Mendelian randomization analyses for the causal relationship between early age at first sexual intercourse, early age at first live birth, and postpartum depression in pregnant women.

Introduction: There are insufficient epidemiological studies on the impact of age at first sexual intercourse (AFS) and age at first live birth (AFB) on postpartum depression (PPD) in pregnant women, and the conclusions of these studies are inconsistent. Methods: We performed a Mendelian randomization (MR) study to determine the causal relationship between AFS or AFB and the risk of PPD. The summary data were extracted from genome-wide association study (GWAS) summary datasets. We selected the instrumental variables according to the P value of exposure-related single nucleotide polymorphisms (P<5 ×10-9 for AFS and P<5 ×10-8 for AFB) and estimated the linkage disequilibrium using the clump parameter (10,000 kb, r2 < 0.001). Single nucleotide polymorphisms were considered instrumental variables that were significantly associated with exposure factors without linkage disequilibrium. The F-statistics of the instrumental variables should all be larger than 10. A random-effects model of IVW was constructed as the main method in our study. Results and discussion: MR studies based on GWAS data revealed that both AFS (OR = 0.4, P <0.001) and AFB (OR = 0.38, P <0.001) were negatively correlated with the risk of PPD. Early AFS and early AFB should be studied as possible risk factors for PPD in the future. Public health departments should attach importance to sex education for young girls. The results of our TSMR should be verified by high-quality prospective epidemiological studies in the future.

Deep Learning Approaches for Imaging-Based Automated Segmentation of Tuberous Sclerosis Complex.

The present study presents a novel approach for identifying epileptogenic tubers in patients with tuberous sclerosis complex (TSC) and automating tuber segmentation using a three-dimensional convolutional neural network (3D CNN). The study retrospectively included 31 TSC patients whose lesions were manually annotated from multiparametric neuroimaging data. Epileptogenic tubers were determined via presurgical evaluation and stereoelectroencephalography recording. Neuroimaging metrics were extracted and compared between epileptogenic and non-epileptogenic tubers. Additionally, five datasets with different preprocessing strategies were used to construct and train 3D CNNs for automated tuber segmentation. The normalized positron emission tomography (PET) metabolic value was significantly lower in epileptogenic tubers defined via presurgical evaluation (p = 0.001). The CNNs showed high performance for localizing tubers, with an accuracy between 0.992 and 0.994 across the five datasets. The automated segmentations were highly correlated with clinician-based features. The neuroimaging characteristics for epileptogenic tubers were demonstrated, increasing surgical confidence in clinical practice. The validated deep learning detection algorithm yielded a high performance in determining tubers with an excellent agreement with reference clinician-based segmentation. Collectively, when coupled with our investigation of minimal input requirements, the approach outlined in this study represents a clinically invaluable tool for the management of TSC.

Localizing seizure onset zone by a cortico-cortical evoked potentials-based machine learning approach in focal epilepsy.

OBJECTIVE: We aimed to develop a new approach for identifying the localization of the seizure onset zone (SOZ) based on corticocortical evoked potentials (CCEPs) and to compare the connectivity patterns in patients with different clinical phenotypes. METHODS: Fifty patients who underwent stereoelectroencephalography and CCEP procedures were included. Logistic regression was used in the model, and six CCEP metrics were input as features: root mean square of the first peak (N1RMS) and second peak (N2RMS), peak latency, onset latency, width duration, and area. RESULTS: The area under the curve (AUC) for localizing the SOZ ranged from 0.88 to 0.93. The N1RMS values in the hippocampus sclerosis (HS) group were greater than that of the focal cortical dysplasia (FCD) IIa group (p < 0.001), independent of the distance between the recorded and stimulated sites. The sensitivity of localization was higher in the seizure-free group than in the non-seizure-free group (p = 0.036). CONCLUSIONS: This new method can be used to predict the SOZ localization in various focal epilepsy phenotypes. SIGNIFICANCE: This study proposed a machine-learning approach for localizing the SOZ. Moreover, we examined how clinical phenotypes impact large-scale abnormality of the epileptogenic networks.

Value of C-reactive protein/albumin ratio in predicting the development of preoperative oxygenation impairment in patients with Stanford type-B acute aortic dissection.

Objectives: We aimed to assess the predicting value of C-reactive protein (CRP)/albumin ratio (CAR) in the development of Oxygenation impairment (OI) in the patients with Stanford type-B acute aortic dissection (AAD). Methods: This study included 133 patients (age = 58.8 ± 12.0 years, median age = 61 years, Male/Female = 117/16) diagnosed as Stanford type-B AAD accompanied by hypertension from July 2012 to May 2020. Clinical data were retrospectively extracted from the database. The patients in this study were divided into OI group (oxygenation index ≤ 200) and non-OI group (oxygenation index > 200). Clinical characteristics in both groups were compared, and predicting value of CAR in the development of OI was assessed. Results: Patients in OI group had higher peak body temperature (37.94 ± 0.62 vs. 37.67 ± 0.51 ℃, P =.010), higher levels of serum CRP (41.74 ± 27.71 vs 15.21 ± 19.66 mg/L, P =.000) and plasma B-type natriuretic peptide (292.14 ± 251.11 vs 179.80 ± 241.27 ng/L, P =.016), lower levels of albumin (34.00 ± 5.14 vs 37.72 ± 5.24 g/L, P =.000), and higher CAR (1.27 ± 0.89 vs 0.41 ± 0.53, P =.000). In multivariate regression analysis, CAR (odds ratio: 5.215, 95 % CI: 2.682; 10.137, P =.000) and the peak body temperature (odds ratio: 2.905, 95 % CI: 1.255; 6.724, P =.013) could significantly predict the OI development. The AUC for CAR was 0.831 (95 % CI: 0.756-0.907). An optimal cutoff value for CAR for predicting OI was ≥ 0.70, with a sensitivity of 67.5 % and a specificity of 88.2 %. Conclusions: Compared with CRP or albumin alone, the CAR might be a more accurate marker in predicting OI development in Stanford type-B AAD.

Transcriptome sequencing of circular RNA reveals the involvement of hsa-SCMH1_0001 in the pathogenesis of Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disease. Exosomes are endosome-derived extracellular vesicles that can take part in intercellular communication. Circular RNAs (circRNAs) are noncoding RNAs characterized by covalently closed-loop structures, which perform a crucial function in many diseases. AIM: To clarify the expression and function of exosomal circRNSs of PD patients and look for circRNAs that might be related to the pathogenesis of PD. MATERIALS AND METHODS: We examined circRNA and mRNA expression profiles in peripheral exosomes from PD patients (n = 23) and healthy controls (n = 15) using next-generation sequencing (NGS) technology, functional annotation, and quantitative polymerase chain reaction. Correlation analysis was performed between the expression levels of the circRNAs and the clinical characteristics of PD patients. The binding miRNAs and target genes were predicted using TargetScanHuman, miRDB, and miRTarBase. The predicted target genes were compared with the differentially expressed mRNAs in sequencing results. RESULTS: According to the NGS, 62 upregulated and 37 downregulated circRNAs in the PD group were screened out. Correlation analysis revealed that hsa-SCMH1_0001 has strong clinical relevance. We identified 17 potential binding miRNAs of hsa-SCMH1_0001 with 149 potential target genes. ARID1A and C1orf115 belong to the intersection of the predicted target genes and the differentially expressed mRNAs obtained by sequencing. CONCLUSION: This study suggested that hsa-SCMH1_0001 and its target genes ARID1A and C1orf115 are downregulated in PD patients and may be involved in the occurrence of PD.

Differences in subthalamic oscillatory activity in the two hemispheres associated with severity of Parkinson's disease.

Background: It is well known that motor features of Parkinson's disease (PD) commonly begin on one side of the body and extend to the other side with disease progression. The onset side generally remains more severely affected over the course of the disease. However, the pathophysiology underlying the asymmetry of motor manifestations remains unclear. The purpose of the present study is to examine whether alterations in neuronal activity in the subthalamic nucleus (STN) associate with PD severity. Methods: Microelectrode recording was performed in the STN during targeting for 30 patients in the treatment of deep brain stimulation. The mean spontaneous firing rate (MSFR), power density spectral analysis, and correlations were calculated. Characteristics of subthalamic oscillatory activity were compared between two hemispheres. UPDRS III scores during "Off" and "On" states were obtained for the body side of initial symptoms (BSIS) and the body side of extended symptoms (BSES). Results: There were significant differences of MSFR (41.3 ± 11.0 Hz vs 35.2 ± 10.0 Hz) and percentage of ß frequency oscillatory neurons (51.3% vs 34.9%) between BSIS and BSES. The percentage of ß frequency oscillatory neurons correlated with the bradykinesia/rigidity scores for both sides (p < 0.05). In contrast, the percentage of tremor frequency oscillatory neurons was significantly higher in the BSES than that in the BSIS. In particular, these neurons only correlated with the tremor scores of the BSES (p < 0.05). Conclusion: The results suggest that increased neuronal firing rate and ß frequency oscillatory neurons in the STN are associated with contralateral side motor severity and its progression. Tremor frequency oscillatory neurons are less observed in the STN of the BSIS suggesting that ß oscillatory activity dominates and tremor frequency oscillatory activity reciprocally declines.

Virtual screening and biological activity evaluation of novel efflux pump inhibitors targeting AdeB.

The AdeABC efflux pump is an important mechanism causing multidrug resistance in Acinetobacter baumannii, and its main component AdeB can recognize carbapenems, aminoglycosides, and other multi-class antibiotics and efflux them intracellularly, which is an ideal target for the development of anti-multidrug resistant bacteria drugs. Here, we combined multiple computer-aided drug design methods to target AdeB to identify promising novel structural inhibitors. Virtual screening was performed by molecular docking and molecular dynamics simulation (MD) and 12 potential compounds were identified from the databases. Meanwhile, their biological activities were validated by in vitro activity assays, and ChemDiv L676-2179 (γ-IFN), ChemDiv L676-1461, and Chembridge 53717615 were confirmed to suppress efflux effects and restore antibiotic susceptibility of resistant bacteria, which are expected to be developed as adjuvant drugs for the treatment of multi-drug resistant Acinetobacter baumannii clinical infections.

Associated factors with stimulation induced seizures and the relevance with surgical outcomes.

OBJECTIVE: To analyze the associated factors with stimulation-induced seizures (SIS) and the relevant factors in predicting surgical outcomes. METHODS: We analyzed 80 consecutive epilepsy patients explored by stereo-electroencephalography with routine electrical stimulation mapping (ESM). If seizures induced by ESM, patients were classified as SIS-positive (SIS-P); otherwise, SIS-negative (SIS-N). Patients received radical surgery were further classified as favorable (Engel I) and unfavorable (Engel II-IV) groups. RESULTS: Of the 80 patients included, we identified 44 (55.0%) and 36(45.0%) patients in the SIS-P and SIS-N groups, respectively. Multivariate analysis revealed that the seizure onset pattern (SOP) of preceding repetitive epileptiform discharges following LVFA (PRED→LVFA) (OR 3.319, 95% CI 1.200-9.183, P = 0.021) and pathology of focal cortical dysplasia (FCD) type II (OR 3.943, 95% CI 1.093-14.226, P = 0.036) were independent factors influencing whether the electrical stimulation can induce a seizure. Among the patients received radical surgery, there were 55 and 15 patients in the favorable and unfavorable groups separately. Multivariate analysis revealed that the SOP of PRED→LVFA induced seizures by stimulation (OR 11.409, 95% CI 1.182-110.161, P = 0.035) and bilateral implantation (OR 0.048, 95% CI 0.005-0.497, P = 0.011) were independent factors affecting surgical outcomes. The previous epilepsy surgery had a trend to be a negative factor with SIS (OR 0.156, 95% CI 0.028-0.880, P = 0.035) and surgical outcomes (OR 0.253, 95% CI 0.053-1.219, P = 0.087). CONCLUSION: ESM is a highly valuable method for localizing the seizure onset zone. The SOP of PRED→LVFA and FCD type II were associated with elicitation of SIS by ESM, whereas a previous epilepsy surgery showed a negative association. Furthermore, the SOP of PRED→LVFA together with SIS in the same patient predicted favorable surgical outcomes, whereas bilateral electrode implantation predicted unfavorable outcomes.

Astrocyte-derived SerpinA3N promotes neuroinflammation and epileptic seizures by activating the NF-κB signaling pathway in mice with temporal lobe epilepsy.

Impaired activation and regulation of the extinction of inflammatory cells and molecules in injured neuronal tissues are key factors in the development of epilepsy. SerpinA3N is mainly associated with the acute phase response and inflammatory response. In our current study, transcriptomics analysis, proteomics analysis, and Western blotting showed that the expression level of Serpin clade A member 3N (SerpinA3N) is significantly increased in the hippocampus of mice with kainic acid (KA)-induced temporal lobe epilepsy, and this molecule is mainly expressed in astrocytes. Notably, in vivo studies using gain- and loss-of-function approaches revealed that SerpinA3N in astrocytes promoted the release of proinflammatory factors and aggravated seizures. Mechanistically, RNA sequencing and Western blotting showed that SerpinA3N promoted KA-induced neuroinflammation by activating the NF-κB signaling pathway. In addition, co-immunoprecipitation revealed that SerpinA3N interacts with ryanodine receptor type 2 (RYR2) and promotes RYR2 phosphorylation. Overall, our study reveals a novel SerpinA3N-mediated mechanism in seizure-induced neuroinflammation and provides a new target for developing neuroinflammation-based strategies to reduce seizure-induced brain injury.

The altered spontaneous neural activity in patients with Parkinson's disease and its predictive value for the motor improvement of deep brain stimulation.

BACKGROUND: This study aims to investigate the altered spontaneous neural activity in patients with Parkinson's disease (PD) revealed by amplitudes of low-frequency fluctuations (ALFF) of resting-state fMRI, and the feasibility of using ALFF as neuroimaging predictors for motor improvement after bilateral subthalamic nucleus (STN) deep brain stimulation (DBS). METHODS: Fourty-four patients and 44 healthy controls were included in this study. First, the ALFF of patients with PD was compared with that of controls; then significant clusters were correlated with motor improvement after DBS (unified Parkinson's disease rating scale (UPDRS-III)) and other clinical variables. Second, regression and classification of the machine learning models were conducted to predict motor improvement after DBS. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the classification model. RESULTS: Compared with healthy controls, patients with PD showed increased ALFF in the bilateral motor area and decreased ALFF in the bilateral temporal cortex and cerebellum. The Hoehn-Yahr stages correlated with ALFF within the bilateral cerebellum (p = 0.021), and UPDRS-III improvement correlated with ALFF in the left (p < 0.001) and right (p = 0.005) motor areas. The regression model showed a significant correlation between the predicted and observed UPDRS-III changes (R = 0.65, p < 0.001). The ROC analysis revealed an area under the curve (AUC) of 0.94 which differentiated moderate and superior DBS responders. CONCLUSION: The results revealed altered ALFF patterns in patients with PD and their correlations with clinical variables. Both binary and continuous ALFF can potentially serve as predictive biomarkers for DBS response.

3D-QSAR, molecular docking, and molecular dynamics analysis of dihydrodiazaindolone derivatives as PARP-1 inhibitors.

CONTEXT: PARP-1 plays an important role in DNA repair and apoptosis, and PARP-1 inhibitors have shown to be effective in the treatment of several malignancies. To evaluate the function of new PARP-1 inhibitors as anticancer adjuvant medicines, 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations of a sequence of dihydrodiazepinoindolone derivatives PARP-1 inhibitors were undertaken in this study. METHODS: In this paper, 43 PARP-1 inhibitors were studied in a three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). CoMFA with q2 of 0.675 and r2 of 0.981 was achieved, as was CoMSIA with q2 of 0.755 and r2 of 0.992. The changed areas of these compounds are shown by steric, electrostatic, hydrophobic, and hydrogen-bonded acceptor field contour maps. Subsequently, molecular docking, and molecular dynamics simulations further confirmed that key residues Gly863 and Ser904 of PARP-1 are vital residues for protein interactions and their binding affinity. The effects of 3D-QSAR, molecular docking and molecular dynamics simulations supply a new route for the search of new PARP-1 inhibitors. Finally, we designed eight new compounds with exact activity and ADME/T properties.

Disturbance of functional brain networks and cognitive decline in Parkinson's disease: Severe cerebral small vessel disease aggravates this relationship.

INTRODUCTION: Several studies have identified a relationship between functional brain network disturbance and cognitive decline in people with Parkinson's disease (PwP); however, few studies have explored whether cerebral small vessel disease (CSVD) burden modifies this relationship. This study aimed to investigate the potential moderating effect of CSVD on the relationship between functional brain network disturbance and cognitive decline in PwP. METHODS: We prospectively recruited 61 PwP from Beijing Tiantan Hospital between October 2021 to September 2022. The Montreal Cognitive Assessment (MoCA) score was used to assess cognition. CSVD imaging markers were evaluated following the STandards for ReportIng Vascular changes on nEuroimaging instructions, and the CSVD burden score was calculated. The functional connectivity indicator was obtained and calculated using quantitative electroencephalography examination. The moderating effect of CSVD burden on the relationship between functional brain network disturbance and cognitive decline was examined using hierarchical linear regression. RESULTS: Forty-six of 61 (75.4%) PwP had cognitive impairment. Higher global weighted phase lag index (wPLI) values in beta1 bands were significantly associated with lower adjusted MoCA scores. CSVD burden aggravated the effect of the global wPLI in beta1 bands on adjusted MoCA scores. This effect was reinforced by the high level of CSVD burden. CONCLUSIONS: Higher wPLI indicates a possible pathological activation of functional brain networks that are associated with cognitive decline in PwP, and the high level of CSVD burden aggravates this relationship.

Efficient volume-based localization and automatic labeling of intracranial depth electrodes.

Background: The accurate localization and anatomical labeling of intracranial depth electrodes are crucial for stereoelectroencephalography (SEEG) recordings and the interpretation of results in patients with epilepsy. The laborious electrode localization procedure requires an efficient and easy-to-use pipeline. Thus, we developed a useful tool, which we called the depth electrode localizer (DELLO), to automatically identify and label depth electrode contacts with ease. Methods: The DELLO is an open-source package developed in MATLAB (MathWorks). It was specifically fine-tuned to expedite the localization of depth electrodes. The basic procedures include preoperative magnetic resonance imaging (MRI) and postoperative computed tomography coregistration, intensity threshold electrode spatial sampling, the hierarchical clustering of electrode samples, and gray-matter and automatic anatomical labeling (AAL). The DELLO also has a graphical user interface (GUI) that can be used to review the results. The only manual intervention procedures are the identification of the target (tip) and entry point of each electrode and the naming of the clustered electrode contact groups, which generally take ~5 min per case. The coordinates of each contact were recorded in individual spaces and were also transformed in standard space by applying a volume-based deformation field. To validate the performance of the current method, 7 patients with epilepsy were retrospectively included in the analysis. Results: A total of 80 depth electrodes, including 1,030 contacts from the 7 patients with epilepsy, were localized. All the procedures functioned well, and the entire process was robust and intuitive. Among the 1,030 contacts, 746 (72.43%) were labeled as inside the gray matter. The gray-matter and AAL accuracy rates were 95.83% and 90.78%, respectively, over all contacts. Conclusions: The DELLO is an integrated tool that was designed to semi-automatically localize and label intracranial depth electrodes. It is open source and freely available. Given its high accuracy and efficiency, the DELLO could facilitate SEEG interpretation and be used in SEEG-based cognitive neuroscience studies.

Treatment of type 2 diabetes mellitus using the traditional Chinese medicine Jinlida as an add-on medication: A systematic review and meta-analysis of randomized controlled trials.

Background: Numerous randomized controlled trials (RCTs) conducted in China have shown that jinlida granules are a promising traditional Chinese medicine (TCM) for the treatment of persons with type 2 diabetes mellitus (T2DM). Controversial results have been reported in different RCTs. The aim of our study was to evaluate the adjuvant hypoglycemic effect of jinlida granules on persons with T2DM and to explore the source of heterogeneity between these RCTs. Materials and methods: Medical article databases were individually searched by two authors for RCTs that provided data regarding the effect of jinlida granules in the treatment of T2DM before 1 June 2022. The methodological quality of the included RCTs was comprehensively assessed by two authors. Data from RCTs with low risk of bias were pooled using Stata SE 12.0 (random-effects model). Evidence derived from the meta-analysis will be assessed according to the GRADE system. Results: Twenty-two RCTs were eventually included in the systematic review and three RCTs with low risk of bias were analyzed in the meta-analysis. Compared with the control groups, significant changes were found in lowering glycosylated hemoglobin a1c (mean difference -0.283 with 95% CI -0.561, -0.004; P=0.046), and were not found in lowering 2-hour postprandial glucose (mean difference -0.314 with 95% CI -1.599, 0.972; P=0.632) and fasting blood glucose (mean difference -0.152 with 95% CI -0.778, -0.474; P=0.634) in the jinlida groups. The GRADE-assessed evidence quality for the outcomes was moderate. Conclusion: The adjuvant hypoglycemic effect of jinlida granules on adult Chinese persons with T2DM was statistically found in lowering HbA1c and was not statistically found in lowering FPG and 2h-PG. Evidence grading should be considered moderate, and the results should be interpreted cautiously. Whether the efficacy of HbA1c-lowering related to clinical significance remains to be investigated in future RCTs. Differences in HbA1c, FPG and 2h-PG at baseline and high risk of bias were important source of heterogeneity between these RCTs. In order to objectively evaluate the efficacy of jinlida granules on T2DM, it is urgently needed that high-quality RCTs evaluating the hypoglycemic effect of jinlida granules in the treatment of qi-yin deficiency pattern T2DM. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42018085135.

Ruthenium red attenuates acute pancreatitis by inhibiting MCU and improving mitochondrial function.

Acute pancreatitis (AP) is a common inflammatory disease of the digestive system. Mitochondrial calcium uniporter (MCU) mediates mitochondrial uptake of Ca2+ and plays an important role in calcium homeostasis. However, it is undefined whether AP can be relieved by inhibiting MCU. This study aimed to study the therapeutic potential of Ruthenium red (RuR), a MCU inhibitor, in AP mice model and primary acinar cells. Cell injury and AP mice model was induced by caerulein. RuR alleviated CER-AP evidenced by reduced serum lipase, TNF-α, and pancreatic MPO levels, less severe pancreatic pathology damage, and decreased inflammatory cell infiltration. In freshly isolated pancreatic acinar cells, RuR diminished cell necrosis with effect on suppressing the expression of MCU. RuR also decreased levels of cytosolic calcium and ROS, preventing mitochondrial membrane potential loss, ATP depletion and MPTP opening. The present findings indicate that inhibit MCU by RuR has a beneficial effect in AP by preventing calcium overload, mitochondrial dysfunction, and cell necrosis.

Combining virtual screening and in vitro evaluation for the discovery of potential CYP11B2 inhibitors.

Aim: To search for highly bioactive hits for CYP11B2 inhibitors by virtual screening and in vitro evaluation. Materials & methods: Virtual screening of potential CYP11B2 inhibitors was performed by molecular docking and molecular dynamics simulation. Compound activity was determined by in vitro evaluation using MTT and ELISA assays. Results & conclusion: Based on the results of molecular docking and molecular dynamics simulation, nine lead hits were selected for in vitro biochemical testing. All hits in in vitro experiments had lower inhibitory effects on cell proliferation and certain inhibitory effects on aldosterone secretion. These hits may be excellent candidates for CYP11B2 inhibitors.

Preoperative acute lung injury and oxygenation impairment occurred in the patients with acute aortic dissection.

Acute lung injury (ALI) and oxygenation impairment (OI) frequently occur in the patients with acute aortic dissection (AAD), which may necessitate mechanical ventilation and result in adverse outcomes. This paper aims to increase clinicians' awareness of the severe respiratory complications in the patients with AAD, and provide the overview of the epidemiology, adverse outcomes, pathogenesis, predictive markers and therapeutic modalities of the concurrent conditions. Currently, it is considered that inflammatory response plays a great role in the pathogenesis of ALI and OI in the patients with AAD, but the definite pathogenesis remains unclear. Given the great importance of the prediction of the occurrence of the severe respiratory complication at a very early stage, some inflammatory biomarkers have been investigated to predict the occurrence of ALI and OI in several studies. C-reactive protein was found to have a significant predictive effect for the development of ALI and OI. Early use of beta-blockers and the use of bindarit could prevent the occurrence of OI and ALI. Ulinastatin could also improve oxygenation in the patients with type-A AAD. Prevention and management of ALI and OI in AAD remain a great challenge. The definite pathogenesis should be clearly clarified and further studies should be performed to look for potential effective way to predict and manage the severe respiratory conditions.

Clinical features of automatisms and correlation with the seizure onset zones: A cluster analysis of 74 surgically-treated cases.

OBJECTIVES: To identify semiologic features of automatisms correlating to different seizure onset zones (SOZ). METHODS: In total, 204 seizures from 74 patients with either oral or manual automatisms were assessed. Patients were divided into four groups depending on the SOZ into frontal, posterior, neocortical temporal, and mesial temporal cortex groups. A k-means analysis was applied on 11 semiologic features on a multi-criteria scale. Then, the resulting clinical patterns were correlated with the SOZs determined by presurgical anatomy-electroclinical data (25 cases with stereo-EEG). RESULTS: Four clinical patterns of automatisms with different accompanying symptoms were identified. The clinical features of clusters 1 and 4 were mostly found in temporal epilepsy whereas clusters 2 and 3 were more frequent in extratemporal epilepsy. Cluster 1 was significantly correlated with mesial temporal lobe epilepsy (p = .017) and was characterised by aura, postictal confusion, short automatisms delay. Cluster 3 included 1/3 patients with frontal lobe epilepsy and was characterised by emotionality. Cluster 4 was related to neocortical temporal lobe epilepsy and characterised by dystonia and short automatism delay (p = .011). CONCLUSION: The distinct semiologic patterns of automatisms may provide information which may allow clinicians to define the SOZs. These findings could improve diagnostic accuracy and surgical outcome.

Effect of Vitamin D Supplementation on the Prognosis of Post-stroke Fatigue: A Retrospective Cohort Study.

Objective: We aimed to evaluate the effect of vitamin D supplementation in post-stroke fatigue (PSF) patients with vitamin D deficiency on fatigue symptoms and outcomes. Methods: Patients with primary acute ischemic stroke (AIS) were recruited consecutively from July 2016 to June 2018. Post-stroke fatigue patients were screened out with the Fatigue Severity Scale (FSS) questionnaire, serum concentrations of 25-hydroxyvitamin D [25-(OH)-D] were assessed with enzyme-linked immunosorbent assay (ELISA), and neurological function was evaluated with FSS and modified Rankin Scale (mRS) scoring criteria. Post-stroke fatigue patients with vitamin D deficiency were divided into two groups: a study group in which patients received vitamin D supplementation (cholecalciferol, 600 IU/day) along with usual care, and a control group in which patients received usual care alone. At the end of 1 and 3 months after treatment, all PSE patients accepted re-measurement of serum vitamin D and re-evaluation of fatigue and neurological function. Results: A total of 532 AIS patients were consecutively recruited to participate in this study. Patients without PSF, non-vitamin D deficiency, pre-stroke fatigue, or vitamin D supplementation were excluded from the study. In addition, patients who were lost to follow-up were also excluded. Finally, 139 out of 532 (26.1%) patients with PSF and vitamin D deficiency received vitamin D supplementation treatment. Fatigue Severity Scale score was significantly lower in the study group than in the control group at 1 month (t = -4.731, p < 0.01) and 3 months (t = -7.937, p < 0.01) after treatment. One month after treatment, mRS score in the study group was lower than that in the control group without statistical difference (t = -0.660, p > 0.05), whereas mRS was significantly higher in the study group than in the control group at 3 months after treatment (t = -4.715, p < 0.01). Conclusions: Our results indicated that vitamin D supplementation could improve fatigue symptoms and neurological outcomes in PSF patients with vitamin D deficiency. Subject to replication in other settings, a randomized controlled trial (RCT) might be undertaken to validate the potential beneficial impact of vitamin D supplementation in post-stroke patients found to be vitamin D deficient.

The amplitude of low-frequency fluctuation predicts levodopa treatment response in patients with Parkinson's disease.

INTRODUCTION: Levodopa has become the main therapy for motor symptoms of Parkinson's disease (PD). This study aimed to test whether the amplitude of low-frequency fluctuation (ALFF) computed by fMRI could predict individual patient's response to levodopa treatment. METHODS: We included 40 patients. Treatment efficacy was defined based on motor symptoms improvement from the state of medication off to medication on, as assessed by the Unified Parkinson's Disease Rating Scale score III. Two machine learning models were constructed to test the prediction ability of ALFF. First, the ensemble method was implemented to predict individual treatment responses. Second, the categorical boosting (CatBoost) classification was used to predict individual levodopa responses in patients classified as moderate and superior responders, according to the 50% threshold of improvement. The age, disease duration and treatment dose were controlled as covariates. RESULTS: No significant difference in clinical data were observed between moderate and superior responders. Using the ensemble method, the regression model showed a significant correlation between the predicted and the observed motor symptoms improvement (r = 0.61, p < 0.01, mean absolute error = 0.11 ± 0.02), measured as a continuous variable. The use of the Catboost algorithm revealed that ALFF was able to differentiate between moderate and superior responders (area under the curve = 0.90). The mainly contributed regions for both models included the bilateral primary motor cortex, the occipital cortex, the cerebellum, and the basal ganglia. CONCLUSION: Both continuous and binary ALFF values have the potential to serve as promising predictive markers of dopaminergic therapy response in patients with PD.