Primary brain calcification(PBC) is a hereditary neurodegenerative disorder with symmetrical calcification in the bilateral basal ganglia and other brain regions as its core imaging feature, and presents diverse heterogeneous clinical manifestations such as movement disorders, cognitive impairment, and psychiatric disturbances. The identification of multiple causative genes has not only facilitated the exploration of PBC pathogenesis but also continuously expanded its phenotypic spectrum. The diagnosis, evaluation, and management of this disease are experiencing pivotal shifts, accompanied by new challenges. In 2025, the first international expert consensus on PBC was published, laying a foundation for the standardized diagnosis and treatment of PBC worldwide. Based on China′s clinical practice and research status, and referring to the international consensus, domestic experts in related fields conducted multiple rounds of discussions, supplemented and revised the contents covering clinical manifestations, auxiliary examinations, diagnostic criteria, differential diagnosis, molecular classification and characteristics, genetic testing and counseling, disease management and treatment of PBC, and finally developed this consensus. This consensus aims to provide guidance for the standardized diagnosis, treatment, and research of PBC in China, help improve the quality of diagnosis and treatment, and drive the steady advancement of relevant research in this field.

Clonorchis sinensis primarily lives in the host liver and biliary system, leading to serious health issues, such as hepatobiliary lesions and cholangiocarcinoma. Establishment of rapid, sensitive and specific tools is of great significance for early diagnosis and management of clonorchiasis. Recently, molecular biological techniques have been widely used for detection of C. sinensis infections. This review summarizes the advances in the major molecular assays for detection of C. sinensis infections in intermediate and definite hosts, including PCR, loop-mediated isothermal amplification, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins system, and high-throughput sequencing, and summarizes the characteristics and application prospects of these assays, so as to provide precision detection and management of C. sinensis infection.

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.

AIM:To explore the impact of chronic stress on postoperative cognitive dysfunction in rats and to elucidate the mechanistic link to histone deacetylase 2(HDAC2).METHODS:A repeated social defeat stress model and a prolonged isoflurane anesthesia model were established in mice.The rats were randomly assigned to four groups:control(Ctrl)group,isoflurane anesthesia(Iso)group,chronic social defeat stress(RSDS)group,and chronic social de-feat stress combined with isoflurane anesthesia(RSDS+Iso)group.Anxiety-like behaviors were evaluated using the social avoidance test and the novelty-suppressed feeding test.Cognitive function was assessed through the novel object recogni-tion test and the Morris water maze.Plasma corticosterone levels were measured via enzyme-linked immunosorbent assay(ELISA).Primary hippocampal neurons were isolated from fetal mouse hippocampi and classified into four groups:con-trol group,chronic stress combined with prolonged isoflurane anesthesia(Cort+Iso)group,CAY-10683 intervention(CAY),and CAY-10683 treatment(CAY+Cort+Iso)group.Cell viability was determined using CCK-8 assay,and pro-tein expression levels of brain-derived neurotrophic factor(BDNF)and HDAC2 were analyzed by Western blot.RE-SULTS:The RSDS mouse model was successfully established,with ELISA results indicating a significant increase in plasma corticosterone levels in mice subjected to chronic stress combined with prolonged isoflurane anesthesia.Behavioral assessments and Western blot analyses revealed that mice exposed to prolonged isoflurane anesthesia following chronic stress showed marked declines in cognitive function and hippocampal BDNF protein expression levels.Additionally,chronic stress significantly elevated HDAC2 protein expression in the hippocampi of mice undergoing prolonged isoflurane anesthesia.Treatment with an HDAC2 inhibitor reduced HDAC2 protein expression in primary hippocampal neurons sub-jected to chronic stress combined with prolonged isoflurane anesthesia,concurrently increasing BDNF protein expression levels.CONCLUSION:Chronic stress significantly worsens postoperative cognitive dysfunction induced by prolonged isoflurane anesthesia,associated with increased HDAC2 protein expression in the hippocampus.Inhibition of HDAC2 ef-fectively counteracts the reduction in BDNF,a protein crucial for cognitive function,caused by the combination of chronic stress and prolonged isoflurane anesthesia.

Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System（BRICS）during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute（CLSI）. Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus（ n=1 544，35.2%），coagulase-negative Staphylococci（ n=1 441，32.9%）， Enterococcus faecium（ n=574，13.1%）， Enterococcus faecalis（ n=385，8.8%），and α-hemolytic Streptococci（ n=187，4.3%）. The prevalence of methicillin-resistant Staphylococcus aureus（MRSA）and methicillin-resistant coagulase-negative Staphylococci（MRCNS）was 26.2%（405/1 544）and 69.8%（1 006/1 441），respectively. Notably，all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility（>97.0%）to cephalobiol，rifampicin，trimethoprim-sulfamethoxazole，linezolid，minocycline，tigecycline，and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium（resistance to vancomycin and teicoplanin：both 1.7%）compared to Enterococcus faecalis（both 0.3%）. The detection rates of MRSA and MRCNS exhibited significant regional variations across the country（ χ2=17.674 and 148.650，respectively，both P<0.001）. No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA（ χ2=14.111， P<0.001）and MRCNS（ χ2=4.828， P=0.028）in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA（ χ2=18.986， P<0.001）and MRCNS（ χ2=4.477， P=0.034）in less developed regions（per capita GDP

Objective:To report the results of bacterial resistant investigation collaborative system（BRICS）on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023，and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period，11 492 strains of Gram-negative bacteria were collected from 60 hospitals，of which 10 098（87.9%）were Enterobacterales and 1 394（12.1%）were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli（50.0%）， Klebsiella pneumoniae（26.1%）， Pseudomonas aeruginosa（5.1%）， Acinetobacter baumannii complex（5.0%）and Enterobacter cloacae complex（4.1%）. The ESBL-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus mirablilis were 46.8%（2 685/5 741），18.3%（549/2 999）and 44.0%（77/175），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（76/5 741）and 15.0%（450/2 999）；32.9%（25/76）and 78.0%（351/450）of CREC and CRKP were sensitive to ceftazidime/avibactam combination，respectively. 94.7%（72/76）and 90.2%（406/450）of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore，57.9%（44/76）and 79.1%（356/450）were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 64.6%（370/573），while more than 80.0% of CRAB complex was sensitive to tigecycline，eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 17.0%（99/581）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China，with statistically significant differences in the prevalence of CREC，CRKP，CRPA and CRAB complex（ χ2=10.6，28.6，10.8 and 19.3， P<0.05）. The prevalence of ESBL-producing Escherichia coli， CREC，CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals（ χ2=12.5，9.8，12.7 and 57.8，all P<0.01）. Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China，and Escherichia coli is ranked in the top，while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend，CREC infecton maintains a low prevalence level，and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.

Objective: To evaluate the efficacy of immune checkpoint inhibitors (ICIs) for fertility-sparing treatment in Lynch syndrome-associated endometrial cancer (LS-EC). Methods: Four LS-EC cases received programmed cell death protein 1 (PD-1) inhibitors for fertility preservation at the Obstetrics and Gynecology Hospital of Fudan University from 2017 to 2023. The clinical data and long-term outcomes were retrospectively reviewed. Results: Case 1, carrying germline MLH1 mutation, was diagnosed with Stage IIAm MMRd (International Federation of Gynecology and Obstetrics 2023) endometrial cancer (EC) at 38 years old. She received PD-1 inhibitor treatment and achieved a pathological complete response (CR) at 42 weeks. Case 2, carrying MLH1 mutation, underwent colorectal cancer surgery at 22 years and was diagnosed with EC and synchronous ovarian cancer at 39 years.After 24-week PD-1 treatment, CR of EC and ovarian cancer was achieved. Case 3, carrying MSH2 mutation, was diagnosed with endometrial atypical hyperplasia (EAH) at 35 years.After receiving 7-month progestin, she had the progressed disease with Stage IA2mMMRd EC and colon cancer was found soon after. She received PD-1 treatment for 18 weeks and achieved a CR of EC. She conceived naturally with full term delivery. Case 4, carrying MSH2 mutation, had a recurrence of Stage IBmMMRd EC 15 months after CR from EAH treated with progestin at 40 years. She received PD-1 treatment for 18 weeks and achieved CR. No recurrence was found in all cases after 3–41 months of follow-up after CR. Conclusion ICIs might be an effective choice for LS-EC patients desiring fertility preservation.

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.