Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

ObjectiveGliomas in the motor functional area can damage the corticospinal tract (CST), leading to motor dysfunction. Currently, there is a lack of unified methods for evaluating the extent of CST damage, especially in patients with high surgical risk where the minimum distance from the lesion to the CST is less than 10 mm. This study aims to further clarify the classification method and clinical significance of CST morphological changes in these patients. MethodsThis retrospective study analyzed 109 high-risk functional area glioma patients who underwent neurosurgical treatment with preoperative diffusion tensor imaging (DTI) imaging and intraoperative neurostimulation guidance between 2014 and 2024. All patients had a lesion-to-tract distance (LTD) of less than 10 mm between the CST and the lesion. Preoperative DTI evaluation of CST involvement-induced morphological changes were reviewed. Patients were divided into 3 groups: 17 cases (15.6%) with symmetric CST morphology compared to the healthy side (CST symmetry), 48 cases (44.0%) with significant CST morphology changes compared to the healthy side (CST deformation), and 44 cases (40.4%) with CST overlap with the tumor (CST overlap). Then we classified patients according to preoperative assessment of tumor-induced morphological changes, and analyze postoperative motor function for each category. ResultsPostoperative pathology showed a significantly higher proportion of high-grade gliomas (HGG) in the CST overlap group compared to the other two groups (P=0.001). Logistic regression analysis showed that CST overlap was a predictor of HGG (P=0.000). The rate of total tumor resection in the CST deformation group and overlap group was lower than in the CST symmetric group (P=0.008). There was a total of 41 postoperative hemiplegic patients, with 4 cases (23.5%) in the CST symmetric group, 11 cases (22.9%) in the CST deformation group, and 26 cases (59.1%) in the CST overlap group. CST overlap with the tumor predicted postoperative hemiplegia (P=0.016). Two-way ANOVA analysis of the affected/healthy side and CST morphology groups showed significant main effects of CST grouping and healthy-affected side (P=0.017 and P=0.010), with no significant interaction (P=0.31). The fractional anisotropy (FA) value in the CST overlap group and the affected side was lower. A decrease in the FA value on the affected side predicted postoperative hemiplegia (sensitivity 69.2%, specificity 71.9%). ConclusionWe have established a method to predict postoperative hemiplegia in high-risk motor functional area glioma patients based on preoperative CST morphological changes. CST overlap leads to a decrease in CST FA values. This method can be used for precise patient management and aid in accurate preoperative surgical planning.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective To analyze the pathogenic characteristics and drug sensitivity of candidaemia,and construct a short-term mortality risk prediction scoring model.Methods The clinical data of patients with candidaemia admitted to the 909 Hospital of Joint Logistics Support Force from January 2011 to December 2020 were retrospectively analyzed,and the composition of pathogen composition,drug sensitivity test results and incidence of hospitalized patients were analyzed.324 cases of candidaemia were randomly divided into modeling group(190 cases)and validation group(134 cases),and the risk factors were screened by binary logistic regression.According to the odds ratio(OR)score,the 30 day mortality risk prediction scoring model was constructed,and the predictive performance of the model was verified both in modeling and validation groups.Results 356 strains of Candida including 126 strains of C.albicans(35.39%),79 strains of C.tropicalis(22.19%),74 strains of C.parapsilosis(20.79%),48 strains of C.glabrata(13.48%),14 strains of C.guilliermondii(3.93%),8 strains of C.krusei(2.25%),and 7 strains of other Candida(1.97%)were detected in 336 patients with candidemia.The incidence of candidaemia among hospitalized patients increased from 0.20 ‰ in 2011 to 0.48 ‰ in 2020.The resistance rate of candida to amphotericin B was significantly lower than that of fluconazole,voriconazole and itraconazole(P＜0.05).Among the 324 cases included in the model,95 patients died in 30 days after diagnosis,and the mortality rate was 29.32%.The proportion of males,fever,and parenteral nutrition in modeling group was significantly higher than that in validation group(P＜0.05),while the proportion of chronic lung disease and surgical history within one month were lower than those in validation group(P＜0.05).Logistic regression analysis showed that chronic renal failure,mechanical ventilation,severe neutropenia,failure to receive anti-fungal treatment within 72 hours,and APACHE Ⅱ≥20 were risk factors for short-term death of candidaemia,the OR values were 3.179,1.970,2.979,2.080,and 2.399,and the risk scores were 6,4,6,4,and 5,respectively.The area under the curve(AUC)of the risk scoring model for modeling group was 0.792(95%CI 0.721-0.862),and the result of Hosmer-Lemeshow(H-L)test was P=0.305;The AUC of validation group was 0.796(95%CI 0.735-0.898),and the H-L test result was P=0.329.A risk score≤8 indicated a low risk group for short-term mortality,a score of 9-15 indicated a medium risk group,and a score≥16 indicated a high risk group.Conclusions The incidence of candidemia in hospitalized patients is increasing and the mortality is high.The risk prediction score model can effectively predict the short-term prognosis and facilitate the early identification of the prognosis.

Objective:To develop and validate a postoperative infection nomogram of hepatitis B-associated hepatocellular carcinoma (HCC) after hepatectomy.Methods:Clinical data of 229 patients with HCC undergoing hepatectomy at the Department of Hepatobiliary Surgery of Tianjin Third Central Hospital from January 2014 to December 2022 were retrospectively analyzed, including 174 males and 55 females, aged (58.2±11.4) years. LASSO regression analysis screened the factors associated with hepatitis B-associated HCC infection after hepatectomy, which were further incorporated into multivariate logistic regression analysis. A nomographic prediction model was established based on the results of multivariate logistic regression analysis. Concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve were used to evaluate the model, and decision curve analysis (DCA) was used to analyze the clinical applicability of the model. Internal validation of the model was performed using bootstrap method.Results:A total of nine variables were screened as factors associated with the postoperative infections using LASSO regression, including gender, smoking history, body mass index (BMI), serum level of alpha fetoprotein, resection fashion (anatomical or non-anatomical), intraoperative blood loss, surgical method (laparoscopy or open), serum level of creatinine, and postoperative biliary fistula. Multivariate logistic regression analysis showed that BMI, resection fashion, intraoperative blood loss >500 ml, and postoperative biliary fistula were risk factors for postoperative infection (all P<0.05). Based on the above risk factors, a postoperative infection nomogram of hepatitis B-associated HCC after hepatectomy was established. The C-index was 0.839 (95% CI: 0.768-0.910), and the area under ROC curve was 0.853 (95% CI: 0.795-0.912), indicating that the model had a good predictive ability. The calibration curve was basically consistent with the ideal curve. The DCA showed that the model had a good clinical applicability. Internal validation C-index was 0.829 (95% CI: 0.766-0.892). Conclusion:The nomogram based on BMI, surgical resection fashion, intraoperative blood loss >500 ml, and postoperative biliary fistula has a high predictive accuracy and can be used to predict postoperative infections after hepatectomy for HCC.

This study design of specific identification primers for the ITS2 sequence of F. ussuriensis. The reaction system and conditions were optimized, and PCR-nucleic acid test strips were constructed to realize the visual detection of F. ussuriensis Bark. Through molecular cloning and sequencing technology, we constructed a positive control for F. ussuriensis DNA and formulated quality standards. The established method was evaluated for sensitivity, specificity and reproducibility, and the authenticity of the commercially available samples was identified. Results demonstrated that based on the ITS2 sequences, F. ussuriensis and its mixed forgeries could be distinguished. The PCR products of the authentic F. ussuriensis on test strips showed two bands in the T and C lines, while the pseudo products and negative control showed only one band in the C line, which was consistent with the results of agarose gel electrophoresis. The specificity was 100%, and the sensitivity of the PCR-nucleic acid test strip was up to 0.1 ng·μL^-1, which was 10 times higher than that of the gel electrophoresis assay. 11 out of 16 commercially available samples of F. ussuriensis were qualified, and 5 were unqualified. Collectively, the PCR-nucleic acid test strip method established in this study is specific, rapid, accurate and visualized, which can provide a new technical idea for the detection of F. ussuriensis.

Objective:To explore the causal relationship between gut microbiota and lung function (FEV1/FVC) using two-sample Mendelian randomization method; To explore its application in the TCM field.Methods:This was a Mendelian randomization study. The GWAS data of gut microbiota from the MiBioGen consortium study and the GWAS data of lung function (FEV1/FVC) published by IEU OpenGWAS in the public database were used, and instrumental variables were extracted according to prespecified thresholds. The inverse variance weighted method (IVW) was mainly used for analysis. The results were evaluated according to the effect indicator β value and 95% CI. When the IVW method was statistically significant, further sensitivity analysis was performed. Leave-one-out test, heterogeneity test, horizontal gene pleiotropy test and MR-Egger regression intercept analysis were used to verify the stability and reliability of the results. Results:A total of 10 causal relationships between gut microbiota and lung function (FEV1/FVC) were determined using the IVW method: family. BacteroidalesS24.7group ( β=-0.029, P=0.015), family. ClostridialesvadinBB60group ( β=-0.028, P=0.040), family. Streptococcaceae ( β=-0.056, P=0.042), genus. LachnospiraceaeFCS020group ( β=0.025, P=0.029), genus. Lactococcus ( β=-0.024, P=0.038), genus. Peptococcus ( β=0.025, P=0.049), genus. RuminococcaceaeUCG011 ( β=-0.030, P=0.038), genus. Ruminococcus2 ( β=0.028, P=0.033), genus. Terrisporobacter ( β=-0.030, P=0.018), phylum. Cyanobacteria ( β=0.027, P=0.039). Leave-one-out analysis showed that the results were stable, and the effects of heterogeneity and horizontal gene pleiotropy on causal effect estimation could be removed. Conclusion:The gut microbiota may play a role in the changes of lung function, which to a certain extent confirms the TCM theory of "exterior-interior relationship between the lung and large intestine", and can provide certain reference for the research direction of TCM.

Human brain banks use a standardized protocol to collect,process and store post-mortem human brains and related tissues,along with relevant clinical information,and to provide the tissue samples and data as a resource to foster neuroscience research according to a standardized operating protocols(SOP).Human brain bank serves as the foundation for neuroscience research and the diagnosis of neurological disorders,highlighting the crucial rule of ensuring the consistency of standardized quality for brain tissue samples.The first version of SOP in 2017 was published by the China Human Brain Bank Consortium.As members increases from different regions in China,a revised SOP was drafted by experts from the China Human Brain Bank Consortium to meet the growing demands for neuroscience research.The revised SOP places a strong emphasis on ethical standards,incorporates neuropathological evaluation of brain regions,and provides clarity on spinal cord sampling and pathological assessment.Notable enhancements in this updated version of the SOP include reinforced ethical guidelines,inclusion of matching controls in recruitment,and expansion of brain regions to be sampled for neuropathological evaluation.

The advantages of fluorescence detection of uric acid were introduced compared to the traditional detection methods.The preparation process,detection principle and performance of organic,inorganic and organic-inorganic hybrid fluorescent probes were reviewed.The advantages and disadvantages of kinds of fluorescent probes were analyzed when used for uric acid detection,and the futural directions were pointed out for related research.[Chinese Medical Equipment Journal,2024,45(6):93-104]

Objective To investigate the disease spectrum and pathogenic genes of inherited metabolic disorder(IMD)among neonates in Gansu Province of China.Methods A retrospective analysis was conducted on the tandem mass spectrometry data of 286 682 neonates who received IMD screening in Gansu Provincial Maternal and Child Health Hospital from January 2018 to December 2021.A genetic analysis was conducted on the neonates with positive results in tandem mass spectrometry during primary screening and reexamination.Results A total of 23 types of IMD caused by 28 pathogenic genes were found in the 286 682 neonates,and the overall prevalence rate of IMD was 0.63‰(1/1 593),among which phenylketonuria showed the highest prevalence rate of 0.32‰(1/3 083),followed by methylmalonic acidemia(0.11‰,1/8 959)and tetrahydrobiopterin deficiency(0.06‰,1/15 927).In this study,166 variants were identified in the 28 pathogenic genes,with 13 novel variants found in 9 genes.According to American College of Medical Genetics and Genomics guidelines,5 novel variants were classified as pathogenic variants,7 were classified as likely pathogenic variants,and 1 was classified as the variant of uncertain significance.Conclusions This study enriches the database of pathogenic gene variants for IMD and provides basic data for establishing an accurate screening and diagnosis system for IMD in this region.