N-nitrosodimethylamine (NDMA) is an environmental and food contaminant, but limited data to concern whether NDMA has adverse effects on the brain. This study first determined the concentration of NDMA in foods from aquaculture markets in Shenzhen, then analyzed the effects on C57BL/6 mice and further evaluated on the urine samples of elderly Chinese residents with normal cognition (NC, n = 144), cognitive decline (CD, n = 116) and mild cognitive impairment (MCI, n = 123). The excessive rate of NDMA in foods was 3.32% (27/813), with a exceeding range of 4.78–131.00 μg/kg. Behavioral tests showed that 60 days treatment of mice with 3 mg/kg NDMA reduced cognitive performance. Cognitive impairment in human was significantly associated with sex, educational levels, length of residence in Shenzhen, household registration, passive smoking, rice, fresh vegetables, bacon products. NDMA was detected in 55.4% (212/383) of urine samples, with a median concentration of 0.23 μg/L (1.20 × 10 –7–157.39 μg/L). The median concentration for NC, CD and MCI were 0.32, 0.27, and 0 μg/L, respectively. The urinary NDMA concentration had a strong negative correlation with cognitive impairment (Kendall’s Tau-b = −0.89, P = 0.024). The median estimated daily intake (EDI) of NDMA was determined to be 6.63 ng/kg-bw/day. Taken together, there appears to be an association between NDMA and human and murine cognition, which provides a new clue to Alzheimer’s disease (AD).

Emotion recognition plays an essential role in interpersonal communication. However, existing recognition systems use only features of a single modality for emotion recognition, ignoring the interaction of information from the different modalities. Therefore, in our study, we propose a global-aware Cross-modal feature Fusion Network (GCF2-Net) for recognizing emotion. We construct a residual cross-modal fusion attention module (ResCMFA) to fuse information from multiple modalities and design a global-aware module to capture global details. More specifically, we first use transfer learning to extract wav2vec 2.0 features and text features fused by the ResCMFA module. Then, cross-modal fusion features are fed into the global-aware module to capture the most essential emotional information globally. Finally, the experiment results have shown that our proposed method has significant advantages than state-of-the-art methods on the IEMOCAP and MELD datasets, respectively.

ObjectiveThis study examined the prevalence of posttraumatic stress disorder (PTSD) symptoms in college students 1 month after the lockdown of Wuhan to identify possible risk factors for PTSD symptoms in a cross-sectional study.MethodsOut of 10,502 who responded, 9,274 students impacted by the COVID-19 pandemic were included in our study. PTSD symptoms was evaluated by the Impact of Event Scale-revised (IES-R). Anxiety/depression symptoms were evaluated by the Kessler Psychological Distress Scale (K10). Personality traits, coping style, and social support were assessed by the Eysenck Personality Questionnaire-Revised Short Scale for Chinese (EPQ-RSC), the Simplified Coping Style Questionnaire (SCSQ), and the Social Support Rating Scale (SSRS). Logistic regression analysis was utilized to further explore risk factors for PTSD symptoms.ResultsMore than 1 month after the COVID-19 outbreak, 13.1% of college students developed PTSD symptoms, indicating that COVID-19 associated stressful experiences were connected with PTSD symptoms. After the COVID-19 outbreak, subjects with symptomatologic PTSD symptoms were more likely to experience strained relationships with their family, to have close contact with COVID-19 patients and to drop out of college. The logistic regression model demonstrated the association factors of PTSD symptoms. Neuroticism, psychoticism and an avoidant coping style were associated with increased risk for PTSD symptoms, while an active coping style was protective against PTSD symptoms during this pandemic.ConclusionThe results showed that PTSD symptoms was prevalent in Chinese college students 1 month after the COVID-19 outbreak. Effective psychological support work should be carried out accordingly.

IntroductionHybrid positron emission tomography/magnetic resonance imaging (PET/MRI) is a novel advanced non-invasive presurgical examination tool for patients with drug-resistant epilepsy (DRE). This study aims to evaluate the utility of PET/MRI in patients with DRE who undergo stereoelectroencephalography-guided radiofrequency thermocoagulation (SEEG-guided RFTC).MethodsThis retrospective study included 27 patients with DRE who underwent hybrid PET/MRI and SEEG-guided RFTC. Surgery outcome was assessed using a modified Engel classification, 2 years after RFTC. Potential areas of the seizure onset zone (SOZ) were identified on PET/MRI and confirmed by SEEG.ResultsFifteen patients (55%) became seizure-free after SEEG-guided RFTC. Engel class II, III, and IV were achieved in six, two, and four patients, respectively at the 2 years follow-up. MRI was negative in 23 patients and structural abnormalities were found in four patients. Hybrid PET/MRI contributed to the identification of new structural or metabolic lesions in 22 patients. Concordant results between PET/MRI and SEEG were found in 19 patients in the identification of SOZ. Among the patients with multifocal onset, seizure-free status was achieved in 50% (6/12).ConclusionSEEG-guided RFTC is an effective and safe treatment for drug-resistant epilepsy. Hybrid PET/MRI serves as a useful tool for detecting the potential SOZs in MRI-negative patients and guide the implantation of SEEG electrodes. Patients with multifocal epilepsy may also benefit from this palliative treatment.

ObjectiveTo investigate whether paravertebral block reduces postoperative delirium (POD)/delayed neurocognitive recovery (DNR) in adults after major surgery with general anesthesia.MethodsFor this systematic review and meta-analysis, we searched online databases PubMed, EMBASE, CENTRAL, and Web of Science till March 19th, 2023 to examine studies which use paravertebral block (PVB) for perioperative neurocognitive disorder. Primary and secondary outcomes were identified for the incidence of perioperative neurocognitive disorder. We did not restrict the follow-up duration of the included studies. Statistical analysis was performed to calculate mean difference (MD), Odd ratios (OR) and CI between RCTs. The quality of the evidence was assessed with the Cochrane risk of bias tool. The registration number of the study in PROSPERO is CRD42023409502. PROSPERO is an international database of prospectively registered systematic reviews. Registration provides transparency in the review process and it helps counter publication bias.ResultsTotal 1,225 patients from 9 RCTs were analyzed. The incidence of POD [Odds Ratio (OR) = 0.48, 95% CI 0.32, 0.72; p = 0.0004; I2 = 0%] and DNR [OR = 0.32, 95% CI 0.13, 0.80; p = 0.01; I2 = 0%] were significantly reduced in PVB group. The analysis showed no significant differences in postoperative MMSE scores [MD = 0.50, 95% CI −2.14, 3.15; p = 0.71; I2 = 98%]. Paravertebral block analgesia reduces pain scores and/or opioid use after surgery. Additionally, blood pressure was significantly lower in the PVB group, intraoperatively [MD = −15.50, 95% CI −20.71, −10.28; p < 0.001; I2 = 12%] and postoperatively [MD = −5.34, 95% CI −10.65, −0.03 p = 0.05; I2 = 36%]. Finally, PVB group had significantly shorter hospital stays [MD = −0.86, 95% CI −1.13, −0.59; p < 0.001; I2 = 0%].ConclusionParavertebral block analgesia may prevent perioperative POD/DNR in patients undergoing major surgery. Further research with large sample sizes is required to confirm its effectiveness.

This paper investigates the containment control of multiple unmanned surface vessels with nonlinear dynamics. To solve the leader-follower synchronization problem in a containment control system, a hierarchical control framework with a topology reconfiguration mechanism is proposed, and the process of containment control is converted into the tracking of a reference signal for each vessel on its respective target heading by means of the light-of-sight (LOS) guidance. In a control system, the neural networks (NNs) are adopted to consider the uncertainty. In the follower layer, a connectivity controller with a topology reconfiguration mechanism is embedded, to change the converging positions of followers so as to avoid collision within the system, and to maintain the system connectivity when the communication equality is poor. The effectiveness of the hierarchical control framework proposed in this paper is valid by simulation.