Objective To investigate the seroprevalence of antibody against Toxoplasma gondii among patients with hematological malignancies, and compare it with that among health individuals, so as to provide insights into unraveling the pathogenesis of hematological malignancies. Methods A total of 225 patients with hematological malignancies in Department of Hematology, Xuzhou Central Hospital and 300 healthy individuals in the same hospital were enrolled from 2017 to 2024. Blood samples were collected from all subjects, and the serum IgG and IgM antibodies against T. gondii were detected using chemiluminescent immunoassay. Demographic and clinical features were collected from patients with hematological malignancies, including gender, age, contact with cats, consumption of raw or undercooked meat, type of malignancy, clinical symptoms, blood transfusion and treatment, and the seroprevalence of anti-T. gondii antibody was compared among patients with different characteristics. Results The age (t = 0.72, P > 0.05) and gender (χ² = 0.93, P > 0.05) were compared between patients with hematological malignancies and healthy individuals. The seroprevalence of T. gondii infection was 20.89% among patients with hematological malignancies and 4.33% among healthy individuals (χ² = 34.81, P < 0.01), and the seroprevalence of anti-T. gondii IgG antibody was 20.89% among patients with hematological malignancies and 4.33% among healthy individuals (χ² = 34.81, P < 0.01), while there was no significant difference in the seroprevalence of anti-T. gondii IgM antibody between patients with hematological malignancies and healthy individuals (1.33% vs. 0; corrected χ² = 2.02, P > 0.05). The seroprevalence of T. gondii infection was 23.08% among patients with leukemia, 16.67% among patients with lymphoma, 19.23% among patients with multiple myeloma, 24.00% among patients with myeloproliferative neoplasm, and 26.09% among patients with myelodysplastic syndrome (χ² = 1.44, P > 0.05), and was all higher than among healthy individuals (corrected χ² = 23.92, 10.74, 13.76, 12.84 and 14.54; all P values < 0.01). In addition, there were no significant differences in the detection of anti-T. gondii antibody among patients with hematological malignancies in terms of gender, age, contact with cats, consumption of raw or undercooked meat, chemotherapy or blood transfusion (χ² = 0.76, 1.97, 0, 2.81, 2.38 and 0.66; all P values > 0.05). Conclusions There is a high risk of T. gondii infection among patients with hematological malignancies, and intensified surveillance of T. gondii infection is recommended among patients with hematological malignancies.

OBJECTIVE To explore the significance of pharmaceutical care through the diagnosis and treatment of a patient with exogenous insulin autoimmune syndrome （EIAS）， combined with the analysis of literature reports. METHODS Clinical pharmacist participated in the diagnosis and treatment process of one case of EIAS. Based on the characteristics of the patient’s condition， the pharmacist provided medication suggestions and formulated pharmaceutical monitoring measures. At the same time， the pharmacist searched for relevant literature on insulin autoimmune syndrome （IAS） and EIAS， extracted data （gender， age， occurrence time， laboratory tests， clinical symptoms， intervention and outcome）， and conducted analysis. RESULTS Based on the patient’s medication information in the past 3 years， clinical pharmacist determined that the EIAS was likely caused by insulin aspartate 30. The clinician adopted the clinical pharmacist’s suggestion to discontinue insulin and switch to oral hypoglycemic drugs. The patient improved after treatment. The literature analysis showed that among the 257 patients with IAS reported， 212 cases were caused by drugs； among them， 23 cases were caused by lipoic acid， and 56 cases were caused by exogenous insulin. There were no significant differences in age， glycosylated hemoglobin， and body mass index between the two groups. The lowest blood glucose level in the lipoic acid group was significantly lower than that in the exogenous insulin group （P＜0.05）. The proportion of females and the proportion of fasting insulin ≥ 1 000 μU/mL were significantly higher in the lipoic acid group than in the exogenous insulin group （P＜0.05）. CONCLUSIONS Compared with EIAS， lipoic acid-induced IAS usually causes more severe hypoglycemia， and the fasting insulin level is usually higher than 1 000 μU/mL， which is more common in female patients. The participation of clinical pharmacists in the diagnosis and treatment of EIAS can help improve the diagnosis and treatment level of similar rare diseases and ensure the safety of patients’ medication.

ObjectiveTo compare the clinical features of patients with hepatitis B virus （HBV）-related early-onset liver cancer and those with late-onset liver cancer， to assess the severity of the disease， and to provide a theoretical basis for the early diagnosis and treatment of liver cancer. MethodsA retrospective analysis was performed for 695 patients who were diagnosed with HBV-related liver cancer for the first time in Guangzhou Eighth People’s Hospital， Guangzhou Medical University， from January 2019 to August 2023， among whom 93 had early-onset liver cancer （defined as an age of50 years for female patients and40 years for male patients） and 602 had late-onset liver cancer （defined as an age of ≥50 years for female patients and ≥40 years for male patients）. Related clinical data were collected， including demographic data， clinical symptoms at initial diagnosis， comorbidities， smoking history， drinking history， family history， routine blood test results， biochemical parameters of liver function， serum alpha-fetoprotein（AFP）， virological indicators， coagulation function， and imaging findings. The pan-inflammatory indices neutrophil-to-lymphocyte ratio （NLR）， platelet-to-lymphocyte ratio （PLR）， and lymphocyte-to-monocyte ratio （LMR） were calculated， as well as FIB-4 index， aspartate aminotransferase-to-platelet ratio index （APRI）， S index， Model for End-Stage Liver Disease （MELD） score， Child-Turcotte-Pugh （CTP） score， albumin-bilirubin （AIBL） grade， and Barcelona Clinic Liver Cancer （BCLC） stage. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Wilcoxon rank-sum test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test or Fisher’s exact test were used for comparison of categorical data between two groups. ResultsThere were significant differences between the two groups in the proportion of male patients and the incidence rates of diabetes， hypertension， and fatty liver disease （χ²=6.357， 15.230， 11.467， and 14.204， all P0.05）， and compared with the late-onset liver cancer group， the early-onset liver cancer group had a significantly higher proportion of patients progressing to liver cancer without underlying cirrhosis （χ²=24.657， P0.001） and a significantly higher proportion of patients with advanced BCLC stage （χ²=6.172， P=0.046）. For the overall population， the most common clinical symptoms included abdominal distension， abdominal pain， poor appetite， weakness， a reduction in body weight， edema of both lower limbs， jaundice， yellow urine， and nausea， and 55 patients （7.9%） had no obvious symptoms at the time of diagnosis and were found to have liver cancer by routine reexamination， physical examination suggesting an increase in AFP， or radiological examination indicating hepatic space-occupying lesion； compared with the late-onset liver cancer group， the patients in the early-onset liver cancer group were more likely to have the symptoms of abdominal distension， abdominal pain， and jaundice （all P0.05）. Compared with the late-onset liver cancer group， the early-onset liver cancer group had a significantly larger tumor diameter （Z=2.845， P=0.034）， with higher prevalence rates of multiple tumors and intrahepatic， perihepatic， or distant metastasis （χ²=5.889 and 4.079， both P0.05）， and there were significant differences between the two groups in tumor location and size （χ²=3.948 and 11.317， both P0.05）. Compared with the late-onset liver cancer group， the early-onset liver cancer group had significantly lower FIB-4 index， proportion of patients with HBsAg ≤1 500 IU/mL， and levels of LMR and Cr （all P0.05）， as well as significantly higher positive rate of HBeAg and levels of log₁₀ HBV DNA， AFP， WBC， Hb， PLT， NLR， PLR， TBil， ALT， Alb， and TC （all P0.05）. ConclusionCompared with late-onset liver cancer， patients with early-onset liver cancer tend to develop liver cancer without liver cirrhosis and have multiple tumors， obvious clinical symptoms， and advanced BCLC stage， which indicates a poor prognosis.

Objective To precisely identify the para-Bombay blood types in cancer patients at our hospital, establish a robust system for the identification of challenging blood types in our laboratory, and provide a foundation for precise transfusion practices. Methods We retrospectively analyzed the blood type results of 91 874 cancer patients from January 1, 2019, to December 31, 2023. Conventional serological methods were used to screen for blood types, and suspected para-Bombay blood types were identified. Further analysis was performed using Pacific Biosciences (PacBio) single-molecule real-time sequencing and Sanger sequencing was used to determine the genotypes of the ABO, FUT1, and FUT2 genes. Results Eight cases of para-Bombay blood type were confirmed through serological and molecular biological methods. The FUT1 genotypes identified were: 5 cases of h1h1 (homozygous mutation 551_552delAG) and 3 cases of h1h2 (compound heterozygous mutations of 551_552delAG and 880_882delTT). The FUT2 genotypes identified were: 2 cases of Se³⁵⁷/Se^{357, 716} and 4 cases of Se³⁵⁷/Se³⁵⁷. Additionally, one sample revealed a novel heterozygous mutation, 818C>T, in exon 7 of the ABO gene, which was confirmed by PacBio sequencing to be located on the O haplotype. Conclusion PacBio sequencing technology demonstrates significant advantages in analyzing the haplotypes of para-Bombay blood type genes. This approach supports the establishment of a robust system for the identification of challenging blood types and provides novel evidence for precise transfusion practices in cancer patients.
Humans ; Neoplasms/genetics* ; Fucosyltransferases/genetics* ; ABO Blood-Group System/genetics* ; Male ; High-Throughput Nucleotide Sequencing/methods* ; Galactoside 2-alpha-L-fucosyltransferase ; Female ; Retrospective Studies ; Genotype ; Middle Aged ; Blood Grouping and Crossmatching/methods* ; Adult ; Mutation ; Aged

Alzheimer's disease (AD) is a common neurodegenerative disorder among the elderly, and BuChE has emerged as a potential therapeutic target. In this study, we reported the development of compound 8e, a selective reversible BuChE inhibitor (eqBuChE IC₅₀ = 0.049 μmol/L, huBuChE IC₅₀ = 0.066 μmol/L), identified through extensive virtual screening and lead optimization. Compound 8e demonstrated favorable blood-brain barrier permeability, good drug-likeness property and pronounced neuroprotective efficacy. Additionally, 8e exhibited significant therapeutic effects in zebrafish AD models and scopolamine-induced cognitive impairments in mice. Further, 8e significantly improved cognitive function in APP/PS1 transgenic mice. Proteomics analysis demonstrated that 8e markedly elevated the expression levels of very low-density lipoprotein receptor (VLDLR), offering valuable insights into its potential modulation of the Reelin-mediated signaling pathway. Thus, compound 8e emerges as a novel and potent BuChE inhibitor for the treatment of AD, with significant implications for further exploration into its mechanisms of action and therapeutic applications.

OBJECTIVES: To explore the active components that mediate the therapeutic effect of Centella asiatica on psoriasis and their therapeutic mechanisms. METHODS: TCMSP, TCMIP, PharmMapper, Swiss Target Prediction, GeneCards, OMIM and TTD databases were searched for the compounds in Centella asiatica and their targets and the disease targets of psoriasis. A drug-active component-target network and the protein-protein interaction network were constructed, and DAVID database was used for pathway enrichment analysis. In a RAW264.7 macrophage model of LPS-induced inflammation, the anti-inflammatory effect of 7.5, 15, 30, and 60 μmol/L quercetin, asiaticoside, and asiatic acid, which were identified as the main active components in Centella asiatica, were tested by measuring cellular production of NO, TNF‑α and IL-6 using Griess method and ELISA and by detecting mRNA expressions of IL-23, IL-17A, TNF-α and IL-6 and protein expressions of p-STAT3 (Tyr705) and p-STAT3 (Ser727) with RT-qPCR and Western blotting. RESULTS: A total of 139 targets of Centella asiatica and 4604 targets of psoriasis were obtained, and among them CASP3, EGFR, PTGS2, and ESR1 were identified as the core targets. KEGG analysis suggested that quercetin, asiaticoside, and asiatic acid in Centella asiatica were involved in cancer and IL-17 and MAPK signaling pathways. In the RAW264.7 macrophage model of inflammation, treatment with quercetin significantly reduced cellular production of NO, TNF‑α and IL-6, and lowered mRNA expressions of IL-23, IL-17A, TNF‑α and IL-6 and protein expressions of p-STAT3 (Tyr705) and p-STAT3 (Ser727). CONCLUSIONS Quercetin, asiaticoside and asiatic acid are the main active components in Centella asiatica to mediate the therapeutic effect against psoriasis, and quercetin in particular is capable of suppressing cellular production of NO, TNF‑α and IL-6 and regulating the IL-23/IL-17A inflammatory axis by mediating STAT3 phosphorylation to inhibit inflammatory response.
Quercetin/pharmacology* ; Psoriasis/metabolism* ; STAT3 Transcription Factor/metabolism* ; Mice ; Animals ; Centella/chemistry* ; Triterpenes/pharmacology* ; Phosphorylation ; Interleukin-17/metabolism* ; Interleukin-23/metabolism* ; RAW 264.7 Cells ; Pentacyclic Triterpenes/pharmacology* ; Macrophages/drug effects* ; Signal Transduction ; Plant Extracts

OBJECTIVE: To identify the optimal machine learning algorithm for predicting post-stroke epilepsy (PSE) within one year following acute stroke, establish a nomogram model based on this algorithm, and perform external validation to achieve accurate prediction of secondary epilepsy. METHODS: A total of 870 acute stroke patients admitted to the emergency department of Xiang'an Hospital of Xiamen University from June 2019 to June 2023 were enrolled for model development (model group). An external validation cohort of 435 acute stroke patients admitted to the Fifth Hospital of Xiamen during the same period was used to validate the machine learning algorithms and nomogram model. Patients were classified into control and epilepsy groups based on the development of PSE within one year. Clinical and laboratory data, including baseline characteristics, stroke location, vascular status, complications, hematologic parameters, and National Institutes of Health Stroke Scale (NIHSS) score, were collected for analysis. Nine machine learning algorithms such as logistic regression, CN2 rule induction, K-nearest neighbors, adaptive boosting, random forest, gradient boosting, support vector machine, naive Bayes, and neural network were applied to evaluate predictive performance. The area under the curve (AUC) of receiver operator characteristic curve (ROC curve) was used to identify the optimal algorithm. Logistic regression was used to screen risk factors for PSE, and the top 10 predictors were selected to construct the nomogram model. The predictive performance of the model was evaluated using the ROC curve in both the model and validation groups. RESULTS: Among the 870 patients in the model group, 29 developed PSE within one year. Among the nine algorithms tested, logistic regression demonstrated the best performance and generalizability, with an AUC of 0.923. Univariate logistic regression identified several risk factors for PSE, including platelet count, white blood cell count, red blood cell count, glycated hemoglobin (HbA1c), C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL), aspartate aminotransferase (AST), alanine aminotransferase (ALT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen, creatine kinase (CK), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), serum sodium, lactic acid, anion gap, NIHSS score, brain herniation, periventricular stroke, and carotid artery plaque. Further multivariate logistic regression analysis showed that white blood cell count, HDL, fibrinogen, lactic acid and brain herniation were independent risk factors [odds ratio (OR) were 1.837, 198.039, 47.025, 11.559, 70.722, respectively, all P < 0.05]. In the external validation group, univariate logistic regression analysis showed that platelet count, white blood cell count, CRP, triacylglycerol, APTT, D-dimer, fibrinogen, CK, CK-MB, LDH, NIHSS score, and cerebral herniation were risk factors for PSE one year after acute stroke. Further multiple logistic regression analysis showed that APTT and cerebral herniation were independent predictors (OR were 0.587 and 116.193, respectively, both P < 0.05). The nomogram model, constructed using 10 key variables-brain herniation, periventricular stroke, carotid artery plaque, white blood cell count, triglycerides, thrombin time, D-dimer, serum sodium, lactic acid, and NIHSS score-achieved an AUC of 0.908 in the model group and 0.864 in the external validation group. CONCLUSIONS The logistic regression-based prediction model for epilepsy one year after acute stroke, developed using machine learning algorithms, showed optimal predictive performance. The nomogram model based on the logistic regression-derived predictors showed strong discriminative power and was successfully validated externally, suggesting favorable clinical applicability and generalizability.
Humans ; Machine Learning ; Stroke/complications* ; Nomograms ; Epilepsy/etiology* ; Algorithms ; Male ; Female ; Logistic Models ; Middle Aged ; Aged ; Risk Factors ; Bayes Theorem

Objective To analyze the expression levels of serum microRNA(miR)-211 and miR-202 in patients with Alzheimer's disease and their correlation with cognitive function,anxiety and depression.Methods A total of 90 patients with Alzheimer's disease admitted to Hebei Yanda Hospital from March 2019 to March 2022 were selected as the research group.According to the Clinical Dementia Rating(CDR)score,the patients were grouped into mild group(n=24),moderate group(n=48)and severe group(n=18).Another 90 healthy individuals who underwent physical examination were collected as the control group.The expression levels of miR-211 and miR-202 in serum were compared.Pearson method and Spearman method were used to analyze serum miR-211 and miR-202 and their correlation with cognitive function,anxiety and depression.Logistic regression analysis was used to analyze the influencing factors of Alzheimer's disease.Results The expression levels of serum miR-211(0.59±0.16,1.01±0.31)and miR-202(0.35±0.10,1.00±0.32)were significantly reduced in the research group and control group,with significant differences(t=11.422,18.393,all P<0.05).Serum miR-211(0.73±0.21,0.62±0.17,0.32±0.08)expression levels,miR-202(0.51±0.15,0.33±0.10,0.19±0.04)expression levels,mini-mental state examination(MMSE)score(22.54±1.41 score,19.35±1.01 score,16.23±1.00 score)and Montreal cognitive assessment(MoCA)score(25.35±2.60 score,18.59±1.32 score,16.59±1.24 score)in the mild,moderate and severe groups gradually decreased,and the differences were statistically significant(F=32.006,46.917,163.048,163.703,all P<0.05).Compared with mild group,the serum miR-211,miR-202,MMSE and MoCA scores of severe group and moderate group were reduced,and the differences were statistically significant(t=3.685～25.375,all P<0.05).The mild,moderate and severe groups had a gradual increase in Hamilton anxiety scale(HAMA)score(12.34±1.27 score,20.59±2.09 score and 31.29±2.19 score)and Hamilton depression scale(HAMD)score(14.35±2.13 score,23.89±2.20 score and 35.35±1.21 score),and the differences were statistically significant(F=496.059,553.939,all P<0.05).According to Pearson correlation analysis,miR-211 was positively correlated with miR-202(r=0.651,P<0.05).According to Spearman correlation analysis,miR-211 and miR-202 were positively correlated with MMSE and MoCA(r=0.539～0.585,all P<0.05)and negatively correlated with HAMA and HAMD(r=-0.651～-0.539,all P<0.05).Logistic regression analysis showed that the low expression of miR-211[OR(95%CI):5.321(1.648～17.180)]and miR-202[OR(95%CI):3.158(1.989～5.012)]were risk factors for Alzheimer's disease(P<0.05).Conclusion The serum expression levels of miR-211 and miR-202 in patients with Alzheimer's disease were reduced,indicating miR-211 and miR-202 were closely related to cognitive function,anxiety and depression.

Objective To analyze the feasibility and efficacy of a deep convolutional neural network(DCNN)model based on chest CT images to evaluate bone mineral density(BMD).Methods A total of 1 048 health check subjects'2 096 central level images of lumbar 1 and 2 vertebral bodies were used for experiments and analysis in this retrospective study.According to the results of quanti-tative computed tomography(QCT)BMD measurement,the subjects were divided into three categories:normal,osteopenia,osteopo-rosis(OP).Herein,a DCNN segmentation model was constructed based on chest CT images[training set(n=1 096),tuning set(n=200),and test set(n=800)],the segmentation performance was evaluated using the Dice similarity coefficient(DSC)to com-pare the consistency with the manually sketched region of vertebral body.Then,the DCNN classification models 1(fusion feature construction of lumbar 1 and 2 vertebral bodies)and model 2(image feature construction of lumbar 1 alone)was developed based on the training set(n=530).Model performance was compared in a test set(n=418)by the receiver operating characteristic(ROC)curve analysis.Results When the number of images in the training set(n=300)was adopted,the DSC value was 0.950 in the test set.The results showed that the sensitivity,specificity and area under the curve(AUC)of model 1 and model 2 in diagno-sing osteopenia and OP were 0.716,0.960,0.952;0.941,0.948,0.980;0.638,0.954,0.940;0.843,0.959,0.978,respectively.The AUC value of normal model 1 was higher than that of model 2(0.990 vs 0.983,P=0.033),while there was no significant difference in AUC values between osteopenia and OP(P=0.210,0.546).Conclusion A DCNN may have the potential to evaluate bone mass based on chest CT images,which is expected to become an effective tool for OP screening.

Objective:To investigate the application value of the teaching evaluation method guided by cultivating "excellent doctors" in the clinical teaching of dermatology and venereology.Methods:A non-simultaneous control study was conducted, and the medical students who received theoretical learning and clinical internship in Department of Dermatology and Venereology, Affiliated Hospital of North Sichuan Medical College, from March 2020 to February 2022, were enrolled as subjects. According to the order of enrollment, 32 students who were enrolled from March 2020 to February 2021 were set up as control group, and 31 students who were enrolled from March 2021 to February 2022 were set up as experimental group. The students in the control group received lecture-based learning, and those in the experimental group received clinical teaching using a teaching and evaluation method guided by cultivating "excellent doctors". After the course ended, the two groups were compared in terms of the scores of theoretical knowledge and operation skills, clinical thinking ability [Self-Assessment of Clinical Reasoning and Reflection (SACRR)], core competence [Mini-Clinical Evaluation Exercise (Mini CEX)], and degree of satisfaction with teaching. SPSS 25.0 software was used to perform the independent samples t-test, the Mann-Whitney U test, the chi-square test, and the rank sum test. Results:One student in the control group voluntarily withdrew from the study, and one student in the experimental group did not complete the contents of internship. Finally, 31 students in the control group and 30 in the experimental group were included in the study. After 4 weeks of internship, compared with the control group, the experimental group had significantly higher scores of theoretical knowledge (88.00±4.30 vs. 85.71±4.12, t=2.12, P=0.040) and operation skills (91.87±3.99 vs. 88.23±3.84, t=3.63, P<0.05). After 4 weeks of internship, compared with the control group, the experimental group had significantly higher information systematization score (47.23±3.11 vs. 45.16±3.00), analysis problem score (34.87±2.30 vs. 31.29±2.30), truth finding score (16.30±1.49 vs. 14.45±1.52), reflective ability score [3.50 (3.00, 4.00) vs. 3.00 (3.00, 3.00)], and total score of SACRR (101.87±4.47 vs. 93.90±4.47), with significant differences between the two groups ( t/ Z=2.65, 6.17, 4.79, 3.15, and 6.96, all P<0.05). After 4 weeks of internship, the experimental group had a significantly better core competence than the control group ( Z=2.12, P=0.030); compared with the control group, the experimental group had significantly higher classroom teaching score (20.17±1.98 vs. 18.45±2.23, t=3.17, P<0.05), clinical practice score (19.83±2.10 vs. 17.65±2.17, t=4.00, P<0.05), learning plan score (18.63±2.24 vs. 17.03±2.15, t=2.85, P<0.05), teaching resource score (20.07±1.82 vs. 18.58±2.00, t=3.04, P<0.05) and total score (78.70±3.67 vs. 71.71±4.13, t=6.98, P<0.05). Conclusions:The application of the teaching and evaluation method guided by cultivating "excellent doctors" in the clinical teaching of dermatology and venereology can improve clinical theoretical knowledge, practical operation skills, clinical thinking ability, and core ability among interns and thus help to improve teaching quality. Therefore, it holds promise for clinical application.