Diffusion-/perfusion-weighted imaging fusion to automatically identify stroke within 4.5 h.

OBJECTIVES: We aimed to develop machine learning (ML) models based on diffusion- and perfusion-weighted imaging fusion (DP fusion) for identifying stroke within 4.5 h, to compare them with DWI- and/or PWI-based ML models, and to construct an automatic segmentation-classification model and compare with manual labeling methods. METHODS: ML models were developed from multimodal MRI datasets of acute stroke patients within 24 h of clear symptom onset from two centers. The processes included manual segmentation, registration, DP fusion, feature extraction, and model establishment (logistic regression (LR) and support vector machine (SVM)). A segmentation-classification model (X-Net) was proposed for automatically identifying stroke within 4.5 h. The area under the receiver operating characteristic curve (AUC), sensitivity, Dice coefficients, decision curve analysis, and calibration curves were used to evaluate model performance. RESULTS: A total of 418 patients (≤ 4.5 h: 214; > 4.5 h: 204) were evaluated. The DP fusion model achieved the highest AUC in identifying the onset time in the training (LR: 0.95; SVM: 0.92) and test sets (LR: 0.91; SVM: 0.90). The DP fusion-LR model displayed consistent positive and greater net benefits than other models across a broad range of risk thresholds. The calibration curve demonstrated the good calibration of the DP fusion-LR model (average absolute error: 0.049). The X-Net model obtained the highest Dice coefficients (DWI: 0.81; Tmax: 0.83) and achieved similar performance to manual labeling (AUC: 0.84). CONCLUSIONS: The automatic segmentation-classification models based on DWI and PWI fusion images had high performance in identifying stroke within 4.5 h. CLINICAL RELEVANCE STATEMENT: Perfusion-weighted imaging (PWI) fusion images had high performance in identifying stroke within 4.5 h. The automatic segmentation-classification models based on DWI and PWI fusion images could provide clinicians with decision-making guidance for acute stroke patients with unknown onset time. KEY POINTS: • The diffusion/perfusion-weighted imaging fusion model had the best performance in identifying stroke within 4.5 h. • The X-Net model had the highest Dice and achieved performance close to manual labeling in segmenting lesions of acute stroke. • The automatic segmentation-classification model based on DP fusion images performed well in identifying stroke within 4.5 h.

Migraine among students of a medical college in western China: a cross-sectional study.

OBJECTIVE: As one of the most common primary headaches in clinical practice, migraine affects the learning ability and life quality of college students worldwide, posing a heavy burden on individuals and society. This study aims to investigate the incidence of migraine among Chinese medical college students and to explore its characteristics and typical triggers. METHOD: From July 2019 to July 2020, North Sichuan Medical College in Sichuan province, China preliminarily screened migraine cases using ID-Migraine through cluster sampling. College students with positive ID-Migraine results would be included in this study if they were further diagnosed with migraine by neurologists based on ICHD-3. After the ethical review, patients' personal and headache information would be collected, and the frequency, severity, onset time, and related triggers of migraine would be measured. RESULTS: The preliminary screening covered 8783 college students. The overall prevalence rate of migraine is 6.57%, 5.90% in men and 6.77% in women. The prevalence rate of migraine is higher for students in the first and second grades (8.01%, 8.05%), and students with a family history of migraine are more likely to suffer from migraine (OR = 1.509, 95% CI 1.060-2.148, P = 0.022 < 0.005). Staying up late (n = 329, 57.01%), stress (n = 319, 55.29%), catch a cold (n = 313, 54.25%) and sleep disorders (n = 302, 52.34%) are the common triggers. CONCLUSION: Migraine is common among college students in North Sichuan Medical College. The incidence is higher among lower grade students, female students, and students with a family history of migraine. Improving sleep quality and reducing stress may be effective in relieving migraines.

Prevalence and Factors Associated With Suicidal Ideation in Medical Students With Migraine.

Background: The association between migraine and suicide ideation has been identified. However, the predictive factors of suicidal ideation are still controversial and whether migraine with aura can serve as an independent associated factor is uncertain. This manuscript studied the association between migraine with aura and suicidal ideation and explored the predictive factors for suicidal ideation. Methods: We surveyed 9,057 medical students and included 579 medical students with migraine into our study population. All students completed the General Situation Questionnaire, the Verified Headache Questionnaire, Hamilton Anxiety Scale (24 items), Hamilton Depression Scale (24 items), 36-item Health Survey Brief (SF-36), Headache Impact Text-6 (HIT-6), Test Anxiety Scale (TAS), and Pittsburgh Sleep Quality Index (PSQI). Suicidal ideation was measured by the Self-rating Idea of Suicide Scale (SIOSS). Results: Out of the 579 migraine medical college students, 562 (age 19.6 ± 1.6; 448 women and 114 men) were included in the final study. The positive rate of suicidal ideation was 13.7%. Compared with students suffering from migraine without aura, those having migraine with aura had higher suicidal ideation (p < 0.015). After adjusting for demographic factors and headache characteristics, migraine with aura was found to be independently associated with suicidal ideation. Other independent associated factors include anxiety, depression, test anxiety, sleep, headache, and quality of life. Among these various factors, high quality of life was found to play a protective role against suicidal ideation. Conclusions: Migraine with aura is independently associated with suicidal ideation. Furthermore, anxiety, depression, text anxiety, poor sleep quality, and headache frequency are associated with suicidal ideation among medical college students with migraine.

Altered cerebellum functional network on newly diagnosed drug-naïve Parkinson's disease patients with anxiety.

INTRODUCTION: Damage to the cerebellar functional network may underlie anxiety symptoms in patients with Parkinson's disease (PD). Herein we investigated the regional homogeneity (ReHo) and functional connectivity (FC) patterns of cerebellar and clinical correlates in PD patients with anxiety and explored their clinical significance. METHODS: We enrolled 50 newly diagnosed drug-naïve PD patients and 30 normal controls (NCs). Twenty-six PD patients with anxiety symptoms (PD-A) and 24 PD patients without anxiety symptoms (PD-NA) were sorted into groups based on the Hamilton Anxiety Scale (HAMA). All included participants underwent rest-state functional magnetic resonance imaging (rs-fMRI) scanning. Cerebellar FC based on the seed-based method was used to investigate regional and whole brain function in PD-A, PD-NA, and NCs, and the relationship between the abnormal brain function and anxiety symptoms in PD patients was also detected. RESULTS: Compared with the PD-NA group and the NCs, the ReHo value of the PD-A group was significantly decreased in the left medial frontal gyrus and increased in the left cerebellum. Further, left-cerebellum-based FC patterns were used to detect the decreased FC in the right cerebellum, while FC was increased in the right caudate nucleus, and the right anterior cingulate cortex (ACC) in the PD-A group was compared with that in the PD-NA group. Further, the altered FC between the left cerebellum and the right cerebellum was significantly associated with anxiety symptoms in the PD-A group. CONCLUSION: The present study found abnormal regional cerebellum function as well as disruptions in the connectivity network within the cerebellum, caudate, and ACC in patients with PD-A. In addition, the FC between the left cerebellum and the right cerebellum was associated with anxiety symptoms in patients with PD. The present study indicated that cerebellar functional damage may be associated with anxiety symptoms in PD patients.

Box-copper catalyzed cascade asymmetric amidation for chiral exo-methylene aminoindoline derivatives.

Enantioselective copper-catalyzed cascade inter- and intramolecular amidation was achieved between ethynyl benzoxazinanones and α-halohydroxamates in the presence of an indapybox ligand. The one-pot cascade transformation was triggered by the attack of hydroxamates to dipolar copper-allenylidene intermediates, followed by a nucleophilic annulation reaction. Thus, a series of exo-methylene 3-aminoindoline derivatives were obtained in good yields with high enantioselectivities under mild reaction conditions.

Chiral Bidentate Phosphoramidite-Pd Catalyzed Asymmetric Decarboxylative Dipolar Cycloaddition for Multistereogenic Tetrahydrofurans with Cyclic N-Sulfonyl Ketimine Moieties.

An asymmetric [3 + 2] cycloaddition of vinyl ethylenecarbonates (VECs) and (E)-3-arylvinyl substituted benzo[d] isothiazole 1,1-dioxides has been developed using the Pd complex of a bidentate phosphoramidite (Me-BIPAM) as the catalyst, providing a wide variety of chiral multistereogenic vinyltetrahydrofurans in good yields with excellent diastereo- and enantioselectivities (up to >20:1 dr, 99% ee).

Dabigatran Suppresses PAR-1/SphK/S1P Activation of Astrocytes in Experimental Autoimmune Encephalomyelitis Model.

Multiple sclerosis (MS) is an inflammatory autoimmune disease affecting the central nervous system (CNS) that currently does not have any effective treatment. Experimental autoimmune encephalomyelitis (EAE) is often employed as a model to mimic the clinical manifestations of MS, mainly CNS demyelination. Coagulation is known to participate in crosstalk with inflammation and autoimmunity. We herein explored the correlation between the coagulation cascade and CNS immune diseases in vitro using primary astrocytes isolated from mice and in vivo using a mouse model of EAE. We showed that dabigatran, a clinical oral anti-coagulant drug, suppressed the thrombin-induced activation of astrocytes, and the underlying mechanisms are related to the activity of protease-activated receptor-1 (PAR-1), sphingosine-1-phosphate (S1P), and sphingosine kinases (SphKs). Importantly, dabigatran effectively recovered neurological function, reduced inflammation in the spinal cord, and prevented spinal cord demyelination caused by EAE. We suggest that dabigatran, a specific inhibitor of thrombin, antagonized the effect of thrombin in astrocytes by limiting the activation of PAR-1, in turn downregulating SphK1 and disrupting S1P receptor signaling. These findings reveal critical information about the relationship between coagulation mechanisms and CNS immune diseases and will contribute to the clinical translation and development of therapeutic strategies against MS.