Objective To investigate the effects of ubiquitin-like modifier activating enzyme 1(UBA1) on the proliferation and apoptosis of acute myeloid leukemia(AML) cells(HL60 and THP-1 cells) and its mechanism, so as to evaluate the possibility of using UBA1 as a molecular marker and target for diagnosis and treatment of AML. Methods The expression of UBA1 in HL60 and THP-1 cells was inhibited via shRNA interference, and stable transfection cell lines were screened. The inhibition effect was detected by qPCR and Western blot. The effect of inhibiting UBA1 on proliferation of AML cells was measured by CCK-8 assay. Flow cytometry was used to detect the effect of inhibiting UBA1 on apoptosis of AML cells. The effects on the expression of apoptosis proteins(Bax, Bc12), cell cycle regulation related proteins(CDK4, CDK6 and CyclinD1) and MAPK signaling pathway related proteins(P-ERK, P-JNK, P-P38MAPK, T-ERK, T-P38) in AML cells were determined by Western blot. Results Following UBA1 knockdown, both HL60 and THP-1 cells exhibited a significant reduction in UBA1 mRNA transcription and protein expression levels(t = 2. 065-43. 591, each P < 0. 05). Cell proliferation capacity was significantly suppressed(t = 12. 274-17. 252, each P < 0. 05), while the apoptosis rate increased significantly(t = 12. 690-18. 855, P <0. 05). The pro-apoptotic protein Bax was significantly upregulated(t = 17. 094-20. 781, P < 0. 01), whereas the anti-apoptotic protein Bcl-2 was downregulated(t = 42. 494-53. 050, P < 0. 01). The expression levels of cell cycle regulatory proteins CDK4, CDK6, and Cyclin D1 all significantly decreased(t = 12. 193-51. 666, each P < 0. 05). The expression levels of P-ERK and P-P38MAPK in MAPK signaling pathway increased significantly(t = 3. 759-10. 822, each P < 0. 05),but the expression levels of P-JNK, T-ERK and T-P38 had no statistically significant difference(t = 0. 133-1. 794, each P >0. 05). Conclusion Interference with the expression of UBA1 can inhibit the proliferation of HL60 and THP-1 cells and promote their apoptosis, of which the mechanism may be related to the increased expression of P-ERK and P-P38MAPK proteins in MAPK signaling pathway.

Objective To investigatethe relationship between gastroesophageal reflux disease (GERD) symptoms and clinicopathological characteristics, p53 expression, and survival of Chinese patients with esophageal adenocarcinoma. Methods A total of 3882 patients with esophageal adenocarcinoma, 970 matched patients with esophageal squamous cell carcinoma, and 970 matched patients with gastric cardia adenocarcinoma were included to compare the incidence of GERD symptoms. Patients with esophageal adenocarcinoma were divided into two groups according to the presence and absence of GERD symptoms. The differences in clinicopathological characteristics and p53 expression between the two groups were compared by chi-square test, and the differences in survival between the two groups were compared by landmark analysis. Results The incidence of GERD symptoms increased successively in esophageal squamous cell carcinoma, esophageal adenocarcinoma, and gastric cardia adenocarcinoma. In patients with esophageal adenocarcinoma, the proportions of male, less than 65 years old, lower thoracic tumors, tumors without squamous cell carcinoma, poorly differentiation, early tumors (stage 0-I), and p53-positive tumors in the group with GERD symptoms were higher than those in the group without GERD symptoms; moreover, the long-term survival (≥15 years) was better. Conclusion GERD symptom is an important clinical sign of esophageal adenocarcinoma. It is closely related to specific clinicopathological characteristics, p53 overexpression, and good long-term prognosis.

Chronic hepatitis B virus (HBV) infection remains a major global public health concern. The persistent presence of intrahepatic covalently closed circular DNA (cccDNA) poses a major challenge to the complete cure of chronic HBV infection. Therefore, identifying reliable and effective serological surrogate markers for cccDNA holds great clinical significance in evaluating antiviral efficacy, predicting prognosis, and guiding the clinical management of chronic HBV-infected patients. In recent years, serum HBV RNA has emerged as a promising non-invasive alternative marker for cccDNA, offering the potential for monitoring disease progression and predicting prognosis in chronic HBV-infected patients. In this review, we summarize recent studies on HBV RNA, highlighting its ability to assess the immune and histological status of patients, and discussing its value in guiding the timing of antiviral therapy. Furthermore, we systematically summarize the clinical significance of HBV RNA in multiple domains: monitoring viral replication, evaluating antiviral treatment efficacy, predicting relapse after treatment cessation, and guiding new antiviral strategies. This review aims to provide clinicians with valuable insights for better utilizing this marker in the clinical management of chronic HBV infection.

Objective:To explore the changes in behavioral indexes and electroencephalogram (EEG) in the stage of temporal memory retrieval under different extraction times.Methods:A total of 30 healthy subjects were randomly selected from Shanghai University of Science and Technology in November 2022. The reaction time and EEG of the subjects in the 1 500 ms stage of temporal memory retrieval were recorded by a reproduction method of time estimation task. The memory error rate, precision, accuracy, and low-frequency power of EEG were calculated, and time-frequency analysis and traceability analysis were carried out. Pearson correlation analysis was used to analyze the correlation between memory error rate, accuracy, θ rhythm, and β rhythm.Results:The main effects of time difference and memory precision between retrieval times were found [ F(3, 1 196) = 2.932, P = 0.033; F(3, 1 196) = 3.191, P = 0.026], and they increased with the extraction times. There was no main effect on memory accuracy, but as the number of extractions increases, the average accuracy increased. With the increase in memory retrieval times, the power of θ rhythm in the left frontal lobe gradually increased [ F(3, 116) = 2.668, P = 0.035], and the average power of β rhythm in the middle frontal lobe gradually decreased [ F(3, 116) = 2.810, P = 0.029]. The differences in current density distribution in the somatosensory cortex (BA7), dorsolateral prefrontal cortex (BA9), and premotor cortex (BA6) increased in the first and second, second and third, and third and fourth memory retrievals ( P < 0.01). The θ rhythm was positively correlated with memory accuracy ( r = 0.258, P < 0.05), and the β rhythm was negatively correlated with memory precision ( r = ? 0.404, P < 0.01). Conclusions:In the stage of temporal memory extraction, increasing the number of temporal memory extraction times can reduce the memory error rate and improve accuracy. Memory accuracy is related to the power of the θ rhythm in the left frontal lobe and the power of the β rhythm in the middle frontal lobe.

Alzheimer’s disease (AD) is a neurodegenerative disease that has become increasingly serious with the aging of human society. It has become an important factor that hinders the development of society, making early diagnosis and intervention of great significance. In recent years, with the continuous development of computer technology, deep learning has shown superior performance in processing AD big data, identifying effective detection indices, and improving detection accuracy. In this paper, the research progress of deep learning in early diagnosis of AD in areas such as neuroimaging data, electroencephalogram, blood and genetic data, and multimodal fusion data was mainly introduced. Common deep learning models were summarized, and future research directions in this field were discussed.

Objective:To analyze the electroencephalogram (EEG) features of patients with Alzheimer’s disease (AD) and mild cognitive impairment (MCI), and to combine the characteristics for classification and prediction.Methods:One hundred and thirty-five patients attending the Department of Neurology at the General Hospital of Tianjin Medical University were enrolled, including 34 patients with AD, 67 patients with MCI, and 34 healthy control (HC). The electroencephalogram signals of these patients in the resting state were collected and preprocessed. Relative power spectral density features and sample entropy features on a multi-band scale were extracted to compare the whole-brain differences in electroencephalogram features among the 3 groups of subjects, and then subdivided into brain regions and individual leads for in-depth analysis. The above two features were fused to classify and predict AD, MCI, and HC by support vector machine (SVM).Results:The frontal regions had higher δ relative power spectral densities than the other regions, and the occipital and temporal regions showed relatively lower distributions. θ-Band relative power spectral densities had a more even distribution of sizes across brain regions. α-Band relative power spectral densities were concentrated in the occipital lobe, while β-band relative power spectral densities were mainly concentrated in the parietal and temporal lobes. Except for the central lobe, the δ-band relative power spectral densities of the AD group were higher than those of the MCI group ( P < 0.05) and HC group ( P < 0.01) in all brain regions and the whole brain. θ-band relative power spectral densities of the AD group were higher than those of the MCI gourp ( P < 0.001) and HC group ( P < 0.001) in the whole brain and in all brain regions. α-Band relative power spectral densities of the AD group were lower than those of the other groups only in the temporal lobe (all P < 0.05). The relative power spectral density of the β-band in the AD group was higher than that of the other groups in the whole brain and in all brain regions ( P < 0.05, 0.01, 0.001). The difference in the relative power spectral density of the δ-band in the C3 lead in the central lobe of the AD and HC groups was statistically significant ( P < 0.05). The relative power spectral density of the γ-band in the temporal lobe was higher than that in the other regions of the AD group, the MCI group, and the HC group. The relative power spectral density of the γ-band in the T3 lead in the AD group was significantly lower than that in the T4 lead. The average entropy of samples in the whole brain and in each brain region was lower than that in the HC group in the AD and MCI groups (all P < 0.05). The entropy of the samples at lead C3 in the AD group was lower than that in the MCI group ( P < 0.05). The differences between the relative power spectral density, sample entropy, and the actual data classification evaluation indexes (accuracy rate, precision rate, recall rate, and F1 score) that fused the two features, and the rearranged data were all statistically significant (all P < 0.001). When the relative power spectral density feature and the sample entropy feature were fused in the classification features, the best classification prediction was achieved, with an accuracy rate of 80%, a precision rate of 78%, a recall rate of 78%, and the F1 score of 79%. Conclusions:Relative power spectral density and sample entropy analysis can reveal the abnormalities of electroencephalogram activities of AD and MCI patients from different perspectives (linear and nonlinear), and the combination of these two features in classification prediction can improve the classification effect.

Objective:To investigate the influences of Neferine(Nef)on inflammatory injury in nephrotic syndrome(NS)rats by regulating the MAPK/NF-κB pathway.Methods:SD rats were separated into control check group(CK group),Model group,low-dose Nef group(Nef-L group,2.5 mg/kg),high-dose Nef group(Nef-H group,5 mg/kg),prednisone acetate group(PA group,6.3 mg/kg),Anisomycin(MAPK agonist)group(5 μmol/L),Nef-H+Anisomycin group(5 mg/kg+5 μmol/L),with 12 rats in each group.Except for the CK group,all other groups were injected with doxorubicin through the tail vein to induce the NS rat model.Rats in CK group were injected with an equal volume of normal saline through the tail vein at the same time.After successful modeling,dosing treatment was performed once a day for 4 weeks.Detected 24-hour urine protein content,serum creatinine(Scr),albumin(ALB),urea nitro-gen(BUN)levels,renal tissue pathology,and levels of TNF-α,IL-6,and IL-1β in renal tissue;TUNEL staining was performed to detect cell apoptosis in rat kidney tissue;Western blot was performed to detect the expression of p-p38,p-JNK,p-ERK1/2 and p-NF-κB p65 proteins in rat kidney tissue.Results:Compared with CK group,Model group had severe renal tissue pathological damage,the 24 h urinary protein,Scr,BUN,TNF-α,IL-6,IL-1β,apoptosis rate,p-p38,p-JNK,p-ERK1/2,p-NF-κB p65 protein expressions were increased,while ALB level was decreased(P<0.05);compared with Model group,the renal tissue pathological damage of rats in Nef-L group,Nef-H group and PA group were severe,the 24 h urinary protein,Scr,BUN,TNF-α,IL-6,IL-1β,apoptosis rate,p-p38,p-JNK,p-ERK1/2,p-NF-κB P65 protein expressions were decreased,while ALB level was increased,the renal tissue pathological damage in the Anisomycin group was aggravated,the 24 h urinary protein,Scr,BUN,TNF-α,IL-6,IL-1β,apoptosis rate,p-p38,p-JNK,p-ERK1/2,p-NF-κB p65 protein expressions were increased,while ALB level was decreased(P<0.05);Anisomycin attenu-ated the effects of high doses of Nef on NS rats.Conclusion:Nef may alleviate the inflammatory injury in NS rats by inhibiting MAPK/NF-κB signaling pathway.

Objective:To explore the risk factors of severe acute kidney injury (AKI) in septic patients, and to establish an hour-specific prediction model.Methods:Based on the information of septic patients in the Medical Information Mart for Intensive Care-Ⅳ (MIMIC-Ⅳ) database, general information, comorbidities, vital signs, severity scoring system, laboratory indicators, invasive operations and medication use were recorded. The enrolled patients were randomized into a training set and a validation set according to a ratio of 7∶3. AKI was diagnosed according to the guidelines of Kidney Disease: Improving Global Outcome (KDIGO). Based on Lasso regression and Cox regression, the risk factors of severe AKI (AKI stage 2 and stage 3) in septic patients were analyzed and hour-specific prediction model were established. Consistency index (C-index), area under the receiver operator characteristic curve (AUC) and calibration curve were used to assess the predictive efficacy of the model.Results:A total of 20 551 septic patients were enrolled, including 14 385 patients in the training set and 6 166 patients in the validation set. Multivariate Cox regression analysis showed that atrial fibrillation [hazard ratio ( HR) = 1.266, 95% confidence interval (95% CI) was 1.150-1.393], heart failure ( HR = 1.348, 95% CI was 1.217-1.493), respiratory failure ( HR = 1.565, 95% CI was 1.428-1.715), heart rate ( HR = 1.004, 95% CI was 1.002-1.007), mean arterial pressure ( HR = 1.245, 95% CI was 1.126-1.377), lactic acid ( HR = 1.051, 95% CI was 1.025-1.077), simplified acute physiology score Ⅱ (SAPSⅡ, HR = 1.019, 95% CI was 1.016-1.023), serum creatinine ( HR = 1.171, 95% CI was 1.127-1.216), anion gap ( HR = 1.024, 95% CI was 1.010-1.038), serum potassium ( HR = 1.155, 95% CI was 1.079-1.236), white blood cell count ( HR = 1.006, 95% CI was 1.003-1.009) and furosemide use ( HR = 0.414, 95% CI was 0.368-0.467) were independently associated with severe AKI in septic patients (all P < 0.01). The above predictors were applied to construct an hour-specific prediction model for the occurrence of severe AKI in septic patients. The C-index of the prediction model was 0.723 and 0.735 in the training and validation sets, respectively. The AUC for the occurrence of severe AKI at 12, 24, and 48 hours were 0.795 (95% CI was 0.782-0.808), 0.792 (95% CI was 0.780-0.805), and 0.775 (95% CI was 0.762-0.788) in the training set, and the AUC were 0.803 (95% CI was 0.784-0.823), 0.791 (95% CI was 0.772-0.810), and 0.773 (95% CI was 0.752-0.793) in the validation set, respectively. The calibration curves of the two cohorts were in good agreement. Conclusion:The hour-specific prediction model effectively identifies high-risk septic patients for developing severe AKI within 48 hours, aiding clinicians in stratifying patients for early therapeutic interventions to improve outcomes.

Objective To investigate the current status of mini-CEX scores among students in the Elderly Service Man-agement program after completing the"Fundamentals of Nursing"course and analyze the influencing factors.Methods A total of 99 students from the Elderly Service Management program at the Wuming campus of Guangxi Medical University were selected as the study subjects.Assessment tools included a general information questionnaire,the Chinese version of the Mini Clinical E-valuation Exercise(mini-CEX),the Self-Rating Scale of Self-Directed Learning(SRSSDL),and a self-learning ability assess-ment scale.Stepwise linear regression analysis was employed to explore the factors affecting mini-CEX scores.Results The total mini-CEX score for the 99 students was 49.00(44.00,55.00).Stepwise linear regression analysis revealed that being a student leader,SRSSDL scores,self-learning ability,and teaching model were significant factors(P＜0.05),explaining 56.8％of the total variance.Conclusion The clinical comprehensive ability of students in the Elderly Service Management program requires enhancement,influenced by multiple factors including teaching model,self-learning ability,and self-directed learning capacity.

Objective:To investigate the changes in plasma ghrelin and influencing factors of weight loss effects after laparoscopic sleeve gastrectomy combined with fundoplication surgery (LSGFD).Methods:The retrospective cohort study was conducted. The clinical data of 115 obesity patients who were admitted to the People′s Hospital of Xinjiang Uygur Autonomous Region from April to June 2023 were collected. There were 37 males and 78 females, aged (37±9)years. Of 115 pati-ents, 93 cases undergoing laparoscopic sleeve gastrectomy (LSG) were divided into the LSG group, and 22 cases undergoing LSGFD were divided into the LSGFD group. Measurement data with normal distribution were represented as Mean± SD, and the independent sample t test was used for com-parison between groups. Count data were described as absolute numbers, and the chi-square test was used for comparison between groups. Repeated measurement data were analyzed using the repeated ANOVA, and their variances were tested using a spherical test. The Logistic regression model was used for univariate and multivariate analyses. Results:(1) Changes in preoperative and postoperative plasma ghrelin in two groups of patients. The plasma ghrelin of patients at preopera-tive and postoperative 6 months changed from (16±14)×10 2 ng/L to (10±4)×10 2 ng/L in the LSG group and changed from (12±11)×10 2 ng/L to (11±3)×10 2 ng/L in the LSGFD group. There was no significant difference in the time effect, inter group effect, and interaction effect of changes in plasma ghrelin between the LSG group and the LSGFD group before and after surgery at 6 months ( Ftime=2.199, Fgroup=0.001, Finteraction=0.793, P>0.05). There was a significant difference in plasma ghrelin in the LSG group before and after surgery at 6 months ( t=4.148, P<0.05), and there was no significant difference in plasma ghrelin in the LSGFD group before and after surgery at 6 months ( t=0.622, P>0.05). (2) Changes in preoperative and postoperative weight loss and metabolic related indicators in two groups of patients. ① There was a significant difference in the time effect of changes in body mass between the LSG group and the LSGFD group before and after surgery at 6 months ( Ftime=242.285, P<0.05), and there was no significant difference in the inter group effect and interaction effect of changes in body mass between the LSG group and the LSGFD group before and after surgery at 6 months ( Fgroup=1.163, Finteraction=0.606, P>0.05). There were significant differences in body mass in the LSG group or the LSGFD group before and after surgery at 6 months ( t=23.597, 14.680, P<0.05). ② There was a significant difference in the time effect of changes in body mass index (BMI) between the LSG group and the LSGFD group before and after surgery at 6 months ( Ftime=382.431, P<0.05), and there was no significant difference in the inter group effect and interaction effect of changes in BMI between the LSG group and the LSGFD group before and after surgery at 6 months ( Fgroup=1.619, Finteraction=1.085, P>0.05). There were significant differences in BMI in the LSG group or the LSGFD group before and after surgery at 6 months ( t=25.645, 16.628, P<0.05). ③ There was a significant difference in the time effect of changes in excess weight loss (%EWL) between the LSG group and the LSGFD group after surgery at 1 to 6 months ( Ftime=666.136, P<0.05), and there was no significant difference in the inter group effect and interaction effect of changes in %EWL between the LSG group and the LSGFD group after surgery at 1 to 6 months ( Fgroup=0.127, Finteraction=0.498, P>0.05). ④ There was no significant difference in the time effect, inter group effect, and interaction effect of changes in fasting blood glucose between the LSG group and the LSGFD group before and after surgery at 6 months ( Ftime=1.573, Fgroup=1.872, Finteraction=0.948, P>0.05). There was a significant difference in fasting blood glucose in the LSG group before and after surgery at 6 months ( t=2.675, P<0.05), and there was no significant difference in fasting blood glucose in the LSGFD group before and after surgery at 6 months ( t=1.074, P>0.05). ⑤ There were significant differences in the inter group effect and interaction effect of changes in triglyceride between the LSG group and the LSGFD group before and after surgery at 6 months ( Fgroup=8.419, Finteraction=3.180, P<0.05), and there was no significant diffe-rence in the time effect of changes in triglyceride between the LSG group and the LSGFD group before and after surgery at 6 months ( Ftime=1.398, P>0.05). Results of individual effect shown that there was no significant difference in triglyceride in the LSG group or the LSGFD group before and after surgery at 3 months ( F=2.956, 3.248, P>0.05), and there were significant differences in trigly-ceride in the LSG group or the LSGFD group after surgery at 1 month and 6 months ( F=14.152, 3.477, P<0.05). There was a significant difference in triglyceride in the LSG group before and after surgery at 6 months ( t=3.164, P<0.05), and there was no significant difference in triglyceride in the LSGFG group before and after surgery at 6 months ( t=0.023, P>0.05). ⑥ There were significant differences in the time effect and inter group effect of changes in total cholesterol between the LSG group and the LSGFD group before and after surgery at 6 months ( Ftime=3.662, Fgroup=7.591, P<0.05), and there was no significant difference in the interaction effect of changes in total cholesterol between the LSG group and the LSGFD group before and after surgery at 6 months ( Finteraction=0.626, P>0.05). There was a significant difference in cholesterol in the LSG group before and after surgery at 6 months ( t=3.253, P<0.05), and there was no significant difference in total cholesterol in the LSGFG group before and after surgery at 6 months ( t=1.567, P>0.05). ⑦ There were significant differences in the time effect and inter group effect of changes in uric acid between the LSG group and the LSGFD group before and after surgery at 6 months ( Ftime=15.306, Fgroup=4.244, P<0.05), and there was no significant difference in the interaction effect of changes in uric acid between the LSG group and the LSGFD group before and after surgery at 6 months ( Finteraction=0.968, P>0.05). There were significant differ-ences in uric acid in the LSG group or the LSGFG group before and after surgery at 6 months ( t=6.152, 3.660, P<0.05). (3) Analysis of influencing factors on postoperative weight loss effects. Results of multivariate analysis showed that preoperative BMI, postoperative 6 months plasma ghrelin were independent protective factors for postoperative weight loss effects ( odds ratio=0.881, 0.673, 95% confidence interval as 0.817-0.950, 0.577-0.787, P<0.05). Conclusions:The decrease in plasma ghrelin in patients after LSGFD is not as obvious as that in patients after LSG, but it can achieve the same weight loss and metabolic improvement effects as after LSG. The lower preoperative BMI and postoperative 6 months plasma ghrelin are independent protective factors for postoperative weight loss effects.