ObjectiveTo investigate the application of the novel inflammatory factor adsorption column CA280 combined with low-dose plasma exchange （LPE） in patients with acute-on-chronic liver failure （ACLF）. MethodsA prospective cohort study was designed， and a total of 93 ACLF patients who were admitted to The Ninth Hospital of Nanchang from June 2023 to January 2025 were enrolled and randomly divided into DPMAS+LPE group with 50 patients and CA280+LPE group with 43 patients. In addition to comprehensive medical treatment， the patients in the DPMAS+LPE group received DPMAS and LPE treatment， and those in the CA280+LPE group received CA280 and LPE treatment. The two groups were observed in terms of routine blood test results， liver function parameters， renal function markers， electrolytes， coagulation function parameters， cytokines， adverse events， and 28-day prognosis before surgery （baseline）， during surgery （DPMAS or CA280）， and after surgery （after sequential LPE treatment）. The paired t-test was used for comparison of normally distributed continuous data before and after treatment within each group， and the independent-samples t test was used for comparison between groups； the Wilcoxon signed-rank test was used for comparison of non-normally distributed continuous data before and after treatment within each group， and the Mann-Whitney U test was used for comparison between groups. The chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups， and the Spearman test was used for correlation analysis. ResultsAfter CA280 treatment， the ACLF patients had significant reductions in the levels of cytokines （IL-6， IL-8， IL-10， TNF-α， and IFN-γ）， liver function parameters （ALT， AST， ALP， TBil， DBil， Alb， and glutathione reductase）， and the renal function marker urea nitrogen （all P<0.05）， and in terms of coagulation function parameters， there were significant increases in prothrombin time， activated partial thromboplastin time （APTT）， thrombin time， and international normalized ratio （INR） and significant reductions in prothrombin activity （PTA） and fibrinogen （FIB） （all P<0.05）. Compared with the DPMAS+LPE group， the CA280+LPE group showed better improvements in the serum cytokines IL-8 （Z=-2.63， P=0.009）， IL-10 （Z=-3.94， P<0.001）， and TNF-α （Z=-1.53， P=0.023）， and the two artificial liver support systems had a similar effect in improving liver function （ALT， AST， GGT， GR， TBil， and DBil） （all P >0.05）， but the CA280+LPE group showed a significantly greater reduction in Alb （Z=-2.08， P=0.037）. CA280+LPE was more effective in reducing uric acid （Z=-2.97， P=0.003）. Compared with DPMAS+LPE， CA280+LPE treatment resulted in a significant reduction in INR （Z=-4.01， P<0.001）， a significant increase in APTT （Z=-2.53， P=0.011）， and significant greater increases in PTA （Z=-6.28， P<0.001） and FIB （Z=-3.93， P<0.001）. There were no significant differences in the incidence rates of adverse reactions and the rate of improvement at discharge between the two groups （all P>0.05）. The Spearman correlation analysis showed that IL-6 was significantly correlated with WBC （r=0.22， P=0.042）， TBil （r=0.29， P=0.005）， and FIB （r=-0.33， P=0.003）； IL-8 was positively correlated with APTT （r=0.37， P<0.001） and INR （r=0.25， P=0.013）； TNF-α was significantly correlated with WBC （r=0.40， P<0.001） and TBil （r=0.34， P<0.001）. ConclusionCompared with DPMAS， CA280 combined with LPE can effectively clear proinflammatory cytokines and improve liver function in ACLF patients， but it has a certain impact on Alb and coagulation function. This regimen provides a new option for the individualized treatment of ACLF and can improve the short-term prognosis of patients， but further studies are needed to verify its long-term efficacy.

[This corrects the article DOI: 10.1016/j.apsb.2021.07.024.].

Recent studies have revealed a significant association between Porphyromonas gingivalis(P.gingivalis)infection and poor prognosis in esophageal squamous cell carcinoma(ESCC).Although cer-tain circular RNAs(circRNA)have been shown to suppress ESCC tumorigenesis and progression,their regulatory mechanisms in P.gingivalis infection-associated ESCC remain elusive.In this study,RT-qPCR analysis demonstrated that P.gingivalis infection downregulated hsa_circ_0057552 expression in ESCC cells and tissues in a time-and dose-dependent manner.Actinomycin D assays further confirmed that P.gingivalis infection reduced the RNA stability of hsa_circ_0057552 in ESCC cells(P＜0.05).Functional assays in vitro and a subcutaneous tumor xenograft model in vivo revealed that hsa_circ_0057552 overexpression significantly inhibited ESCC cell proliferation,migration,invasion,and tumor growth(P＜0.05).Additionally,PCR array screening combined with RT-qPCR and Western blotting in-dicated that P.gingivalis infection markedly upregulated human antigen R(HuR)expression at both RNA and protein levels(P＜0.05).Mechanistic investigations demonstrated that HuR knockdown signifi-cantly increased hsa_circ_0057552 expression(P＜0.01),whereas hsa_circ_0057552 overexpression had no regulatory effect on HuR.Finally,si-HuR treatment reversed the inhibitory effect of P.gingivalis on hsa_circ_0057552 transcription.This study demonstrated that P.gingivalis may promote the progression of ESCC through a novel mechanism involving the regulation of HuR/hsa_circ_0057552,thereby identif-ying a novel therapeutic target and molecular marker for P.gingivalis-associated ESCC.

Objective To determine the pathogenicity of a novel mutation(c.109_111del)in DKC1 gene of an adult patient,and to analyze the clinical phenotype,immunophenotype and telomere length,so as to provide clues for early clinical identification and diagnosis.Methods The clinical data and peripheral blood samples of the patient were collected for genetic testing and family analysis.The lymphocyte subsets of the patient were detected by Flow cytometry,and the telomere length of the patient and healthy controls were detected by Flow-FISH.Results The main clinical manifestations of the patient were mucocutaneous triad,bone marrow failure and infection.The telomere length of lymphocytes in the patient was significantly shorter than that of healthy controls of the same age,and the absolute value and percentage of lymphocyte subsets were abnormal.Conclusion The clinical manifestations of DC patients are diverse.Flow-FISH detection of telomere length is helpful for early diagnosis of DC patients.

Objective:To explore the application value of the artificial intelligence (AI) morphological assisted analysis system in the pre-classification of blood cells in patients with acute myeloid leukemia, myelodysplasia-related (AML-MR).Methods:A retrospective analysis was conducted on the bone marrow and peripheral blood cell morphology of patients initially diagnosed with AML-MR at Taizhou Hospital in Zhejiang Province from September 1, 2022, to December 31, 2023. A total of 44 patients, including 25 males and 19 females, with a median age of 71 (63.5, 75.3) years. Bone marrow and peripheral blood morphology were examined using the Morphogo cell morphology assisted analysis system, with the artificial classification results serving as the gold standard. A confusion matrix was constructed to evaluate the precision, sensitivity, and specificity of the AI system in identifying various cell types in bone marrow and peripheral blood for AML-MR diagnosis. The impact of dysplastic hematopoiesis on AI pre-classification was analyzed by comparing AI and manual classification results.Results:The AI system completed the pre-classification of 44 bone marrow smears and 42 corresponding peripheral blood smears from AML-MR patients. For bone marrow smears, the precision, sensitivity, and specificity of AI in pre-classifying blast cells were 85.78%, 91.01%, and 94.58%, respectively. For peripheral blood smears, these values were 87.11%, 87.05%, and 98.29%, respectively. The precision and sensitivity of AI in pre-classifying promyelocytes were 54.26% and 46.93%, respectively, while for monocytes, they were 58.16% and 68.34%, both lower than those for blast cells. The precision and sensitivity of AI in identifying myelocytes and metamyelocytes also decreased (77.47%, 66.25% and 81.91%, 63.29%, respectively). The precision and sensitivity of AI in pre-classifying erythroblasts/proerythroblasts (67.71%, 69.89%) were lower than those for polychromatic and orthochromatic normoblasts (83.43%, 85.53% and 92.97%, 86.96%, respectively). The confusion matrix and comparative analysis of AI and manual classification indicated that the decline in AI pre-classification precision and sensitivity was due to frequent misclassification between promonocytes and monocytes, as well as between monocytes and promyelocytes. Additionally, this decline is associated with dysplasia. However, the impact of dysplasia on the AI pre-classification of mature-stage granulocytes was minimal.Conclusion:The AI system demonstrated high precision, sensitivity, and specificity in pre-classifying blast cells in bone marrow and peripheral blood smears from AML-MR patients. The AI-assisted morphological analysis system can be effectively utilized for the pre-classification of blood cells in AML-MR patients.

Objective:To explore the immunophenotypic differences between acute promyelocytic leukemia (APL) and APL-like NPM1 mutant acute myeloid leukemia (NPM1mutAML) using flow cytometry, and to investigate early diagnostic markers for differentiating APL from NPM1mutAML.Methods:A retrospective study was conducted on 72 cases of APL diagnosed at Taizhou Hospital, affiliated with Wenzhou Medical University, from February 2nd, 2018 to December 16th, 2023, including 42 male and 30 female patients with a median age of 42 (32, 57) years old. Based on morphology, 51 cases were classified as the coarse-granular type and 21 cases as the fine-granular type. Additionally, 45 cases of NPM1mutAML, comprising 20 male and 25 female patients with a median age of 58 (47, 65) years old, were included. Of these, 12 cases were classified as the coarse-granular type and 33 as the fine-granular type. Immunophenotypic analysis was performed using multiparameter flow cytometry, and all patients underwent cytogenetic analysis for chromosome karyotyping. FISH analysis was used for detecting the PML-RARα fusion gene in APL cases, and sequencing was used for identifying NPM1 mutations in NPM1mutAML patients. The antigen expression parameters (expression rate, median fluorescence intensity [MdFI], and coefficient of variation [ CV]) were analyzed using principal component analysis (PCA). The antigen expression rates were compared using the Wilcoxon rank-sum test, and the positive rates of antigens were compared using the Chi-square test. Sensitivity and specificity for diagnosis by the some antigens were evaluated using ROC curve analysis. Results:The immunophenotypic analysis revealed that the expression rates of CD123, CD64, CD13, and CD9 were significantly higher in APL compared to NPM1mutAML ( Z values of-6.72, -6.29, -5.63, -7.67, P<0.01). In the coarse-granular type, the expression rates of CD123 and CD9 in APL were also significantly higher than those in NPM1mutAML ( P<0.01). In the fine-granular type, the expression levels of CD123, CD13, CD64, and CD9 were significantly higher in APL than in NPM1mutAML ( P<0.01). ROC curve analysis showed that in the fine-granular type, the areas under the curve (AUC) for CD64, CD13, CD123, and CD9 in diagnosing APL and NPM1mutAML were 0.96, 0.89, 0.86, and 0.89, respectively ( P<0.01). In the coarse-granular type, the AUC for CD64 and CD13 were 0.49 and 0.51 ( P>0.05), while the AUC for CD123 and CD9 were 0.96 and 0.96 ( P<0.01). Principal component analysis (PCA) of antigen expression (expression rate, MdFI, CV) showed complete separation of the APL and NPM1mutAML groups. Conclusion:APL and APL-like NPM1mutAML patients exhibit distinct antigen expression profiles. Specifically, a combined detection of CD64, CD13, CD123, and CD9 can help to rapidly differentiate APL from APL-like NPM1mutAML at initial diagnosis.

Objective To explore the possibility and genetic identification method of constructing a hepatocyte-specific NLRP3 gene knockout mouse model by using Cre-LoxP system gene knockout technology.Methods Phase one:mice specifically expressing the albumin promoter-Cre(AlbCre)recombinase in hepatocytes were mated with NLRP3flox/flox mice,and the hepatocyte-specific NLRP3 gene knockout mice with the genotype of NLRP3flox/flox/AlbCre+/-(hepatocyte NLRP3 knockout group)and the control mice in the same litter with the genotype of NLRP3flox/flox/AlbCre-/-(control group in the same litter)were obtained after two generations of selection and mating.The second stage was the mass reproduction stage.Mating NLRP3flox/flox/AlbCre+/-target mice with NLRP3flox/flox mice could quickly obtain a large number of experimental target mice and control mice in the same litter.The DNA was extracted from the tails of mice after numbering,and the offspring genotype was identified by PCR.qPCR and Western blot were used to detect the mRNA and protein expression levels of NLRP3 gene in the liver tissue.HE staining was used to observe the morphological changes in liver tissues,and serum liver transaminases and inflammatory factors were detected.The changes in body weight,liver-to-body ratio and special circumstances during reproduction and development of mice in the two groups were observed.Results The offspring genotype of the target mice in the F2 generation was consistent with theoretical result of NLRP3flox/flox/AlbCre+/-.The mRNA and protein levels of NLRP3 in liver tissues of mice in the hepatocyte NLRP3 knockout group were significantly lower than those in the control group in the same litter(P<0.05).The mice in the hepatocyte NLRP3 knockout group was not affected in terms of growth,development and reproduction after the NLRP3 gene knockout.There were no statistically significant differences in the body weight,liver-to-body ratio,liver tissue morphology,serum liver transaminase or inflammatory factors between the hepatocyte NLRP3 knockout group and the control group in the same litter(P>0.05).Conclusion The Cre-LoxP gene knockout technology can be used to successfully construct a hepatocyte-specific NLRP3 gene knockout mouse model,providing an important technical support for the next step of studying the function of the NLRP3 gene in the liver at the animal level.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

Objective:To explore the application value of the artificial intelligence (AI) morphological assisted analysis system in the pre-classification of blood cells in patients with acute myeloid leukemia, myelodysplasia-related (AML-MR).Methods:A retrospective analysis was conducted on the bone marrow and peripheral blood cell morphology of patients initially diagnosed with AML-MR at Taizhou Hospital in Zhejiang Province from September 1, 2022, to December 31, 2023. A total of 44 patients, including 25 males and 19 females, with a median age of 71 (63.5, 75.3) years. Bone marrow and peripheral blood morphology were examined using the Morphogo cell morphology assisted analysis system, with the artificial classification results serving as the gold standard. A confusion matrix was constructed to evaluate the precision, sensitivity, and specificity of the AI system in identifying various cell types in bone marrow and peripheral blood for AML-MR diagnosis. The impact of dysplastic hematopoiesis on AI pre-classification was analyzed by comparing AI and manual classification results.Results:The AI system completed the pre-classification of 44 bone marrow smears and 42 corresponding peripheral blood smears from AML-MR patients. For bone marrow smears, the precision, sensitivity, and specificity of AI in pre-classifying blast cells were 85.78%, 91.01%, and 94.58%, respectively. For peripheral blood smears, these values were 87.11%, 87.05%, and 98.29%, respectively. The precision and sensitivity of AI in pre-classifying promyelocytes were 54.26% and 46.93%, respectively, while for monocytes, they were 58.16% and 68.34%, both lower than those for blast cells. The precision and sensitivity of AI in identifying myelocytes and metamyelocytes also decreased (77.47%, 66.25% and 81.91%, 63.29%, respectively). The precision and sensitivity of AI in pre-classifying erythroblasts/proerythroblasts (67.71%, 69.89%) were lower than those for polychromatic and orthochromatic normoblasts (83.43%, 85.53% and 92.97%, 86.96%, respectively). The confusion matrix and comparative analysis of AI and manual classification indicated that the decline in AI pre-classification precision and sensitivity was due to frequent misclassification between promonocytes and monocytes, as well as between monocytes and promyelocytes. Additionally, this decline is associated with dysplasia. However, the impact of dysplasia on the AI pre-classification of mature-stage granulocytes was minimal.Conclusion:The AI system demonstrated high precision, sensitivity, and specificity in pre-classifying blast cells in bone marrow and peripheral blood smears from AML-MR patients. The AI-assisted morphological analysis system can be effectively utilized for the pre-classification of blood cells in AML-MR patients.

Objective:To explore the immunophenotypic differences between acute promyelocytic leukemia (APL) and APL-like NPM1 mutant acute myeloid leukemia (NPM1mutAML) using flow cytometry, and to investigate early diagnostic markers for differentiating APL from NPM1mutAML.Methods:A retrospective study was conducted on 72 cases of APL diagnosed at Taizhou Hospital, affiliated with Wenzhou Medical University, from February 2nd, 2018 to December 16th, 2023, including 42 male and 30 female patients with a median age of 42 (32, 57) years old. Based on morphology, 51 cases were classified as the coarse-granular type and 21 cases as the fine-granular type. Additionally, 45 cases of NPM1mutAML, comprising 20 male and 25 female patients with a median age of 58 (47, 65) years old, were included. Of these, 12 cases were classified as the coarse-granular type and 33 as the fine-granular type. Immunophenotypic analysis was performed using multiparameter flow cytometry, and all patients underwent cytogenetic analysis for chromosome karyotyping. FISH analysis was used for detecting the PML-RARα fusion gene in APL cases, and sequencing was used for identifying NPM1 mutations in NPM1mutAML patients. The antigen expression parameters (expression rate, median fluorescence intensity [MdFI], and coefficient of variation [ CV]) were analyzed using principal component analysis (PCA). The antigen expression rates were compared using the Wilcoxon rank-sum test, and the positive rates of antigens were compared using the Chi-square test. Sensitivity and specificity for diagnosis by the some antigens were evaluated using ROC curve analysis. Results:The immunophenotypic analysis revealed that the expression rates of CD123, CD64, CD13, and CD9 were significantly higher in APL compared to NPM1mutAML ( Z values of-6.72, -6.29, -5.63, -7.67, P<0.01). In the coarse-granular type, the expression rates of CD123 and CD9 in APL were also significantly higher than those in NPM1mutAML ( P<0.01). In the fine-granular type, the expression levels of CD123, CD13, CD64, and CD9 were significantly higher in APL than in NPM1mutAML ( P<0.01). ROC curve analysis showed that in the fine-granular type, the areas under the curve (AUC) for CD64, CD13, CD123, and CD9 in diagnosing APL and NPM1mutAML were 0.96, 0.89, 0.86, and 0.89, respectively ( P<0.01). In the coarse-granular type, the AUC for CD64 and CD13 were 0.49 and 0.51 ( P>0.05), while the AUC for CD123 and CD9 were 0.96 and 0.96 ( P<0.01). Principal component analysis (PCA) of antigen expression (expression rate, MdFI, CV) showed complete separation of the APL and NPM1mutAML groups. Conclusion:APL and APL-like NPM1mutAML patients exhibit distinct antigen expression profiles. Specifically, a combined detection of CD64, CD13, CD123, and CD9 can help to rapidly differentiate APL from APL-like NPM1mutAML at initial diagnosis.