Explore the vast range of titles available.

Rumination is a repetitive self-referential thinking style that is often interpreted as an expression of abnormalities of the default mode network (DMN) observed during “resting-state” in major depressive disorder (MDD). Recent evidence has demonstrated that the DMN is not unitary but can be further divided into 3 functionally heterogenous subsystems, although the subsystem mechanistically underlying rumination remains unclear. Due to the unconstrained and indirect correlational nature of previous resting-state fMRI studies on rumination's network underpinnings, a paradigm allowing direct investigation of network interactions during active rumination is needed. Here, with a modified continuous state-like paradigm, we induced healthy participants to ruminate or imagine objective scenarios (distraction, as a control condition) on 3 different MRI scanners. We compared functional connectivities (FC) of the DMN and its 3 subsystems between rumination and distraction states. Results yielded a highly reproducible and dissociated pattern. During rumination, within-DMN FC was generally decreased as compared to the distraction state. At the subsystem level, we found increased FC between the core and medial temporal lobe (MTL) subsystem as well as decreased FC between the core and dorsal medial prefrontal cortex (DMPFC) subsystem and within the MTL subsystem. Finally, subjects’ behavioral measures of rumination and brooding were negatively correlated with FC between the core and DMPFC subsystems. These results suggest active rumination involves enhanced constraint by the core subsystem on the MTL subsystem and decreased coupling between the core and DMPFC subsystem, allowing for more information exchange among those involved DMN components. Furthermore, the reproducibility of our findings provides a rigorous evaluation of their validity and significance.

•Developed think-aloud functional magnetic resonance imaging method.•Combined natural language processing and representational similarity analysis methods.•Resting-state thoughts involve all brain networks. Is the brain at rest during the so-called resting state? Ongoing experiences in the resting state vary in unobserved and uncontrolled ways across time, individuals, and populations. However, the role of self-generated thoughts in resting-state fMRI remains largely unexplored. In this study, we collected real-time self-generated thoughts during “resting-state” fMRI scans via the think-aloud method (i.e., think-aloud fMRI), which required participants to report whatever they were currently thinking. We first investigated brain activation patterns during a think-aloud condition and found that significantly activated brain areas included all brain regions required for speech. We then calculated the relationship between divergence in thought content and brain activation during think-aloud and found that divergence in thought content was associated with many brain regions. Finally, we explored the neural representation of self-generated thoughts by performing representational similarity analysis (RSA) at three neural scales: a voxel-wise whole-brain searchlight level, a region-level whole-brain analysis using the Schaefer 400-parcels, and at the systems level using the Yeo seven-networks. We found that “resting-state” self-generated thoughts were distributed across a wide range of brain regions involving all seven Yeo networks. This study highlights the value of considering ongoing experiences during resting-state fMRI and providing preliminary methodological support for think-aloud fMRI.

•Holistic thinking and analytic thinking are advanced modes of thinking, which neural mechanisms have not been fully explored.•We used the frame-line task and the triad task, with multivariate pattern analysis (MVPA).•We mapped the fundamental neural substrates of holistic thinking and analytic thinking.•We provided a new method to explore the neural representation of cultural constructs. Holistic and analytic thinking are two distinct modes of thinking used to interpret the world with relative preferences varying across cultures. While most research on these thinking styles has focused on behavioral and cognitive aspects, a few studies have utilized functional magnetic resonance imaging (fMRI) to explore the correlations between brain metrics and self-reported scale scores. Other fMRI studies used single holistic and analytic thinking tasks. As a single task may involve processing in spurious low-level regions, we used two different holistic and analytic thinking tasks, namely the frame-line task and the triad task, to seek convergent brain regions to distinguish holistic and analytic thinking using multivariate pattern analysis (MVPA). Results showed that brain regions fundamental to distinguish holistic and analytic thinking include the bilateral frontal lobes, bilateral parietal lobes, bilateral precentral and postcentral gyrus, bilateral supplementary motor areas, bilateral fusiform, bilateral insula, bilateral angular gyrus, left cuneus, and precuneus, left olfactory cortex, cingulate gyrus, right caudate and putamen. Our study maps brain regions that distinguish between holistic and analytic thinking and provides a new approach to explore the neural representation of cultural constructs. We provide initial evidence connecting culture-related brain regions with language function to explain the origins of cultural differences in cognitive styles.

Background The NOD-, LRR- and pyrin domain‑containing 3 (NLRP3) inflammasome is a critical component of the innate immune system. It has been known to play an important role in the carcinogenesis and prognosis of breast cancer patients. While the clinical evidence of the relationship between NLRP3 inflammasome activation and long-term survival is still limited, the possible roles of parenchymal or immune-stromal cells of breast cancer tissues in contributing to such carcinogenesis and progression still need to be clarified. This study is an analysis of patients receiving breast cancer surgery in a previous clinical trial. Methods Immunohistochemistry (IHC) was used to detect the expression levels of NLRP3 inflammasome pathway-related proteins, including NLRP3, caspase-1, apoptosis-associated speck-like protein (ASC), IL-1β, and IL-18, in parenchymal and immune-stromal cells of breast cancer tissues compared to those of adjacent normal tissues, respectively. The relationship between NLRP3 inflammasome expression and clinicopathological characteristics, as well as 5-year survivals were analyzed using the Chi-square test, Kaplan–Meier survival curves, and Cox regression analysis. Results In the parenchymal cells, ASC and IL-18 protein levels were significantly up-regulated in breast cancer tissues compared with adjacent normal tissues ( P <0.05). In the immune-stromal cells, all the five NLRP3 inflammasome pathway-related proteins were significantly elevated in breast cancer tissues compared with adjacent normal tissues ( P < 0.05). Carcinoma cell embolus was found to significantly correlate with high NLRP3 expression in parenchymal cells of the tumor ( x 2 =4.592, P =0.032), while the expression of caspase-1 was negatively correlated with tumor progression. Histological grades were found to have a positive correlation with IL-18 expression in immune-stromal cells of the tumor ( x 2 =14.808, P =0.001). Kaplan–Meier survival analysis revealed that high IL-18 expression in the immune-stromal cells and the positive carcinoma cell embolus were both associated with poor survival ( P < 0.05). The multivariable Cox proportional hazards regression model implied that the high IL-18 expression and positive carcinoma cell embolus were both independent risk factors for unfavorable prognosis. Conclusions The activation of NLRP3 inflammasome pathways in immune-stromal and tumor parenchymal cells in the innate immune system was not isotropic and the main functions are somewhat different in breast cancer patients. Caspase-1 in parenchymal cells of the tumor was negatively correlated with tumor progression, and upregulation of IL-18 in immune-stromal cells of breast cancer tissues is a promising prognostic biomarker and a potential immunotherapy target. Trial registration This clinical trial has been registered at the Chictr.org.cn registry system on 21/08/2018 (ChiCTR1800017910)

IntroductionPostoperative delirium (POD) is a common cognitive disturbance in elderly individuals that is characterised by acute and fluctuating impairments in attention and awareness. Remimazolam tosylate is a novel, ultrashort-acting benzodiazepine, and there is limited evidence of its correlation with the incidence of early POD. The aim of this study is to evaluate the incidence of POD after anaesthesia induction and maintenance with remimazolam tosylate or propofol in elderly patients undergoing major non-cardiac surgery.Methods and analysisThis is a single-centre, randomised controlled trial. 636 elderly patients undergoing major non-cardiac surgery will be enrolled and randomised at a 1:1 ratio to receive total intravenous anaesthesia with either remimazolam tosylate or propofol. The primary outcome is the incidence of POD within 5 days after surgery. Delirium will be assessed twice daily by the 3 min Diagnostic Interview for the Confusion Assessment Method or the Confusion Assessment Method for the intensive care unit (ICU) for ICU patients. Secondary outcomes are the onset and duration of delirium, cognitive function at discharge and within 1-year postoperatively, postoperative analgesia within 5 days, chronic pain at 3 months, quality of recovery and postoperative inflammatory biomarker levels.Ethics and disseminationThe study was approved by the institutional ethics committee of the National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences (approval No. 22/520–3722). Written informed consent will be obtained from each patient before enrolment. The results of this trial will be presented at scientific conferences and in peer-reviewed scientific journals.Trial registration numberChiCTR2300067368.

Rumination is closely linked to the onset and maintenance of major depressive disorder (MDD). Prior neuroimaging studies have identified the association between self‐reported rumination trait and the functional coupling among a network of brain regions using resting‐state functional magnetic resonance imaging (MRI). However, little is known about the underlying neural circuitry mechanism during active rumination in MDD. Degree centrality (DC) is a simple metric to denote network integration, which is critical for higher‐order psychological processes such as rumination. During an MRI scan, individuals with MDD ( N  = 45) and healthy controls (HC, N  = 46) completed a rumination state task. We examined the interaction effect between the group (MDD vs. HC) and condition (rumination vs. distraction) on vertex‐wise DC. We further characterized the identified brain region's functional involvement with Neurosynth and BrainMap. Network‐wise seed‐based functional connectivity (FC) analysis was also conducted for the identified region of interest. Finally, exploratory correlation analysis was conducted between the identified region of interest's network FCs and self‐reported in‐scanner affect levels. We found that a left superior frontal gyrus (SFG) region, generally overlapped with the frontal eye field, showed a significant interaction effect. Further analysis revealed its involvement with executive functions. FCs between this region, the frontoparietal, and the dorsal attention network (DAN) also showed significant interaction effects. Furthermore, its FC to DAN during distraction showed a marginally significant negative association with in‐scanner affect level at the baseline. Our results implicated an essential role of the left SFG in the rumination's underlying neural circuitry mechanism in MDD and provided novel evidence for the conceptualization of rumination in terms of impaired executive control.

Background Cold knife conization is usually performed under general anesthesia without intubation. This type of anesthesia is more critical in terms of the properties of the sedative drugs. Remimazolam is a novel ultrashort-acting benzodiazepine in which the lipid bond can be rapidly hydrolyzed by nonspecific lipases in the plasma. Therefore, remimazolam can be used for general anesthesia without intubation in patients undergoing short procedures. In this study, we compared the safety and efficacy of remimazolam with those of propofol for cold knife conization. Methods This single-center, randomized controlled trial screened 104 patients, and 90 were randomly assigned to receive propofol (P, N  = 45) or remimazolam (R, N  = 45) during cold knife conization. All the patients received a 1 µg/kg fentanyl injection. The patients received 1.5 mg/kg propofol or 0.2 mg/kg remimazolam injection, followed by a rate of 4 ~ 12 mg/kg/h or 1.0 ~ 3.0 mg/kg/h continuous intravenous infusion, respectively, to keep the patient state index (PSi) between 35 and 50. The primary outcome was intraoperative hypoxemia. The secondary outcomes were hemodynamic parameters, respiratory parameters, and other adverse events. Results The incidence of intraoperative hypoxemia in the R group was significantly lower than that in the P group (46.7% vs. 71.1%, p  = 0.018). Compared with patients in the P group, patients in the R group had fewer changes in the respiratory rate, mean arterial pressure and heart rate at some time points during surgery. The incidences of hypotension (15.6% vs. 35.6%, p  = 0.030) and injection pain (42.2% vs. 84.4%, p  < 0.001) were lower in the R group than in the P group; however, patients in the R group required more time to awaken (7.9 ± 4.5 min vs. 4.3 ± 1.7 min, p  < 0.001). Conclusion In conclusion, patients in the R group had a lower incidence of hypoxemia and fewer hemodynamic changes than did patients in the P group. Thus, remimazolam can be safely used for unintubated general anesthesia in patients undergoing cold knife conization. Trial registration The trial registration number is ChiCTR2200065519.

Objective: To explore the role and mechanism of the Kelch sample related protein-1-nuclear factor erythroid-2 related factor 2/antioxidant response element (Keap1-Nrf2/ARE) signaling pathway in protection of dexmedetomidine (DEX) preconditioning against myocardial ischemia/reperfusion injury (MIRI). Methods: A total of 70 male SD rats were randomly divided into seven equal groups (n=10): blank control (S group), ischemia/reperfusion injury (C group), DEX preconditioning (DEX group), tertiary butylhydroquinone (tBHQ) control (tBHQ group), combined tBHQ and DEX preconditioning (tBHQ+DEX group), all-trans retinoic acid (ATRA) control (ATRA group), and combined ATRA and DEX preconditioning (ATRA+DEX group). Serum creatine kinase-MB (CK-MB) and cardiac troponin I (cTnI) concentrations were measured by ELISA kits, and the infarct size (IS) was assessed by Evan’s blue and 2,3,5-triphenyltetrazolium chloride (TTC) staining. Oxidative stress was assessed through Western blotting for expression of Keap1-Nrf2/ARE pathway members and oxidative stress markers. Results: Cardioprotection of DEX, tBHQ, and tBHQ+DEX preconditioning treatments were shown as lower concentrations of serum CK-MB and cTnI and a smaller IS following MIRI in rats compared with those of MIRI rats without pre-treatment. In addition, tBHQ+DEX preconditioning exhibited stronger myocardial protection compared with DEX preconditioning. Mechanistically, the cardioprotection offered by DEX, tBHQ, and tBHQ+DEX preconditioning treatments was mediated via exerting antioxidant stress through activation of the Keap1-Nrf2/ARE signal transduction pathway. Conversely, the protective effects of DEX were diminished by blocking the Keap1-Nrf2/ARE pathway with inhibitor ATRA. Conclusion: DEX preconditioning protects against MIRI by exerting antioxidant stress through activation of the Keap1-Nrf2/ARE signal transduction pathway, while inhibition of the Keap1-Nrf2/ARE signal transduction pathway reverses the protective effect of DEX preconditioning on MIRI.

In order to improve the acoustic performance of honeycomb sandwich structures, a Helmholtz-type honeycomb sandwich acoustic metamaterial (HHSAM) was proposed. The theoretical and finite element models were established by calculating the acoustic impedance of multiple parallel Helmholtz resonators (HR). By comparing the sound absorption of the single and multiple HR, it was found that the simulation results were basically consistent with the theoretical calculations. The sound absorption and insulation performance of the honeycomb panels, the honeycomb perforated panels, and the HHSAM structure were compared through impedance tube experiments. The results showed that, over a wide frequency range, the acoustic performance of the HHSAM structure was superior to that of the other two structures. Under scattered sound field conditions, the reverberation room results showed that the sound absorption of the HHSAM structure was better than that of the honeycomb panel in the frequency range of 100–5000 Hz. The noise reduction coefficient (NRC) of the honeycomb panel was 0.1, indicating almost no sound absorption effect in engineering. The NRC of the HHSAM structure could reach 0.35. In terms of sound insulation, the HHSAM structure was more prominent in the 400–4000 Hz range than the honeycomb panel. In the frequency range of 500–1600 Hz, the transmission loss of the HHSAM was 5 dB higher than that of the honeycomb panel.

Beyond detecting brain lesions or tumors, comparatively little success has been attained in identifying brain disorders such as Alzheimer’s disease (AD), based on magnetic resonance imaging (MRI). Many machine learning algorithms to detect AD have been trained using limited training data, meaning they often generalize poorly when applied to scans from previously unseen scanners/populations. Therefore, we built a practical brain MRI-based AD diagnostic classifier using deep learning/transfer learning on a dataset of unprecedented size and diversity. A retrospective MRI dataset pooled from more than 217 sites/scanners constituted one of the largest brain MRI samples to date (85,721 scans from 50,876 participants) between January 2017 and August 2021. Next, a state-of-the-art deep convolutional neural network, Inception-ResNet-V2, was built as a sex classifier with high generalization capability. The sex classifier achieved 94.9% accuracy and served as a base model in transfer learning for the objective diagnosis of AD. After transfer learning, the model fine-tuned for AD classification achieved 90.9% accuracy in leave-sites-out cross-validation on the Alzheimer’s Disease Neuroimaging Initiative (ADNI, 6,857 samples) dataset and 94.5%/93.6%/91.1% accuracy for direct tests on three unseen independent datasets (AIBL, 669 samples / MIRIAD, 644 samples / OASIS, 1,123 samples). When this AD classifier was tested on brain images from unseen mild cognitive impairment (MCI) patients, MCI patients who converted to AD were 3 times more likely to be predicted as AD than MCI patients who did not convert (65.2% vs. 20.6%). Predicted scores from the AD classifier showed significant correlations with illness severity. In sum, the proposed AD classifier offers a medical-grade marker that has potential to be integrated into AD diagnostic practice.