Serum fatty acid binding protein 4 is positively associated with early stroke recurrence in nondiabetic ischemic stroke

Development of a therapeutic monoclonal antibody against circulating adipocyte fatty acid binding protein to treat ischaemic stroke

BACKGROUND AND PURPOSE

Adipocyte fatty acid-binding protein (A-FABP) exacerbates cerebral ischaemia injury by disrupting the blood-brain barrier (BBB) through inducing expression of MMP-9. Circulating A-FABP levels positively correlate with infarct size in stroke patients. We hypothesized that targeting circulating A-FABP by a neutralizing antibody would alleviate ischaemic stroke outcome.

EXPERIMENTAL APPROACH

Monoclonal antibodies (mAbs) against A-FABP were generated using mouse hybridoma techniques. Binding affinities of a generated mAb named 6H2 towards various FABPs were determined using Biacore. Molecular docking studies were performed to characterize the 6H2-A-FABP complex structure and epitope. The therapeutic potential and safety of 6H2 were evaluated in mice with transient middle cerebral artery occlusion (MCAO) and healthy mice, respectively.

KEY RESULTS

Replenishment of recombinant A-FABP exaggerated the stroke outcome in A-FABP-deficient mice. 6H2 exhibited nanomolar to picomolar affinities to human and mouse A-FABP, respectively, with minimal cross-reactivities with heart and epidermal FABPs. 6H2 effectively neutralized JNK/c-Jun activation elicited by A-FABP and reduced MMP-9 production in macrophages. Molecular docking suggested that 6H2 interacts with the "lid" of the fatty acid binding pocket of A-FABP, thus likely hindering the binding of its substrates. In mice with transient MCAO, 6H2 significantly attenuated BBB disruption, cerebral oedema, infarction, neurological deficits, and decreased mortality associated with reduced cytokine and MMP-9 production. Chronic 6H2 treatment showed no obvious adverse effects in healthy mice.

CONCLUSION AND IMPLICATIONS

These results establish circulating A-FABP as a viable therapeutic target for ischaemic stroke, and provide a highly promising antibody drug candidate with high affinity and specificity.

A machine learning model for visualization and dynamic clinical prediction of stroke recurrence in acute ischemic stroke patients: A real-world retrospective study

Background and purpose

Recurrent stroke accounts for 25–30% of all preventable strokes, and this study was conducted to establish a machine learning-based clinical predictive rice idol for predicting stroke recurrence within 1 year in patients with acute ischemic stroke (AIS).

Methods

A total of 645 AIS patients at The Second Affiliated Hospital of Xuzhou Medical University were screened, included and followed up for 1 year for comprehensive clinical data. Univariate and multivariate logistic regression (LR) were used to screen the risk factors of stroke recurrence. The data set was randomly divided into training set and test set according to the ratio of 7:3, and the following six prediction models were established by machine algorithm: random forest (RF), Naive Bayes model (NBC), decision tree (DT), extreme gradient boosting (XGB), gradient boosting machine (GBM) and LR. The model with the strongest prediction performance was selected by 10-fold cross-validation and receiver operating characteristic (ROC) curves, and the models were investigated for interpretability by SHAP. Finally, the models were constructed to be visualized using a web calculator.

Results

Logistic regression analysis showed that right hemisphere, homocysteine (HCY), C-reactive protein (CRP), and stroke severity (SS) were independent risk factors for the development of stroke recurrence in AIS patients. In 10-fold cross-validation, area under curve (AUC) ranked from 0.777 to 0.959. In ROC curve analysis, AUC ranged from 0.887 to 0.946. RF model has the best ability to predict stroke recurrence, and HCY has the largest contribution to the model. A web-based calculator https://mlmedicine-re-stroke2-re-stroke2-baylee.streamlitapp.com/ has been developed accordingly.

Conclusion

This study identified four independent risk factors affecting recurrence within 1 year in stroke patients, and the constructed RF-based prediction model had good performance.

Thiosulfate-Cyanide Sulfurtransferase a Mitochondrial Essential Enzyme: From Cell Metabolism to the Biotechnological Applications

Thiosulfate: cyanide sulfurtransferase (TST), also named rhodanese, is an enzyme widely distributed in both prokaryotes and eukaryotes, where it plays a relevant role in mitochondrial function. TST enzyme is involved in several biochemical processes such as: cyanide detoxification, the transport of sulfur and selenium in biologically available forms, the restoration of iron–sulfur clusters, redox system maintenance and the mitochondrial import of 5S rRNA. Recently, the relevance of TST in metabolic diseases, such as diabetes, has been highlighted, opening the way for research on important aspects of sulfur metabolism in diabetes. This review underlines the structural and functional characteristics of TST, describing the physiological role and biomedical and biotechnological applications of this essential enzyme.

Effects of insulin combined with metformin on serum cystatin C, homocysteine and maternal and neonatal outcomes in pregnant women with gestational diabetes mellitus

Effects of insulin combined with metformin on serum cystatin C (Cys C), homocysteine (Hcy) and maternal and neonatal outcomes in pregnant women with gestational diabetes mellitus (GDM) were investigated. In total, 80 cases of pregnant women diagnosed with GDM in the Department of Obstetrics and Gynecology of Liaocheng Third People's Hospital from July 2015 to July 2017 were selected and divided into a study group (42 cases) and a control group (38 cases). The study group was treated with insulin combined with metformin, and the control group was treated with insulin. Fasting blood glucose (FBG) and postprandial blood glucose after 2 h (2hPG) of the two groups were compared before and after treatment. Levels of serum Cys C, Hcy, urinary protein (UmAlb), postpartum maternal outcomes and adverse reactions during pregnancy were compared in the two groups before and after treatment. After treatment, the level of FBG and 2hPG in the control group was higher than that in the treatment group (P<0.05). After treatment, the level of serum Cys C and Hcy in both groups were lower than that before the treatment, and the level in the study group was lower than that in the control group (P<0.05). The total incidence of neonatal adverse outcomes and the number of adverse pregnancies in GDM patients in the study group were significantly lower than those in the control group (P<0.05). There were no significant differences in adverse reactions during pregnancy between the two groups (P>0.05). In conclusion, insulin combined with metformin is more effective than insulin alone in reducing serum Cys C and Hcy levels, with significant effect on the improvement of maternal and neonatal outcomes.