Objective To investigate the association between fibrinogen-to-albumin ratio （FAR） and the overall burden of cerebral small vessel disease （CSVD）， as well as their value in predicting early neurological deterioration （END） in patients with acute ischemic stroke （AIS）. Methods A total of 103 AIS patients who were admitted to our hospital from January 2023 to March 2025 were enrolled. According to the CSVD total burden score， the patients were divided into low burden group （0-2 points） with 58 patients and high burden group （3-4 points） with 45 patients； According to the presence or absence of END， they were divided into END group with 21 patients and non-END group with 82 patients. The weighted generalized additive model combined with smooth curve fitting was used to investigate the correlation between FAR and CSVD total burden score. A logistic regression analysis was used to explore the association of FAR and CSVD total burden score with the prognosis of END in AIS patients. The receiver operating characteristic （ROC） curve was used to assess the value of FAR and CSVD total burden score in predicting END in AIS patients. The restricted cubic spline method was used to analyze the dose-response relationship between FAR and END in AIS patients. The Bootstrap method was used to investigate the mediating effect of CSVD total burden score in the relationship between FAR and END in AIS patients. Results The high burden group had a significantly higher FAR than the low burden group （P<0.05）， and there was a U-shaped relationship between FAR and CSVD total burden score， with an inflection point of 8.14%. Compared with the non-END group， the END group had a significantly higher proportion of patients with a CSVD total burden score of 3-4 points and a significantly higher FAR （P<0.05）. After adjustment for the covariates such as age and sex， FAR （OR=1.918， 95%CI 1.825‒2.157，P<0.05） and CSVD global burden score （OR=2.167，95%CI 2.051‒2.249， P<0.05） were still independently associated with the risk of END in AIS patients. FAR combined with CSVD total load score had a significantly higher predictive value than either indicator alone， with an area under the ROC curve of 0.951. The mediating effect analysis showed that CSVD total burden score played a mediating effect between FAR and AIS patient prognosis END （P<0.05）. Conclusion There is a significant association between FAR and the overall burden of CSVD， and combined measurement of FAR and CSVD total burden score can significantly enhance the performance in predicting END， thereby providing an important basis for developing individualized treatment strategies in clinical practice.

ObjectiveTo investigate the epidemiological and clinical characteristics of human bocavirus (HBoV) in hospitalized children with acute lower respiratory tract infection (ALRTI) at a single-center children’s hospital in Shanghai, thereby providing evidence for the diagnosis, treatment, and prevention of HBoV infection. MethodsA retrospective study was conducted on 19 537 hospitalized children with ALRTI at Shanghai Children’s Hospital from January 2021 to December 2023. Multiplex polymerase chain reaction (PCR) combined with capillary electrophoresis was used to detect HBoV and 12 other common respiratory viruses /atypical pathogens. The positive detection rate, demographic characteristics (sex, age), temporal distribution (year, season) of HBoV, as well as the clinical characteristics of severe and non-severe pneumonia were analyzed. ResultsThe overall HBoV-positive rate was 2.57% (503/19 537), with 59.44% (299/503) being single infections and 40.56% (204/503) being co-infections. The positive detection rate was significantly higher in boys than that in girls (2.78% vs 2.33%, χ²=3.88, P=0.049). The highest infection rate was observed in toddlers, followed by infants (χ²=379.57, P<0.001). The positive rate peaked in 2021 and reached its lowest point in 2023 (χ²=45.49, P<0.001), with epidemics mainly prevalent in summer and autumn. The main clinical symptoms were cough (90.06%, 453/503), fever (75.94%, 382/503), and wheezing (39.96%, 201/503). Children with severe pneumonia showed a higher incidence of wheezing compared with the non-severe group (P<0.001), while underlying diseases and co-infections had no significant association with disease severity (P>0.05). ConclusionHBoV was an important pathogen of ALRTI in children, predominantly affecting infants and toddlers, with higher susceptibility in boys and seasonal peaks in autumn and summer. The main clinical manifestations included cough, fever, and wheezing, with wheezing being more prevalent in children with severe pneumonia.

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 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 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 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 Aimed to investigate the impact of comorbid asthma on chronic rhinosinusitis with nasal polyps(CRSwNP)and identify key proteins and signaling pathways.METHODS Proteomic methods were employed to analyze differentially expressed proteins(DEPs)in nasal lavage fluid(NLF)from control,CRSwNP,and CRSwNP with asthma groups.DIA quantitative analysis technology was used to assess the gradient changes of DEPs among the three groups to determine key proteins affected by comorbid asthma in CRSwNP.RESULTS Compared to the control group,1 377 and 1 006 DEPs were identified in the CRSwNP and CRSwNP with asthma groups,respectively.Peroxiredoxin-5(PRDX5),Ran-Binding Protein 1(RanBP1)(upregulated),and Keratin 9(KRT9)(downregulated)were identified as key proteins affecting CRSwNP with asthma.CONCLUSION Comorbid asthma may promote the occurrence and development of nasal polyps through specific key proteins and signaling pathways,providing new molecular insights into the interaction between CRSwNP and asthma.

BACKGROUND:Studies have shown that the vulnerability and elasticity of carotid plaques are related to the presence and degree of neovascularization within the plaque. Ultrasound,as the preferred measure to screen and evaluate vulnerable carotid plaques,is non-invasive,easy to perform,highly reproducible and radiation-free.OBJECTIVE:To investigate the influencing factors of vulnerable carotid plaque in the high-risk stroke population based on clinical baseline characteristics and carotid ultrasound parameters,and to develop a Nomogram prediction model based on independent risk factors.METHODS:A total of 180 patients who were identified to be at high risk of stroke by stroke screening at Fuzhou First People's Hospital from November 2021 to November 2023 were retrospectively selected as the study objects,and the patients were divided into a modeling set (n=126) and a validation set (n=54)at a ratio of 7∶3. According to the results of carotid artery ultrasound,the subjects in the modeling set were divided into a vulnerable plaque group (n=54) and a non-vulnerable plaque group (n=72). Independent risk factors were obtained by multi-factor Logistic regression,and a Nomogram model was constructed. Decision curves were drawn using R language to evaluate the clinical benefit of the model. The predictive efficacy of the model was tested by receiver operating characteristic curve and calibration curve,and the case data of the validation set were analyzed for external validation.RESULTS AND CONCLUSION:Multivariate Logistic regression results showed that age,family history of stroke,maximum carotid plaque thickness,carotid plaque quantity,urine microalbumin,urine microalbumin/creatinine ratio were associated with vulnerable carotid plaques in patients at high risk of stroke (P<0.05). The area under curve of the established Nomogram model was 0.917,and the sensitivity and specificity were 79.6％ and 91.7％,respectively. The results of decision curve showed that the potential clinical benefit of this model was considerable and its usability was high. The calibration curve results showed that the model had good prediction accuracy. The verification set results showed that the external prediction performance of the model was good. To conclude,age,family history of stroke,and maximum carotid plaque thickness in the high-risk population are all factors that influence this prediction model. This Nomogram based on these independent risk factors can provide a powerful reference for the clinical treatment of this high-risk population.