Objective:To evaluate the clinical efficacy of allogeneic hematopoietic stem cell transplantation（allo-HSCT）in children with severe aplastic anemia（SAA）.Methods:Twenty-seven cases with SAA who had been treated with allo-HSCT from January 2020 to December 2022 were retrospectively analyzed and reviewed.Results:（1）A total of 27 SAA patients were enrolled，including 18 males and 9 females，with a median age of 8 (2-15) years.There were 20 cases of SAA-Ⅰ type,7 cases of SAA-Ⅱ type.Based upon donor sources，three cases of matched sibling donors hematopoietic stem cell transplantation,and 24 cases of haploidentical hematopoietic stem cell transplantation were adopted.（2）Hematopoietic reconstruction was achieved in all 27 cases.The median implantation time of neutrophils and platelets was 10（9-20）days and 12（7-26）days respectively.The cumulative incidence of acute graft-versus-host disease（GVHD）was 66.67%（18/27）.The incidence of grade Ⅰ-Ⅱ was 55.56%（15/27）and that of grade Ⅲ-Ⅳ was 11.11%（3/27）.The incidence of chronic GVHD was 7.41%（2/27）.Transplant-associated thrombotic microangiopathy (TA-TMA) occurred in 7.41%（2/27）patients,cytomegalovirus viremia in 62.96%（17/27）patients,epstein-barr virus infection in 33.33%（9/27）patients,and 14.81%（4/27）patients progressed to post-transplant lymphoproliferative disorder (PTLD).（3）The median follow-up time was 12 (2-28) months.The overall survival rate was 96.29%.Twenty-six patients survived,and one patient died due to multiple complications of severe acute GVHD,TA-TMA,cytomegalovirus infection,PTLD and secondary epilepsy.Conclusion:Allo-HSCT is an effective therapy for SAA in children.The effective rate of this research is 96.29%.Acute GVHD is still the key to therapy.The incidence rate of acute GVHD is 66.67% in this study.The blood incompatibility of donor and recipient may affect the incidence of GVHD.The intensity of GVHD prevention should be reduced after HLA-matched sibling donor-hematopoietic stem cell transplantation so as to avoid the complications of virus recurrence and PTLD.

Objective To investigate the levels and clinical significance of serum microRNA(miR)-651 and miR-630 in patients with cervical cancer.Methods From June 2017 to May 2020,108 cervical cancer patients accepted by our hospital were collected as the cervical cancer group.Meantime,100 cervical intraepithelial neoplasia(CIN)patients treated in our hospital were regarded as the CIN group,and 110 healthy individuals who underwent physical examination were regarded as the control group.Real-time fluorescence quantitative PCR(qRT-PCR)was applied to detect serum levels of miR-651 and miR-630,while analyzing the relationship between serum miR-651 and miR-630 as well as clinical features and prognosis of patients.Results The serum levels of miR-651 and miR-630 in the cervical cancer group and CIN group were obviously lower than those in the control group(P<0.05),while the serum levels of miR-651 and miR-630 in the cervical cancer group were obviously lower than those in the CIN group(P<0.05).The expression levels of serum miR-651 and miR-630 were positively corre-lated(r = 0.542,P<0.05).The serum levels of miR-651 and miR-630 were related to HPV infection,differentia-tion,lymph node metastasis,and FIGO staging(P<0.05).The overall survival rate of patients with low levels of miR-651 and miR-630 was lower than that of patients with high levels.Cox regression analysis showed that,HPV infection,degree of differentiation,lymph node metastasis,FIGO staging,miR-651,and miR-630 were all influ-encing factors for the prognosis of cervical cancer patients(P<0.05).Conclusion The serum levels of miR-651 and miR-630 in cervical cancer patients decrease,which are related to HPV infection,differentiation,lymph node metastasis,FIGO staging,and prognosis.

Myocardial infarction is one of the major diseases that seriously threaten human health. In the clinical treatment of myocardial infarction, there are unpredictable complications, and most patients will suffer a severe cardiac function decline due to excessive loss of myocardia and formation of scar tissue, eventually progressing to heart failure or even death. With rapid development of biological materials, they as an important part of tissue repair and regeneration research, have become a hot spot in the research and development of cardiovascular repair materials. Among them, decellularized extracellular matrix (dECM) materials, a class of natural materials with good histocompatibility, low immunogenicity, and suitable cell growth and metabolism characteristics, have been applied in clinical or preclinical cardiovascular tissue engineering or regenerative medicine. In this review, the application progress of dECM materials in tissue engineering, including the dECM preparation of 3D printed bioink, electrospinning, matrix hydrogel, and myocardial patch, in myocardial infarction treatment was summarized, and prospects and current challenges in the treatment of myocardial infarction were discussed.

Due to the low contrast of CT images,irregular shape of the liver,and blurred boundaries with adjacent organs,the existing methods based on convolutional neural network underperform in liver segmentation tasks,especially for boundary recognition and small object detection.A novel liver segmentation method is proposed based on multi-scale feature fusion and attention,namely MFFA UNet.Multi-scale feature fusion is firstly employed to acquire abundant segmentation details,while spatial and channel attention mechanisms are utilized to capture global spatial and inter-channel relationships.Additionally,a deep supervision module fully leverages the output of intermediate hidden layers,enhancing the learning capability of the network,which in turn accelerates the network's convergence speed.Moreover,a hybrid loss function is adopted to address the issue of class imbalance,further boosting the model's segmentation efficacy.Experimental results demonstrate that the proposed MFFA UNet outperforms the prevailing segmentation networks on the public LITS dataset,producing results that are closer to the ground truth.

To address the inability of the existing machine learning methods to simultaneously consider both the temporal and spatial domain features of electroencephalogram(EEG)signals in classifying EEG features,a feature fusion based Attention-EEGNet-BiGRU(AEBGNet)is presented for classifying motor imagery(MI)EEG signals.AEBGNet is capable of fusing the temporal domain features extracted by convolutional neural network with attention mechanism and spatial domain features extracted by a bidirectional gated recurrent unit to obtain more distinctive spatiotemporal features.The constructed AEBGNet classification model achieves an average accuracy of 80.37%on the BCI competition IV 2b dataset,and there is an improvement of 6.09%over the standard EEGNet method.The results demonstrate the effectiveness of the proposed method in enhancing the classification accuracy of MI EEG signals,providing a new idea for MI EEG signal classification.

A composite nystagmus classification framework enhanced by dual attention mechanism is proposed to address the problem that the existing researches only identify whether nystagmus occurs in a horizontal,vertical,or axial direction,but fail to consider the issue of composite nystagmus composed of multiple directions with various intensities in clinical practice.A spatiotemporal concentration algorithm for nystagmus videos is presented,and it combines convolutional neural networks and Hough transform to remove interference from invalid frames and regions and to improve the quality of nystagmus videos.Then,a dense optical flow algorithm is used to extract the optical flow field of eye movement.Finally,a composite nystagmus classification network based on dual attention mechanism enhancement is constructed.An improved efficient channel attention module is used to effectively obtain the direction and intensity of nystagmus in different channels of the optical flow map;and a temporal attention module is added at the end of the bidirectional long short-term memory network to achieve significant expression of classification results based on different temporal features.On the nystagmus dataset provided by the cooperating hospital,the proposed method has an accuracy rate of 83.17%for composite nystagmus classification,and achieved accuracy rates of 91.03%,89.74%,and 86.05%for individual horizontal,vertical,and axial nystagmus classifications.The proposed method realizes the intelligent classification of composite nystagmus and is valuable in clinic.

Objective:To investigate diagnostic and prognostic value of actin-binding protein ANLN in clear cell renal cell carcinoma(ccRCC)and its relationship with tumor microenvironment.Methods:Gene expression data and clinical data for ccRCC were downloaded from The Cancer Genome Atlas(TCGA).Relationship between ANLN expression and clinicopathological features was assessed by Wilcoxon rank sum test and Logistic regression.Receiver operating characteristic(ROC)curve was used to assess diagnostic value of ANLN expression in ccRCC.Kaplan-Meier and Cox regression analysis were used to investigate effect of ANLN expression on overall survival.Gene set enrichment analysis(GSEA)was used to identify signaling pathways associated with ANLN in ccRCC.Relationship between ANLN expression and immune infiltration was analyzed by ESTIMATE algorithm,tumor immune estima-tion resource(TIMER)and CIBERSORT algorithms.Relationship between ANLN and drug sensitivity was calculated using CellMiner database.Results:ANLN expression was significantly upregulated in ccRCC tissues.ANLN expression in ccRCC was correlated with clinicopathological features.ROC analysis showed that ANLN had a high diagnostic value in ccRCC.High ANLN expression was signifi-cantly associated with poor prognosis.Multivariate Cox regression analysis showed that high ANLN expression was an independent risk factor for overall survival in ccRCC patients.GSEA showed that ANLN was associated with multiple signaling pathways.In terms of immunity,ANLN was closely associated with tumor microenvironment,immune infiltration and immune checkpoint molecules in ccRCC.ANLN expression was negatively correlated with sensitivity of most antitumor drugs.Conclusion:ANLN is a potential diagnos-tic and prognostic biomarker and immunotherapeutic target for ccRCC.

Objective:To explore the application value of qualitative characteristics and quantitative parameters of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of pancreatic ductal adenocarcinoma (PDAC) and non-PDAC presenting as pancreatic solid focal lesions.Methods:A retrospective analysis was conducted on 64 cases of PDAC(the PDAC group) and 52 cases of non-PDAC(the non-PDAC group) who underwent CEUS examination at Tianjin Medical University Cancer Institute and Hospital from July 2022 to June 2023. Clinical characteristics, two-dimensional ultrasound features, CEUS qualitative characteristic, and quantitative parameters were compared between the two groups. ROC curves were plotted, and the Delong test was used to evaluate the diagnostic performance of qualitative and quantitative analyses in distinguishing PDAC from non-PDAC. Binary logistic regression analysis was employed to assess the independent predictors of PDAC.Results:①There were significant differences in serum CA19-9, lesion size, boundary, the main pancreatic duct (MPD) diameter, degree of enhancement and enhancement pattern between the PDAC group and the non-PDAC group (all P<0.05). ②The relative peak intensity (rPE), and relative wash-in and wash-out area under the curve (rWiWoAUC) were lower in the PDAC group than the non-PDAC group, with statistically significant differences(all P<0.001). ③The areas under the curve (AUC) for diagnosing PDAC using enhancement pattern, venous phase(VP) enhancement degree, rPE, and rWiWoAUC were 0.698, 0.707, 0.863, and 0.867, respectively. The AUCs of quantitative parameters were superior to those of qualitative characteristics, with statistically significant differences ( P<0.05). Using CEUS mode B, low VP enhancement, rPE<72.44, and rWiWoAUC<86.59 as cut-off values, the accuracies for diagnosing PDAC were 0.698, 0.741, 0.828, and 0.802, respectively. ④Serum CA19-9, lesion size, MPD diameter, rPE, and rWiWoAUC were independent predictors of PDAC (all P<0.05). Conclusions:CEUS qualitative and quantitative analyses are helpful in the differential diagnosis of PDAC and non-PDAC, with rPE and rWiWoAUC being useful indicators for diagnosing PDAC.

Objective To investigate the relationship between preoperative frailty and short-term postoperative complications in elderly breast cancer patients.Methods A convenience sampling method was used to select 231 elderly breast cancer patients who underwent elective surgery in a tertiary care hospital in Beijing from July 2022 to December 2022.General information on elderly patients was collected and the frailty assessment was performed 1 day before surgery,and the occurrence of complications in elderly patients was followed up 30 days after surgery.Results Among the 214 elderly breast cancer patients,37 patients had complications within 30 days postoperatively.Binary logistic regression analysis showed that the risk of complications at 30 days postoperatively was 5.532 times higher in elderly breast cancer patients with preoperative frailty than it in non-frail patients(P＜0.05).Elder breast cancer patients with problems of decreased free movement,increased resistance/loss of endurance,and weight loss had a high risk of postoperative complications.Conclusion Preoperative frailty affects the occurrence of complications in elderly breast cancer patients within 30 days after surgery and suggests that nursing staff should strengthen perioperative health management for elderly breast cancer patients with preoperative frailty and actively prevent the occurrence and development of frailty.

Background:HBV-related acute-on-chronic liver failure(ACLF)has a high mortality rate,early and accurate prediction is helpful for formulating the best treatment options.Aims:To investigate the value of serum decoy receptor 3(DcR3)combined with COSSH-ACLF scoring model in predicting short-term(90-day)prognosis in patients with HBV-ACLF.Methods:A total of 205 patients with HBV-ACLF,50 patients with chronic hepatitis B(CHB)and 50 healthy people(control group)from January 2020 to August 2022 at the Third Affiliated Hospital of Nantong University were enrolled.Serum DcR3 level was detected by ELISA.Patients with HBV-ACLF were divided into improvement group and deterioration group according to the survival status at 90 days after admission.Scores of iMELD,CLIF-C ACLF and COSSH-ACLF were calculated.Multivariate Logistic regression analysis was used to evaluate the risk factors affecting short-term prognosis of patients with HBV-ACLF.ROC curve was used to assess the predictive value of serum DcR3 and COSSH-ACLF score.Results:Serum DcR3 level in HBV-ACLF group was significantly higher than that in CHB group and control group(P<0.05).Serum DcR3,iMELD score,CLIF-C ACLF score and COSSH-ACLF score in HBV-ACLF deterioration group were significantly higher than those in improvement group(P<0.001).Multivariate Logistic regression analysis showed that serum DcR3 and COSSH-ACLF score were independent risk factors affecting short-term prognosis of patients with HBV-ACLF(P<0.001).Pearson correlation analysis showed that serum DcR3 was positively correlated with COSSH-ACLF score(r=0.477,P<0.001).ROC curve results showed that AUC of serum DcR3,COSSH-ACLF score for predicting short-term prognosis of patients with HBV-ACLF were 0.869 and 0.897,respectively.AUC of combined prediction model was 0.939.Conclusions:Serum DcR3 and COSSH-ACLF score have a good value in predicting short-term prognosis of patients with HBV-ACLF,and the combination of serum DcR3 and COSSH-ACLF score has higher predictive value.