ObjectiveTo investigate the expression of serum Aldo-keto reductase family 1 member B10 （AKR1B10） in patients with hepatocellular carcinoma （HCC） in northern China， and to provide a new and valuable biomarker for the clinical diagnosis of HCC. MethodsThis study was conducted among 102 patients with HCC， 119 patients with benign liver disease， and 132 patients with other malignant tumors who attended The Affiliated Hospital of Chengde Medical University and 148 healthy individuals who underwent physical examination from May 2020 to May 2024. ELISA and chemiluminescence were used to measure the serum levels of AKR1B10 and alpha-fetoprotein （AFP）. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between three groups and further comparison between two groups； the chi-square test was used for comparison of categorical data between groups. The area under the ROC curve （AUC） was used to assess diagnostic efficiency. ResultsThe expression level of AKR1B10 was 3 053.79 （1 475.67‍ ‍—‍ ‍4 605.86） pg/mL in the HCC group， 1 324.42 （659.68‍ ‍—‍ ‍2 023.88） pg/mL in the benign liver disease group， 660.68 （377.56‍ ‍—‍ ‍2 087.77） pg/mL in the other malignant tumor group， and 318.30 （82.73‍ ‍—‍ ‍478.82） pg/mL in the healthy group， with a significant difference between the four groups （H=240.86， P<0.001）， and further comparison between two groups showed that the HCC group had a significantly higher level than the other three groups （all P<0.001）. The ROC curve analysis of the HCC group and the other three groups showed that serum AKR1B10 had an optimal cut-off value of 1 584.97 pg/mL in the diagnosis of HCC， with an AUC of 0.86 （95% confidence interval ［CI］： 0.82‍ ‍—‍ ‍0.90）， a sensitivity of 74.3%， and a specificity of 85.2%. Compared with each indicator alone， a combination of AKR1B10 and AFP could improve the sensitivity （81.8%） and specificity （91.4%） of HCC diagnosis. AKR1B10 had an AUC of 0.84 （95%CI： 0.78‍ ‍—‍ ‍0.90） in the diagnosis of patients with early- or middle-stage HCC， with a sensitivity of 76.2% and a specificity of 81.2%. AKR1B10 had an AUC of 0.85 （95%CI： 0.77‍ ‍—‍ ‍0.92） in the diagnosis of patients with AFP-negative HCC， with a sensitivity of 81.6% and a specificity of 79.9%. ConclusionAKR1B10 is a promising serological marker for the diagnosis of HCC， and a combination of AKR1B10 and AFP can improve the detection rate of HCC patients in northern China， especially those with early- or middle-stage HCC and AFP-negative HCC.

Objective To analyze the status quo and related factors of treatment compliance in elderly patients with advanced gastric cancer complicated with cancer pain. Methods Three hundred and ten elderly patients with advanced gastric cancer from January 2021 to June 2024 were selected, and their general data were collected. Hospital Anxiety and Depression Scale (HADS), Beliefs about Medicines Questionnaire (BMQ), Numerical Rating Scale (NRS) and 8-item Morisky Medication Adherence Scale (MMAS-8) were adopted to investigate the psychological status, necessity of medication belief, degree of cancer pain and treatment compliance. Univariate analysis, correlation analysis and multivariate logistic regression analysis were used to describe and analyze the treatment compliance status and related factors in elderly advanced gastric cancer with cancer pain. Results A total of 310 patients were divided into group A (good compliance, 93 cases), group B (moderate compliance ,102 cases) and group C (poor compliance , 115 cases) by means of compliance degree. There were significant differences in education level , pain duration and intensity and analgesic category (P<0.05). Treatment compliance was associated with education level, analgesic category, psychological status, medication belief and pain degree (P<0.05). The necessity of medication belief and pain duration and degree were influencing factors of treatment compliance. Conclusion The treatment compliance in advanced gastric cancer with cancer pain is poor, and can be affected by the necessity of medication belief and duration and degree of pain.

Objective To explore the effect of continuous cuff compression in improvement of forearm hematoma in patients with percutaneous coronary intervention.Methods A total of 94 patients with coronary intervention for acute myocardial infarction in the hospital from September 2021 to September 2024 were selected as research objects,and they were divided into control group and ob-servation group according to the random number table method,with 47 cases in each group.The control group adopted a customized sphygmomanometer combined with a conventional cuff for intermit-tent compression of the forearm hematoma,and the observation group adopted a customized sphygmo-manometer combined with a double-balloon hollow cuff for continuous compression of the forearm he-matoma.The cyanosis of the hand,wrist skin temperature,numbness and swelling of the hand,the forearm painand heart rate during the cuff compression of the hematoma,as well as the arm circumfer-ence and cuff secondary compression,and direct nursing time of the patients after releasing the cuff compression were compared between the two groups.Results During the period of cuff compression of hematoma,the cyanosis of hand,wrist skin temperature,numbness and swelling of hand,the fore-arm pain and heart rate of the observation group were significantly better than those of the control group(P＜0.05);after releasing the cuff compression,the arm circumference and cuff secondary compression and direct nursing time of the observation group were significantly better than those of the control group(P＜0.05).Conclusion Application of customized sphygmomanometer combined with double-balloon hollow cuff for continuous compression of forearm hematoma can improve patient's comfort degree and cuff compression effect,and reduce nursing workload.

Objective:To explore the application effect of the modified sandwich teaching method based on constructivism theory in clinical teaching of neurology nursing interns.Methods:A total of 29 nursing interns who practiced in the Department of Neurology of the First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital) from June 2020 to May 2021 were selected as the control group, using the conventional clinical nursing teaching method, and 28 nursing interns who practiced from June 2021 to May 2022 were selected as the observation group, using the modified sandwich teaching method based on constructivism theory. Before graduating from the Department of Neurology, nursing interns in the two groups were compared in terms of the teaching effects, such as the score of learning initiative, theoretical examination, operation examination, and nursing round report. SPSS 25.0 was used for t test and chi-square test. Results:The score for each dimension (learning driving force, learning objectives, in-depth learning, controlled learning, and solid learning) and total score in the observation group were significantly higher than those in the control group ( P<0.05). There was no significant difference between the two groups in the scores of theoretical examination and operation examination (89.11±3.58 vs. 88.97±2.74, 93.79±2.48 vs. 93.86±2.20; P>0.05); the scores of nursing rounds in the observation group were significantly higher than those in the control group (88.61±2.60 vs. 83.38±3.97, P<0.05). Conclusions:The modified sandwich teaching method based on constructivism theory can enhance the learning initiative and comprehensive analysis ability of nursing interns in the Department of Neurology. It is suitable for clinical nursing teaching in the Department of Neurology and is worth popularizing.

Objective:To explore the association between polymorphisms of transforming growth factor-β(TGF-β)signaling pathway and non-syndromic cleft lip with or without cleft palate(NSCL/P)among Asian populations,while considering gene-gene interaction and gene-environment interaction.Methods:A total of 1 038 Asian NSCL/P case-parent trios were ascertained from an international consortium,which conducted a genome-wide association study using a case-parent trio design to investigate the genes affec-ting risk to NSCL/P.After stringent quality control measures,343 single nucleotide polymorphism(SNP)spanning across 10 pivotal genes in the TGF-β signaling pathway were selected from the original genome-wide association study(GWAS)dataset for further analysis.The transmission disequilibrium test(TDT)was used to test for SNP effects.The conditional Logistic regression models were used to test for gene-gene interaction and gene-environment interaction.Environmental factors collected for the study in-cluded smoking during pregnancy,passive smoking during pregnancy,alcohol intake during pregnancy,and vitamin use during pregnancy.Due to the low rates of exposure to smoking during pregnancy and al-cohol consumption during pregnancy(＜3％),only the interaction between maternal smoking during pregnancy and multivitamin supplementation during pregnancy was analyzed.The threshold for statistical significance was rigorously set at P=1.46 × 10-4,applying Bonferroni correction to account for multiple testing.Results:A total of 23 SNPs in 4 genes yielded nominal association with NSCL/P(P＜0.05),but none of these associations was statistically significant after Bonferroni's multiple test correction.How-ever,there were 6 pairs of SNPs rs4939874(SMAD2)and rs1864615(TGFBR2),rs2796813(TGFB2)and rs2132298(TGFBR2),rs4147358(SMAD3)and rs1346907(TGFBR2),rs4939874(SMAD2)and rs1019855(TGFBR2),rs4939874(SMAD2)and rs12490466(TGFBR2),rs2009112(TGFB2)and rs4075748(TGFBR2)showed statistically significant SNP-SNP interaction(P＜1.46 × 10-4).In contrast,the analysis of gene-environment interactions did not yield any significant results after being cor-rected by multiple testing.Conclusion:The comprehensive evaluation of SNP associations and interac-tions within the TGF-β signaling pathway did not yield any direct associations with NSCL/P risk in Asian populations.However,the significant gene-gene interactions identified suggest that the genetic architec-ture influencing NSCL/P risk may involve interactions between genes within the TGF-β signaling path-way.These findings underscore the necessity for further investigations to unravel these results and further explore the underlying biological mechanisms.

Medical image is a powerful tool to assist doctors in the diagnosis and treatment planning.Nowadays,the segmentation of medical images is no longer limited to manual segmentation methods.Traditional methods and deep learning methods have been used to achieve more accurate results in medical image segmentation.Herein some innovative medical image segmentation methods in recent years are reviewed.By elaborating on the innovations of deep learning methods(SAM,SegNet,Mask R-CNN,and U-NET)and traditional methods(active contour model and threshold segmentation model),the differences and similarities between them are compared.The summary of medical image segmentation methods and the prospect is expected to help researchers better grasp and familiarize themselves with research status and development trend.

Objective:To investigate the value of three-dimensional (3D) T 1WI structural images using different acceleration methods including parallel acquisition technique, joint compressed sensing (uCS) technique, and artificial intelligence-assisted compressed sensing (ACS) technique for brain region segmentation. Methods:In this cross-sectional study, fifty patients (female: n=25, age range: 13 to 87 years old) at Corning Hospital of Ningbo University from July to September 2023 were prospectively and consecutively collected. All the subjects underwent brain MRI. Six groups of 3D T 1WI structural images were obtained using different acceleration technique and parameters, including 3D T 1WI without acceleration factor (3D-T 1WI group), 3D T 1WI with parallel acquisition technique with acceleration factor 3 (3D-T 1WI-PI-3 group), 3D T 1WI with uCS technique with acceleration factor 4.5 and 6.9 (3D-T 1WI-uCS-4.5 group, 3D-T 1WI-uCS-6.9 group), 3D T 1WI by ACS technique with acceleration factors of 3 and 5 (3D-T 1WI-ACS-3 group, 3D-T 1WI-ACS-5 group). T 2WI fluid-attenuated inversion recovery (FLAIR) images were also acquired. Subjective scores (cerebral grey matter and white matter clarity scores, clarity scores of cerebral white matter degeneration lesions in relation to the surrounding white matter, and Gibbs artifact scores) and objective metrics [signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), cerebrospinal fluid signal homogeneity, peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and natural image quality evaluator (NIQE)] were used to evaluate image quality in different groups. Totally 109 brain regions were segmented and volumes were measured using the uAI Research Portal image analysis tool. Kappa or intraclass correlation coefficient ( ICC) was used to evaluate the agreement of subjective and objective evaluation indexes between the 3D-T 1WI-PI-3 group, 3D-T 1WI-uCS-4.5 group, 3D-T 1WI-uCS-6.9 group, 3D-T 1WI-ACS-3 group, 3D-T 1WI-ACS-5 group, and 3D-T 1WI group. Kappa or ICC value>0.70 was considered as good agreement. Results:The acquisition time for the 3D-T 1WI group, 3D-T 1WI-PI-3 group, 3D-T 1WI-uCS-4.5 group, 3D-T 1WI-uCS-6.9 group, 3D-T 1WI-ACS-3 group, and 3D-T 1WI-ACS-5 group were 527, 204, 169, 95, 133, 90 s, respectively. Subjective evaluation showed that the 3D-T 1WI-uCS-4.5, 3D-T 1WI-ACS-3, and 3D-T 1WI-ACS-5 groups had excellent agreement with the 3D-T 1WI group in terms of the distribution of cases of cerebral grey matter and white matter clarity scores, respectively (all Kappa value=1.000); The distribution of cases of clarity score of cerebral white matter lesions and surrounding white matter in the 3D-T 1WI-PI-3 group, 3D-T 1WI-uCS-4.5 group, and 3D-T 1WI-ACS-3 group were in good agreement with that of the 3D-T 1WI group ( Kappa values of 0.775, 0.701, and 0.777, respectively); the distribution of the number of cases of the Gibbs artifact score of the 3D-T 1WI-uCS-4.5, 3D-T 1WI-ACS-3, and 3D-T 1WI-ACS-5 groups was in good agreement with the 3D-T 1WI group (all Kappa value=1.000). Objective evaluation showed the CNR of the images in the 3D-T 1WI-PI-3, 3D-T 1WI-uCS-4.5, and 3D-T 1WI-uCS-6.9 groups were in good agreement with those of the 3D-T 1WI group ( ICC of 0.720, 0.759, and 0.752, respectively); PSNR and SSIM were in good agreement among the 3D-T 1WI-PI-3 group, 3D-T 1WI-uCS-4.5 group, 3D-T 1WI-uCS-6.9 group, 3D-T 1WI-ACS-3 group, and 3D-T 1WI-ACS-5 group (PSNR: ICC=0.854; SSIM: ICC=0.851). NIQE of 3D-T 1WI-PI-3 group, 3D-T 1WI-uCS-4.5 group, and 3D-T 1WI-ACS-3 group images were in good agreement with the 3D-T 1WI group ( ICC value of 0.866, 0.727, 0.753, respectively). The ICC values of the volume of each segmented brain region among the 3D-T 1WI-PI-3, 3D-T 1WI-uCS-4.5, 3D-T 1WI-uCS-6.9, 3D-T 1WI-ACS-3, 3D-T 1WI-ACS-5 group and the 3D-T 1WI group images showed decreased in order (all ICC≥0.62). Conclusions:The uCS and ACS techniques used in 3D-T 1WI show high agreement with 3D-T 1WI in terms of brain segmentation. The application of these accelerating techniques can significantly shorten the acquisition time with obtaining images with good image quality, displaying great value.

0n December 31,2021,the Chinese Nursing Association released the group standard"nursing care of patients with infusion of vasoactive agents(T/CNAS 22-2021)",which outlines the fundamental requirements for intravenous infusion of vasoactive drugs and standardizes the evaluation,administration,and monitoring.This article provides an interpretation of the key parts and sections of the standard to ensure nursing safety during the administration of vasoactive drugs,aiming to reduce complications.Additionally,it serves as a crucial reference for nurses during the administration of the medication.

Objectives:To develop a machine learning prediction model for post-stroke depression (PSD) in patients with acute ischemic stroke (AIS) at 3 months after onset.Methods:Patients with AIS admitted to the Second People's Hospital of Hefei from January 2021 to December 2023 were included retrospectively. According to the 17-item Hamilton Depression Rating Scale (HAMD) evaluation results at 3 months after onset, they were divided into PSD group and non-PSD group. The recursive feature elimination (RFE) method was used to screen the characteristic variables of PSD. A PSD prediction model for patients with AIS was developed based on three machine learning algorithms: logistic regression (LR), random forest (RF), and supported vector machine (SVM). The area under a receiver operating characteristic (ROC) curve (AUC) and calibration curve were used to evaluate the performance of the model. The SHapley Additive exPlanations (SHAP) algorithm was used to analyze the contribution of each risk factor. Results:A total of 243 patients with AIS were included, including 159 males (64.6%), aged 64.32±11.54 years, the median years of schooling was 6 years, and 13 males (5.3%) lived alone. 105 patients (42.7%) had a history of stroke. The median baseline National Institutes of Health Stroke Scale (NIHSS) score was 3, and the median baseline Modified Rankin Scale (mRS) score was 2. 33 patients (13.4%) received intravenous thrombolysis treatment. 93 patients (38.27%) had PSD at 3 months after onset. RFE showed that the optimal number of features was 11, including baseline NIHSS score, baseline mRS score, C-reactive protein, intravenous thrombolysis, low-density lipoprotein cholesterol, small vessel occlusion, D-dimer, total cholesterol, alcohol consumption, right side infarction, and baseline systolic blood pressure. ROC curve analysis shows that the RF model had the best predictive performance (AUC=0.831, 95% confidence interval 0.730-0.931), followed by the SVM model (AUC=0.827, 95% confidence interval 0.713-0.941), and the LR model has the lowest predictive performance (AUC=0.771, 95% confidence interval 0.658-0.885). The calibration curve shows that the RF model fits well with the ideal curve, making it the final advantageous model. SHAP showed that the contribution of baseline NIHSS score, baseline mRS score, low-density lipoprotein cholesterol, total cholesterol, and intravenous thrombolysis ranked among the top 5.Conclusions:The RF model can effectively predict the risk of PSD. The baseline NIHSS score, baseline mRS score, low-density lipoprotein cholesterol, and total cholesterol, as well as intravenous thrombolysis are the key predictive factors.

Objective: To investigate the incidence and possible risk factors of small intestinal bacterial overgrowth(SIBO) in patients with chronic kidney disease(CKD). Methods : 92 patients with CKD were selected as subjects.SIBO was assessed by lactulose hydrogen methane breath test(LHMBT),fat tissue index(FTI) was determined using multifrequency bioelectrical impedance analysis, and gastrointestinal symptoms were evaluated by gastrointestinal symptom rating scale(GSRS).According to the results of LHMBT,the patients were divided into SIBO group and non-SIBO group.The demographic data, laboratory and clinical indicators, gastrointestinal symptoms and other differences between the two groups were compared.Binomial logistic stepwise regression was used to analyze the possible risk factors of SIBO in CKD patients. Results : The incidence of SIBO in these 92 patients was 47.8%.Compared with the non-SIBO group, the GSRS score of the SIBO group was higher, and the difference was statistically significant [(23.27±3.97)vs(21.13±4.39),t=2.451,P=0.016].Multivariate stepwise logistic regression analysis showed that low serum potassium(OR=0.396,95%CI0.176-0.893,P=0.025) and high FTI(OR=1.182,95%CI1.037-1.348,P=0.013) were independent risk factors for SIBO in patients with CKD. Conclusion The incidence of SIBO is high in CKD patients.Symptoms of dyspepsia are more prominent in SIBO positive patients.Low serum potassium and high FTI are independent risk factors for SIBO in patients with CKD.