMA3 in pancreatic cancer tissue compared with the normal pancreatic tissue. Compared with the HPDE cell line， there were varying degrees of increase in the expression of LAMA3 in pancreatic cancer AsPC-1， BxPC-3， PANC-1， MIA PaCa-2， and SW1990 cell lines， with the highest expression level in PANC-1 cells. The enrichment analysis showed that LAMA3 was associated with the biological processes and signaling pathways such as EMT， collagen metabolism， extracellular matrix degradation， the TGF-β pathway， and the PI3K pathway. After the knockdown of LAMA3， there were significant reductions in the expression levels of N-Cadherin， Vimentin， and Snail， while there was a significant increase in the expression level of E-Cadherin. Transwell assay showed that there were significant reductions in the invasion and migration abilities of PANC-1 cells after the knockdown of LAMA3. ConclusionLAMA3 is highly expressed in PC and can promote the EMT， invasion， and migration of PC cells， and therefore， LAMA3 may be used as a novel diagnostic marker and a new therapeutic target for PC.

Xenotransplantation is one of the effective ways to overcome the shortage of donor organs. However, the molecular incompatibility between xenotransplantation donors and recipients can cause rejection, which greatly limits the clinical application of xenotransplantation. In recent years, researchers have deeply explored the mechanism of xenotransplantation rejection through xenotransplantation models of pig-to-monkey and pig-to-brain death recipients, and found that the innate immune system plays an important role in rejection. Macrophages, as phagocytes in the innate immune system, not only damage xenografts through phagocytosis but also interact with other immune cells to influence the immune microenvironment of xenotransplantation. However, due to the heterogeneity of macrophages, their phenotypes and functions in xenotransplantation rejection remain unclear. Therefore, it is necessary to further explore the role of macrophages in xenotransplantation rejection. This article reviews the latest research progress of macrophages in xenotransplantation rejection, aiming to explore the mechanisms of macrophages in xenotransplantation rejection and provide references for future research.

BACKGROUND: In China, lung cancer remains the cancer with the highest incidence and mortality rate. Among early-stage lung adenocarcinomas (LUAD), the micropapillary (MPP) component is prevalent and typically exhibits high aggressiveness, significantly correlating with early metastasis, lymphatic infiltration, and reduced five-year survival rates. Therefore, the study is to explore the similarities and differences between MPP and non-micropapillary (non-MPP) components in malignant pulmonary nodules characterized by GGOs in early-stage LUAD, identify unique mutational features of the MPP component and analyze the relationship between the ZNF469 gene, a member of the zinc-finger protein family, and the prognosis of early-stage LUAD, as well as its correlation with immune infiltration. METHODS: A total of 31 malignant pulmonary nodules of LUAD were collected and dissected into paired MPP and non-MPP components using microdissection. Whole-exome sequencing (WES) was performed on the components of early-stage malignant pulmonary nodules. Mutational signatures analysis was conducted using R packages such as maftools, Nonnegative Matrix Factorization (NMF), and Sigminer to unveil the genomic mutational characteristics unique to MPP components in invasive LUAD compared to other tumor tissues. Furthermore, we explored the expression of the ZNF469 gene in LUAD using The Cancer Genome Atlas (TCGA) database to investigate its potential association with the prognosis. We also investigated gene interaction networks and signaling pathways related to ZNF469 in LUAD using the GeneMANIA database and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Lastly, we analyzed the correlation between ZNF469 gene expression and levels of immune cell infiltration in LUAD using the TIMER and TISIDB databases. RESULTS: MPP components exhibited a higher number of genomic variations, particularly the 13th COSMIC (Catalogue of Somatic Mutations in Cancer) mutational signature characterized by the activity of the cytidine deaminase APOBEC family, which was unique to MPP components compared to non-MPP components in tumor tissues. This suggests the potential involvement of APOBEC in the progression of MPP components in early-stage LUAD. Additionally, MPP samples with high similarity to APOBEC signature displayed a higher tumor mutational burden (TMB), indicating that these patients may be more likely to benefit from immunotherapy. The expression of ZNF469 was significantly upregulated in LUAD compared to normal tissue, and was associated with poor prognosis in LUAD patients (P<0.05). Gene interaction network analysis and GO/KEGG enrichment analysis revealed that COL6A1, COL1A1, COL1A2, TGFB2, MMP2, COL8A2 and C2CD4C interacted with ZNF469 and were mainly involved in encoding collagen proteins and participating in the constitution of extracellular matrix. ZNF469 expression was positively correlated with immune cell infiltration in LUAD (P<0.05). CONCLUSIONS The study has unveiled distinctive mutational signatures in the MPP components of early-stage invasive LUAD in the Asian population. Furthermore, we have identified that the elevated expression of mutated ZNF469 impacts the prognosis and immune infiltration in LUAD, suggesting its potential as a diagnostic and prognostic biomarker in LUAD.
Humans ; Lung Neoplasms/genetics* ; Adenocarcinoma of Lung/genetics* ; China ; Prognosis ; Transcription Factors

CD47 is a transmembrane protein widely expressed on cell surface, which is considered as a key molecule for immune escape. With an increasing number of related studies, the role of CD47 and its ligands in immunomodulatory effects has been gradually understood. Recent studies have investigated the role of CD47 in ischemia-reperfusion injury of allogenetic kidney transplantation, rejection and xenotransplantation. Nevertheless, the specific role and the key mechanism remain elusive. In this article, the structure and function of CD47, common CD47 ligands, the relationship between CD47 and kidney transplantation, and the application of CD47 in kidney transplantation were reviewed, the latest research progress of CD47 in kidney transplantation was summarized, and the limitations of current research and subsequent research direction were analyzed, aiming to provide reference for subsequent application of CD47 in allogeneic and kidney xenotransplantation.

Objective:To evaluate the feasibility of using MRI-only simulation images for dose calculation of both photon and proton radiotherapy for nasopharyngeal carcinoma cases.Methods:T 1-weighted MRI images and CT images of 100 patients with nasopharyngeal carcinoma treated with radiotherapy in Cancer Hospital of Chinese Academy of Medical Sciences from January 2020 to December 2021 were retrospectively analyzed. MRI images were converted to generate pseudo-CT images by using deep learning network models. The training set, validation set and test set included 70 cases, 10 cases and 20 cases, respectively. Convolutional neural network (CNN) and cycle-consistent generative adversarial neural network (CycleGAN) were exploited. Quantitative assessment of image quality was conducted by using mean absolute error (MAE) and structural similarity (SSIM), etc. Dose assessment was performed by using 3D-gamma pass rate and dose-volume histogram (DVH). The quality of pseudo-CT images generated was statistically analyzed by Wilcoxon signed-rank test. Results:The MAE of the CNN and CycleGAN was (91.99±19.98) HU and (108.30±20.54) HU, and the SSIM was 0.97±0.01 and 0.96±0.01, respectively. In terms of dosimetry, the accuracy of pseudo-CT for photon dose calculation was higher than that of the proton plan. For CNN, the gamma pass rate (3 mm/3%) of the photon radiotherapy plan was 99.90%±0.13%. For CycleGAN, the value was 99.87%±0.34%. The gamma pass rates of proton radiotherapy plans were 98.65%±0.64% (CNN, 3 mm/3%) and 97.69%±0.86% (CycleGAN, 3 mm/3%). For DVH, the dose calculation accuracy in the photon plan of pseudo-CT was better than that of the proton plan.Conclusions:The deep learning-based model generated accurate pseudo-CT images from MR images. Most dosimetric differences were within clinically acceptable criteria for photon and proton radiotherapy, demonstrating the feasibility of an MRI-only workflow for radiotherapy of nasopharyngeal cancer. However, compared with the raw CT images, the error of the CT value in the nasal cavity of the pseudo-CT images was relatively large and special attention should be paid during clinical application.

Objective To improve the performance of auto-segmentation of prostate target area and organs-at-risk in online magnetic resonance image and enhance the efficiency of magnetic resonance imaging-guided adaptive radiotherapy(MRIgART)for prostate cancer.Methods A retrospective study was conducted on 40 patients who underwent MRIgART for prostate cancer,including 25 in the training set,5 in the validation set,and 10 in the test set.The planning CT images and corresponding contours,along with online MR images,were registered and input into a deep learning network for online MR image auto-segmentation.The proposed method was compared with deformable image registration(DIR)method and single-MR-input deep learning(SIDL)method.Results The overall accuracy of the proposed method for auto-segmentation was superior to those of DIR and SIDL methods,with average Dice similarity coefficients of 0.896 for clinical target volume,0.941 for bladder,0.840 for rectum,0.943 for left femoral head and 0.940 for right femoral head,respectively.Conclusion The proposed method can effectively improve the accuracy and efficiency of auto-segmentation in MRIgART for prostate cancer.

Objective:To describe the clinical characteristics and diagnosis and treatment process of one patient with primary thyroid mucosa-associated lymphoid tissue(MALT)lymphoma,in order to broaden the diagnostic and therapeutic strategies for this disease. Methods:The clinical features,diagnosis and treatment of one patient with primary thyroid MALT lymphoma were reported,and the relevant literatures were reviewed. Results:The patient complained of"bilateral thyroid enlargement for over 3 months",and the preoperative thyroid B-ultrasound and neck CT examination showed significant enlargement of thyroid.The patient underwent thyroidectomy on the right lobe behind the sternum,and postoperative pathological diagnosis confirmed primary thyroid MALT lymphoma.After a definitive diagnosis,the radiotherapy was performed on the thyroid lesion and cervical lymph node drainage area at a dose of 30 Gy/15 sessions.There was no disease progression 7 months after radiotherapy. Conclusion:Primary thyroid MALT lymphoma is a subtype of primary thyroid lymphoma(PTL)that commonly occurs in elderly female patients(＞60 years)accompanied by Hashimotos's thyroiditis(HT),and presents progressive enlargement of neck masses or lymph nodes in a short period.The clinical diagnosis of PTL relies on pathological biopsy,and there are significant differences in the clinical manifestations,treatment approaches,and prognosis among different subtypes of PTL.

Acetaminophen (APAP) overdose is a major cause of liver injury. Neural precursor cell expressed developmentally downregulated 4-1 (NEDD4-1) is an E3 ubiquitin ligase that has been implicated in the pathogenesis of numerous liver diseases; however, its role in APAP-induced liver injury (AILI) is unclear. Thus, this study aimed to investigate the role of NEDD4-1 in the pathogenesis of AILI. We found that NEDD4-1 was dramatically downregulated in response to APAP treatment in mouse livers and isolated mouse hepatocytes. Hepatocyte-specific NEDD4-1 knockout exacerbated APAP-induced mitochondrial damage and the resultant hepatocyte necrosis and liver injury, while hepatocyte-specific NEDD4-1 overexpression mitigated these pathological events both in vivo and in vitro. Additionally, hepatocyte NEDD4-1 deficiency led to marked accumulation of voltage-dependent anion channel 1 (VDAC1) and increased VDAC1 oligomerization. Furthermore, VDAC1 knockdown alleviated AILI and weakened the exacerbation of AILI caused by hepatocyte NEDD4-1 deficiency. Mechanistically, NEDD4-1 was found to interact with the PPTY motif of VDAC1 through its WW domain and regulate K48-linked ubiquitination and degradation of VDAC1. Our present study indicates that NEDD4-1 is a suppressor of AILI and functions by regulating the degradation of VDAC1.

ObjectiveTo explore sleep disturbance in preschool children with autism spectrum disorder (ASD) and analyze the relationship between sleep disturbance and social behavior. MethodsFrom December, 2020 to December, 2022, 221 preschool children with ASD from Beijing Bo'ai Hospital and other two institutes, and 246 healthy preschool children socially recruited were investigated with Children's Sleep Habits Questionnaire (CSHQ). A total of 47 ASD children and 47 healthy children were selected from them to wear a sleep monitoring watch for seven days, while the ASD children were evaluated with Gesell Development Diagnosis Scale (GDDS), Psychoeducational Profile-Third Edition (PEP-3), Autism Diagnostic Observation Schedule-2 (ADOS), Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS) and Social Responsiveness Scale (SRS). ResultsAll the factor-scores were more in the ASD children than in the healthy children (t > 2.491, P < 0.05), except that of daytime sleepiness. The prevalence of sleep disturbance (CSHQ ≥ 41) was 89.6% in ASD children, which was more than that of the healthy children (76.8%) (χ² = 13.360, P < 0.001). The sleep problems in ASD children included bedtime resistance, sleep anxiety, sleep duration, sleep onset delay, parasomnias and sleep disordered breathing. ASD children were shorter in total bedtime, shorter in total sleep time, longer in sleep latency, longer in awake time and lower in sleep efficiency (|t| > 2.001, P < 0.05), compared with those of healthy children. For ASD children, the total bedtime negatively correlated with GDDS-language, PEP-3-expressive language, PEP-3-communication and PEP-3-maladaptive behaviors (r < -0.300, P < 0.05); the sleep efficiency negatively correlated with total score of CARS (r = -0.365, P < 0.05); sleep latency correlated with GDDS-social, PEP-3-cognitive, PEP-3-expressive language, PEP-3-receptive language, PEP-3-visual-motor imitation, PEP-3-characteristic verbal behaviors, PEP-3-communication, original score of ADOS, ADOS-social affect, and total score of CARS (|r| > 2.90, P < 0.05); and total awake time positively correlated with total score of CARS (r = 0.406, P < 0.05). ConclusionSleep disturbance is prevalent and various in preschool ASD children, and influence their social behaviors.

Objective:To investigate the method of simulating low-dose CT (LDCT) images using routine dose level scanning mode to generate LDCT images with correspondence to the routine dose CT (RDCT) images in the training sets for deep learning model, which would be used for LDCT noise reduction.Methods:The CT images reconstructed by different algorithms in Philips CT Big Core had different noise levels, where the noise was larger with iDose 4 algorithm and lower with IMR(knowledge-based iterative model reconstruction)algorithm. A new method of replacing LDCT image with noise equivalent reconstructed image was proposed. The uniform module of CTP712 was scanned with the exposure of 250 mAs for RDCT, 35 mAs for LDCT. The images were reconstructed using IMR algorithm for LDCT images and iDose 4 algorithm at multiple noise reduction levels for RDCT images, respectively. The noise distribution of each image set was analyzed to find the noise equivalent images of LDCT. Then, RDCT images, those selected images were used for training cycle-consistent adversarial networks (CycleGAN)model, and the noise reduction ability of the proposed method on real LDCT images of phantom was tested. Results:The RDCT images generated with iDose 4 level 1 could substitute the LDCT images reconstructed with IMR algorithm. The radiation dose was reduced by 86% in low dose scanning. Using CycleGAN model, the noise reduction degree was 45% for uniform module, and 50%, 13%, 7% for CIRS-SBRT 038 phantom in the specific regions of brain, spinal cord, bone, respectively. Conclusions:Equivalent noise level reconstructed images could potentially serve as the alternative of LDCT images for deep learning network training to avoid additional radiation dose. The generated CT images had substantially reduced noise relative to that of LDCT.