Objective In this retrospective study, we aimed to investigate changes in brain morphology and structural topological networks in patients with lung cancer (LC) with or without chemotherapy. Methods We retrospectively recruited 191 participants for this cross-sectional study, including 113 patients with LC without chemotherapy (Ch-), 38 patients with LC with chemotherapy (Ch+), and 40 healthy controls (HC) matched for age, sex, and education. The gray matter volume (GMV) and cortical properties were compared among the three groups. We constructed the structural covariant network (SCN) based on cortical thickness, volumes of subcortical structures, and volumes of hippocampal subfields and the amygdala in all participants. The global and nodal topological properties of SCN were compared among groups. In addition, 23 patients with LC (8 Ch+ and 15 Ch-) who received two identical brain magnetic resonance scans were enrolled in the follow-up study. The paired t-test was used to compare group differences in brain morphology and topological properties in the structural network. Results The GMV of the bilateral caudate and thalamus were smaller in the Ch- and Ch+ groups compared to the HC group using threshold-free cluster enhancement and permutation (P < 0.05, 5000 times permutations) for multiple comparison correction. The cortical SCN analysis suggested multiple enhanced nodal properties in several brain areas in Ch+ and Ch- compared to HC, mainly in the temporal gyrus, using permutations test and false discovery rate (FDR) (P < 0.05) corrections. Moreover, an increased sigma was found in the Ch+ compared with HC (P = 0.0238). The reduced nodal degree (P = 0.0002) and betweenness (P = 0.0008) in the right amygdala of Ch+ compared to HC were detected by subcortical SCN analysis. Furthermore, reduced gamma (P = 0.0342) and sigma (P < 0.0001) were found in Ch- compared with HC in the SCN analysis of subfields of the amygdala-hippocampal complex. In the follow-up study, reduced nodal degree (P < 0.0001) was found in the right anterior amygdala, and reduced clustering coefficient and local efficiency were found in patients with LC after the permutation test. Conclusions Our study showed GMV defects and structural topological property abnormalities related to LC and chemotherapy. Such morphological changes associated with LC and chemotherapy could be used as imaging markers for clinical assessments and pathological indicators.

Cognitive impairment is a common issue among human patients undergoing surgery, yet the neural mechanism causing this impairment remains unidentified. Surgical procedures often lead to glial cell activation and neuronal hypoexcitability, both of which are known to contribute to postoperative cognitive dysfunction (POCD). However, the role of neuron-glia crosstalk in the pathology of POCD is still unclear. Through integrated transcriptomics and proteomics analyses, we found that the complement cascades and microglial phagocytotic signaling pathways are activated in a mouse model of POCD. Following surgery, there is a significant increase in the presence of complement C3, but not C1q, in conjunction with presynaptic elements. This triggers a reduction in excitatory synapses, a decline in excitatory synaptic transmission, and subsequent memory deficits in the mouse model. By genetically knockout out C3ar1 or inhibiting p-STAT3 signaling, we successfully prevented neuronal hypoexcitability and alleviated cognitive impairment in the mouse model. Therefore, targeting the C3aR and downstream p-STAT3 signaling pathways could serve as potential therapeutic approaches for mitigating POCD.

Perioperative neurocognitive disorders (PND) refer to cognitive deterioration that occurs after surgery or anesthesia. Prolonged isoflurane exposure has potential neurotoxicity and induces PND, but the mechanism is unclear. The glymphatic system clears harmful metabolic waste from the brain. This study sought to unveil the functions of glymphatic system in PND and explore the underlying molecular mechanisms. The PND mice model was established by long term isoflurane anesthesia. The glymphatic function was assessed by multiple in vitro and in vivo methods. An adeno-associated virus was used to overexpress AQP4 and TGN-020 was used to inhibit its function. This research revealed that the glymphatic system was impaired in PND mice and the blunted glymphatic transport was closely associated with the accumulation of inflammatory proteins in the hippocampus. Increasing AQP4 polarization could enhance glymphatic transport and suppresses neuroinflammation, thereby improve cognitive function in the PND model mice. However, a marked impaired glymphatic inflammatory proteins clearance and the more severe cognitive dysfunction were observed when decreasing AQP4 polarization. Therefore, long-term isoflurane anesthesia causes blunted glymphatic system by inducing AQP4 depolarization, enhanced the AQP4 polarization can alleviate the glymphatic system malfunction and reduce the neuroinflammatory response, which may be a potential treatment strategy for PND.

Research on the pathophysiological mechanism of carotid artery dissection and its clinical translation is limited due to the lack of effective animal models to simulate the occurrence of this condition. Assuming that intimal injury is an important factor in the formation of carotid dissection, we established a novel method for inducing carotid dissection models by scraping the carotid intima using a fine needle. Scraping the carotid intima with fine needles can induce the rapid formation of carotid dissection. Magnetic resonance imaging and hematoxylin-eosin staining suggest the presence of false lumens and mural hematomas in the vessels. Our model-induction technique, inspired by iatrogenic catheter-induced artery dissections (carotid, coronary, aortic), significantly mimics the pathological process of clinical carotid dissection. The results suggest that mechanical injury may be a significant cause of carotid dissection and that intimal injury is a major factor in the formation of arterial dissections. This approach will provide assistance in the understanding of medically induced arterial dissection.

Alzheimer’s disease (AD) is a prevalent form of dementia that affects an estimated 32 million individuals globally. Identifying early indicators is vital for screening at-risk populations and implementing timely interventions. At present, there is an urgent need for early and sensitive biomarkers to screen individuals at risk of AD. Among all sensory biomarkers, olfaction is currently one of the most promising indicators for AD. Olfactory dysfunction signifies a decline in the ability to detect, identify, or remember odors. Within the spectrum of AD, impairment in olfactory identification precedes detectable cognitive impairments, including mild cognitive impairment (MCI) and even the stage of subjective cognitive decline (SCD), by several years. Olfactory impairment is closely linked to the clinical symptoms and neuropathological biomarkers of AD, accompanied by significant structural and functional abnormalities in the brain. Olfactory behavior examination can subjectively evaluate the abilities of olfactory identification, threshold, and discrimination. Olfactory functional magnetic resonance imaging (fMRI) can provide a relatively objective assessment of olfactory capabilities, with the potential to become a promising tool for exploring the neural mechanisms of olfactory damage in AD. Here, we provide a timely review of recent literature on the characteristics, neuropathology, and examination of olfactory dysfunction in the AD continuum. We focus on the early changes in olfactory indicators detected by behavioral and fMRI assessments and discuss the potential of these techniques in MCI and preclinical AD. Despite the challenges and limitations of existing research, olfactory dysfunction has demonstrated its value in assessing neurodegenerative diseases and may serve as an early indicator of AD in the future.

Repetitive mild traumatic brain injury (rmTBI) is one of the leading causes of cognitive disorders. The impairment of axonal integrity induced by rmTBI is speculated to underlie the progression of cognitive dysfunction. However, few studies have uncovered the cellular mechanism regulating axonal impairment. In this study, we showed that after rmTBI, the activation of neuronal p75NTR signaling contributes to abnormal axonal morphology and impaired axonal transport, which further leads to cognitive dysfunction in mice. By neuron-specific knockdown of p75NTR or treatment with p75NTR inhibitor LM11A-31, we observed better recovery of axonal integrity and cognitive function after brain trauma. Further analysis revealed that p75NTR relies on its adaptor protein TRAF6 to activate downstream signaling via TAK1 and JNK. Overall, our results provide novel insight into the role of neuronal p75NTR in axonal injury and suggest that p75NTR may be a promising target for cognitive function recovery after rmTBI.

Reactive astrocytes play an important role in neurological diseases, but their molecular and functional phenotypes in epilepsy are unclear. Here, we show that in patients with temporal lobe epilepsy (TLE) and mouse models of epilepsy, excessive lipid accumulation in astrocytes leads to the formation of lipid-accumulated reactive astrocytes (LARAs), a new reactive astrocyte subtype characterized by elevated APOE expression. Genetic knockout of APOE inhibited LARA formation and seizure activities in epileptic mice. Single-nucleus RNA sequencing in TLE patients confirmed the existence of a LARA subpopulation with a distinct molecular signature. Functional studies in epilepsy mouse models and human brain slices showed that LARAs promote neuronal hyperactivity and disease progression. Targeting LARAs by intervention with lipid transport and metabolism could thus provide new therapeutic options for drug-resistant TLE.

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive brain modulation and rehabilitation technique used in patients with neuropsychiatric diseases. rTMS can structurally remodel or functionally induce activities of specific cortical regions and has developed to an important therapeutic method in such patients. Magnetic resonance imaging (MRI) provides brain data that can be used as an explanation tool for the neural mechanisms underlying rTMS effects; brain alterations related to different functions or structures may be reflected in changes in the interaction and influence of brain connections within intrinsic specific networks. In this review, we discuss the technical details of rTMS and the biological interpretation of brain networks identified with MRI analyses, comprehensively summarize the neurobiological effects in rTMS-modulated individuals, and elaborate on changes in the brain network in patients with various neuropsychiatric diseases receiving rehabilitation treatment with rTMS. We conclude that brain connectivity network analysis based on MRI can reflect alterations in functional and structural connectivity networks comprising adjacent and separated brain regions related to stimulation sites, thus reflecting the occurrence of intrinsic functional integration and neuroplasticity. Therefore, MRI is a valuable tool for understanding the neural mechanisms of rTMS and practically tailoring treatment plans for patients with neuropsychiatric diseases.

Background Photodynamic therapy (PDT) has achieved continued success in the treatment of tumors, but its progress in the treatment of atherosclerosis has been limited, mainly due to the low tissue-penetration ability of the excitation light for photosensitizers. Methods In this study, we designed a chemiexcited system producing singlet oxygen in an attempt to apply PDT for the treatment of atherosclerosis without the irradiation of external light. The system designed was polymeric nanoparticles (NPs) equipped with chemical fuel and photosensitizers, cross-linked with an Fe3+–catechol complex for stabilization and magnetic resonance imaging (MRI). Results The system (FeCNPs for short) accumulated effectively in plaques, providing persistent and enhanced T1-weighted contrast ability. FeCNPs also prevented progression of atherosclerosis via macrophage elimination, and obviously reduced plaque size and thickness revealed by T1-weighted MRI. Expression of CD68, MCP1, and TNFα was significantly reduced after treatment. However, low doses of FeCNPs exhibited better therapeutic efficacy than high doses. Furthermore, low-dose FeCNPs exhibited effective macrophage elimination in aortic arches and abdominal aortae, but inefficiency in the thoracic aorta, aortic hiatus, and aorta–iliac bifurcation. Conclusion This study provides the first example of a combination of MRI and chemiexcited PDT for atherosclerosis, evidencing the effectiveness of PDT and providing significant pointers for developing nanotherapy on atherosclerosis.

Objective To evaluate the feasibility of 9. 4-T postmortem MRI (pm-MRI) for assessment of major congenital heart defects (CHD) cases terminated in the early stage of gestation. Methods Fetuses with CHD detected by the detailed first-trimester ultrasound scan and terminated before 18 gestational weeks were recruited between January 2018 and June 2020. All fetuses were offered 9.4-T pm-MRI examinations and those terminated over 13+6 weeks were offered conventional autopsies simultaneously. Findings of pm-MRI were compared with those of conventional autopsy and prenatal ultrasound. Results A total of 19 fetuses with major CHD were analyzed, including 6 cases of the atrioventricular septal defect, 5 cases of Tetralogy of Fallot, 3 cases of hypoplastic left heart syndrome, 1 case of tricuspid atresia, 1 case of transposition of the great arteries, 1 case of severe tricuspid regurgitation, and 2 cases of complex CHD. Pm-MRI had concordant findings in 73.7% (14/19) cases, discordant findings in 15.8% (3/19) cases, and additional findings in 10.5% (2/19) cases when compared with prenatal ultrasound. Pm-MRI findings were concordant with autopsy in all 8 CHD cases terminated over 13+6 weeks. Conclusion It is feasible to exhibit the structure of fetal heart terminated in the first trimester clearly on 9.4-T pm-MRI with an optimized scanning protocol. High-field pm-MRI could provide medical imaging information of CHD for those terminated in the early stage of gestation, especially for those limited by conventional autopsy.

ObjectiveChemotherapy-related brain impairments and changes can occur in patients with lung cancer after platinum chemotherapy and have a substantial impact on survivors' quality of life. Therefore, it is necessary to understand the brain neuropathological alterations and response mechanisms to provide a theoretical basis for rehabilitation strategies. This study aimed to investigate the related brain morphological changes and clarified their correlation with clinical and pathological indicators in patients with lung cancer after platinum chemotherapy. MethodsOverall, 28 patients with chemotherapy, 56 patients without chemotherapy, and 41 healthy controls were categorized in three groups, matched for age, sex, and years of education, and included in the cross-sectional comparison of brain volume and cortical thickness. 14 matched patients before and after chemotherapy were subjected to paired comparison for longitudinal observation of brain morphological changes. Three-dimensional T-1-weighted images were acquired from all participants, and quantitative parameters were calculated using the formula of the change from baseline. Correlation analysis was performed to evaluate the relationship between abnormal morphological indices and clinical information of patients. ResultsBrain regions with volume differences among the three groups were mainly distributed in frontal lobe and limbic cortex. Additionally, significant differences in cerebrospinal fluid were observed in most ventricles, and the main brain regions with cortical thickness differences were the gyrus rectus and medial frontal cortex of the frontal lobe, transverse temporal gyrus of the temporal lobe, insular cortex, anterior insula, and posterior insula of the insular cortex. According to the paired comparison, decreased brain volumes in the patients after chemotherapy appeared in some regions of the frontal, parietal, temporal, and occipital lobes; limbic cortex; insular cortex; and lobules VI-X and decreased cortical thickness in the patients after chemotherapy was found in the frontal, temporal, limbic, and insular cortexes. In the correlation analysis, only the differentiation degree of the tumor and duration after chemotherapy were significantly correlated with imaging indices in the abnormal brain regions. ConclusionsOur findings illustrate the platinum-related brain reactivity morphological alterations which provide more insights into the neuropathological mechanisms of patients with lung cancer after platinum chemotherapy and empirical support for the details of brain injury related to cancer and chemotherapy.

Aim Astrocytes are connected by gap junctions Connexin43 (GJs-Cx43) forming an extensive intercellular network and maintain brain homeostasis. Perioperative neurocognitive disorder (PND) occurs frequently after anesthesia/surgery and worsens patient outcome, but the neural circuit mechanisms remain unclear. This study aimed to determine the effects of the GJs-Cx43-mediated astrocytic network on PND and ascertain the underlying neural circuit mechanism. Methods Male C57BL/6 mice were treated with long-term isoflurane exposure to construct a mouse model of PND. We also exposed primary mouse astrocytes to long-term isoflurane exposure to simulate the conditions of in vivo cognitive dysfunction. Behavioral tests were performed using the Y-maze and fear conditioning (FC) tests. Manganese-enhanced magnetic resonance imaging (MEMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) were used to investigate brain activity and functional connectivity. Western blot and flow cytometry analysis were used to assess protein expression. Results Reconfiguring the astrocytic network by increasing GJs-Cx43 expression can modulate 22 subregions affected by PND in three ways: reversed activation, reversed inhibition, and intensified activation. The brain functional connectivity analysis further suggests that PND is a brain network disorder that includes sleep-wake rhythm-related brain regions, contextual and fear memory-related subregions, the hippocampal-amygdala circuit, the septo-hippocampal circuit, and the entorhinal-hippocampal circuit. Notably, remodeling the astrocytic network by upregulation of GJs-Cx43 can partially reverse the abnormalities in the above circuits. Pathophysiological degeneration in hippocampus is one of the primary hallmarks of PND pathology, and long-term isoflurane anesthesia contributes to oxidative stress and neuroinflammation in the hippocampus. However, promoting the formation of GJs-Cx43 ameliorated cognitive dysfunction induced by long-term isoflurane anesthesia through the attenuation of oxidative stress in hippocampus. Conclusion Enhancing GJs-Cx43 coupling can improve brain network abnormalities and cognitive impairment induced by long-term isoflurane anesthesia, its mechanisms might be associated with the regulation of oxidative stress and neuroinflammation.

Chemotherapy-related cognitive impairment (CRCI) is a common complication in patients with non-central nervous system malignancies after chemotherapy and significantly impacts the quality of life of survivors. It is essential to understand the neuroimaging mechanism of CRCI to provide a theoretical basis for clinical rehabilitation strategies as the number of survivors at risk for acute and long-term CRCI is increasing dramatically. In this review, we summarize the main neuroimaging features and findings of clinical patients and preclinical animals with CRCI from structural and functional measurements to molecular imaging, from regional to network-based large-scale analysis, from metabolite concentration to blood perfusion status, and from single-modal group-level statistics to multimodal and individual prediction, with the aim to elaborate on multiple-image signatures of patients and animals with cognitive impairment induced by chemotherapy. In addition, the emerging trend of neuroimaging applications in the comprehensive multimodal and individual prediction in patients with CRCI is addressed. Overall, the review explored the heterogeneity of neuropathological mechanisms of CRCI with neuroimaging technology and verified the findings from clinical to preclinical research. The neuropathological mechanism of CRCI involves abnormal alterations not only in morphology, structure, and functions but also in neuro-electrophysiology, biochemical metabolites, and blood perfusion in related brain regions associated with cognition. We conclude that neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential in identifying underlying neurobiological alterations associated with CRCI. Longitudinal studies with larger sample sizes combined with individual predictions and molecular imaging technology are still warranted to prove their practical utility for more medications than just chemotherapy.

Macrophage accumulation is central to the pathogenesis of atherosclerotic plaques. Reducing macrophages in plaques is an appealing approach to attenuate the development of atherosclerosis. Chemodynamic therapy, specifically inhibiting hydrogen peroxide (H2O2)-rich cells in slightly acidic microenvironment, has emerged as a new method in tumor treatment. Herein, we manufactured ultrasmall dopamine-modified hyaluronic acid (HD)-stabilized Fe(III)-tannic acid nanoparticles (HFTNPs). HFTNPs can specifically accumulate in inflammatory macrophages in atherosclerotic plaques, provide brighter magnetic resonance images, promote reactive oxygen species (ROS) generation, and induce the death of inflammatory macrophages without damaging normal cells and tissues. In conclusion, HFTNPs have a tremendous potential as safe and effective diagnostic and therapeutic reagents for atherosclerosis.

The structural covariance network (SCN) has provided a perspective on the large-scale brain organization impairment in the Alzheimer's Disease (AD) continuum. However, the successive structural impairment across brain regions, which may underlie the disrupted SCN in the AD continuum, is not well understood. In the current study, we enrolled 446 subjects with AD, mild cognitive impairment (MCI) or normal aging (NA) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The SCN as well as a casual SCN (CaSCN) based on Granger causality analysis were applied to the T1-weighted structural magnetic resonance images of the subjects. Compared with that of the NAs, the SCN was disrupted in the MCI and AD subjects, with the hippocampus and left middle temporal lobe being the most impaired nodes, which is in line with previous studies. In contrast, according to the 194 subjects with records on CSF amyloid and Tau, the CaSCN revealed that during AD progression, the CaSCN was enhanced. Specifically, the hippocampus, thalamus, and precuneus/posterior cingulate cortex (PCC) were identified as the core regions in which atrophy originated and could predict atrophy in other brain regions. Taken together, these findings provide a comprehensive view of brain atrophy in the AD continuum and the relationships among the brain atrophy in different regions, which may provide novel insight into the progression of AD.

Patients with Alzheimer's disease (AD) related dementia and mild cognitive impairment experience difficulties with spatial navigation (SN). However, SN has rarely been investigated in individuals with subjective cognitive decline (SCD), a preclinical stage with elevated progression rate to symptomatic AD. In this study, 30 SCD subjects and 30 controls underwent cognitive scale (CS) evaluation, a 2D computerized SN test, and resting-state functional magnetic resonance imaging scanning. Two SN brain networks (ego-network and allo-network), each with 10 selected spherical regions, were defined. We calculated the average network functional connectivity (FC) and region-to-region FC within the two networks and evaluated correlations with SN performance. Compared with the controls, the SCD group performed worse in the SN test and showed decreased FC between the right retrosplenial and right prefrontal cortices in the ego-network, and between the right retrosplenial cortex and right hippocampus in the allo-network. The logistic regression model based on SN and FC measures revealed a high area under the curve of .880 in differentiating SCD individuals from controls. These results suggest that SN network disconnection contributes to spatial deficits in SCD, and SN and FC measures could benefit the preclinical detection of subjects with incipient AD dementia.

Frontotemporal dementia (FTD) and Alzheimer's disease (AD) have overlapping symptoms, and accurate differential diagnosis is important for targeted intervention and treatment. Previous studies suggest that the deep learning (DL) techniques have the potential to solve the differential diagnosis problem of FTD, AD and normal controls (NCs), but its performance is still unclear. In addition, existing DL-assisted diagnostic studies still rely on hypothesis-based expert-level preprocessing. On the one hand, it imposes high requirements on clinicians and data themselves; On the other hand, it hinders the backtracking of classification results to the original image data, resulting in the classification results cannot be interpreted intuitively. In the current study, a large cohort of 3D T1-weighted structural magnetic resonance imaging (MRI) volumes (n = 4,099) was collected from two publicly available databases, i.e., the ADNI and the NIFD. We trained a DL-based network directly based on raw T1 images to classify FTD, AD and corresponding NCs. And we evaluated the convergence speed, differential diagnosis ability, robustness and generalizability under nine scenarios. The proposed network yielded an accuracy of 91.83% based on the most common T1-weighted sequence [magnetization-prepared rapid acquisition with gradient echo (MPRAGE)]. The knowledge learned by the DL network through multiple classification tasks can also be used to solve subproblems, and the knowledge is generalizable and not limited to a specified dataset. Furthermore, we applied a gradient visualization algorithm based on guided backpropagation to calculate the contribution graph, which tells us intuitively why the DL-based networks make each decision. The regions making valuable contributions to FTD were more widespread in the right frontal white matter regions, while the left temporal, bilateral inferior frontal and parahippocampal regions were contributors to the classification of AD. Our results demonstrated that DL-based networks have the ability to solve the enigma of differential diagnosis of diseases without any hypothesis-based preprocessing. Moreover, they may mine the potential patterns that may be different from human clinicians, which may provide new insight into the understanding of FTD and AD.