Plasma Chemical Looping: Unlocking High-Efficiency CO2 Conversion to Clean CO at Mild Temperatures.

We propose a plasma chemical looping CO2 splitting (PCLCS) approach that enables highly efficient CO2 conversion into O2-free CO at mild temperatures. PCLCS achieves an impressive 84% CO2 conversion and a 1.3 mmol g-1 CO yield, with no O2 detected. Crucially, this strategy significantly lowers the temperature required for conventional chemical looping processes from 650 to 1000 °C to only 320 °C, demonstrating a robust synergy between plasma and the Ce0.7Zr0.3O2 oxygen carrier (OC). Systematic experiments and density functional theory (DFT) calculations unveil the pivotal role of plasma in activating and partially decomposing CO2, yielding a mixture of CO, O2/O, and electronically/vibrationally excited CO2*. Notably, these excited CO2* species then efficiently decompose over the oxygen vacancies of the OCs, with a substantially reduced activation barrier (0.86 eV) compared to ground-state CO2 (1.63 eV), contributing to the synergy. This work offers a promising and energy-efficient pathway for producing O2-free CO from inert CO2 through the tailored interplay of plasma and OCs.

Signal enhancement ratio of multi-phase contrast-enhanced MRI: an imaging biomarker for survival in pancreatic adenocarcinoma.

OBJECTIVES: To evaluate signal enhancement ratio (SER) for tissue characterization and prognosis stratification in pancreatic adenocarcinoma (PDAC), with quantitative histopathological analysis (QHA) as the reference standard. METHODS: This retrospective study included 277 PDAC patients who underwent multi-phase contrast-enhanced (CE) MRI and whole-slide imaging (WSI) from three centers (2015-2021). SER is defined as (SIlt - SIpre)/(SIea - SIpre), where SIpre, SIea, and SIlt represent the signal intensity of the tumor in pre-contrast, early-, and late post-contrast images, respectively. Deep-learning algorithms were implemented to quantify the stroma, epithelium, and lumen of PDAC on WSIs. Correlation, regression, and Bland-Altman analyses were utilized to investigate the associations between SER and QHA. The prognostic significance of SER on overall survival (OS) was evaluated using Cox regression analysis and Kaplan-Meier curves. RESULTS: The internal dataset comprised 159 patients, which was further divided into training, validation, and internal test datasets (n = 60, 41, and 58, respectively). Sixty-five and 53 patients were included in two external test datasets. Excluding lumen, SER demonstrated significant correlations with stroma (r = 0.29-0.74, all p < 0.001) and epithelium (r = -0.23 to -0.71, all p < 0.001) across a wide post-injection time window (range, 25-300 s). Bland-Altman analysis revealed a small bias between SER and QHA for quantifying stroma/epithelium in individual training, validation (all within ± 2%), and three test datasets (all within ± 4%). Moreover, SER-predicted low stromal proportion was independently associated with worse OS (HR = 1.84 (1.17-2.91), p = 0.009) in training and validation datasets, which remained significant across three combined test datasets (HR = 1.73 (1.25-2.41), p = 0.001). CONCLUSION: SER of multi-phase CE-MRI allows for tissue characterization and prognosis stratification in PDAC. CLINICAL RELEVANCE STATEMENT: The signal enhancement ratio of multi-phase CE-MRI can serve as a novel imaging biomarker for characterizing tissue composition and holds the potential for improving patient stratification and therapy in PDAC. KEY POINTS: Imaging biomarkers are needed to better characterize tumor tissue in pancreatic adenocarcinoma. Signal enhancement ratio (SER)-predicted stromal/epithelial proportion showed good agreement with histopathology measurements across three distinct centers. Signal enhancement ratio (SER)-predicted stromal proportion was demonstrated to be an independent prognostic factor for OS in PDAC.

Long-range connections damage in white matter hyperintensities affects information processing speed.

White matter hyperintensities, one of the major markers of cerebral small vessel disease, disrupt the integrity of neuronal networks and ultimately contribute to cognitive dysfunction. However, a deeper understanding of how white matter hyperintensities related to the connectivity patterns of brain hubs at the neural network level could provide valuable insights into the relationship between white matter hyperintensities and cognitive dysfunction. A total of 36 patients with moderate to severe white matter hyperintensities (Fazekas score ≥ 3) and 34 healthy controls underwent comprehensive neuropsychological assessments and resting-state functional MRI scans. The voxel-based graph-theory approach-functional connectivity strength was employed to systematically investigate the topological organization of the whole-brain networks. The white matter hyperintensities patients performed significantly worse than the healthy controls in episodic memory, executive function and information processing speed. Additionally, we found that white matter hyperintensities selectively affected highly connected hub regions, predominantly involving the medial and lateral prefrontal, precuneus, inferior parietal lobule, insula and thalamus. Intriguingly, this impairment was connectivity distance-dependent, with the most prominent disruptions observed in long-range connections (e.g. 100-150 mm). Finally, these disruptions of hub connectivity (e.g. the long-range functional connectivity strength in the left dorsolateral prefrontal cortex) positively correlated with the cognitive performance in white matter hyperintensities patients. Our findings emphasize that the disrupted hub connectivity patterns in white matter hyperintensities are dependent on connection distance, especially longer-distance connections, which in turn predispose white matter hyperintensities patients to worse cognitive function.

Development of a radiomics-based model to predict occult liver metastases of pancreatic ductal adenocarcinoma: a multicenter study.

BACKGROUND: Undetectable occult liver metastases block the long-term survival of pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop a radiomics-based model to predict occult liver metastases and assess its prognostic capacity for survival. MATERIALS AND METHODS: Patients who underwent surgical resection and were pathologically proven with PDAC were recruited retrospectively from five tertiary hospitals between January 2015 and December 2020. Radiomics features were extracted from tumors, and the radiomics-based model was developed in the training cohort using LASSO-logistic regression. The model's performance was assessed in the internal and external validation cohorts using the area under the receiver operating curve (AUC). Subsequently, the association of the model's risk stratification with progression-free survival (PFS) and overall survival (OS) was then statistically examined using Cox regression analysis and the log-rank test. RESULTS: A total of 438 patients [mean (SD) age, 62.0 (10.0) years; 255 (58.2%) male] were divided into the training cohort ( n =235), internal validation cohort ( n =100), and external validation cohort ( n =103). The radiomics-based model yielded an AUC of 0.73 (95% CI: 0.66-0.80), 0.72 (95% CI: 0.62-0.80), and 0.71 (95% CI: 0.61-0.80) in the training, internal validation, and external validation cohorts, respectively, which were higher than the preoperative clinical model. The model's risk stratification was an independent predictor of PFS (all P <0.05) and OS (all P <0.05). Furthermore, patients in the high-risk group stratified by the model consistently had a significantly shorter PFS and OS at each TNM stage (all P <0.05). CONCLUSION: The proposed radiomics-based model provided a promising tool to predict occult liver metastases and had a great significance in prognosis.

Plasma Aß level alterations after sleep deprivation correspond to brain structural remodeling in medical night shift workers.

The relationship between brain structure alteration and metabolic product clearance after night shift work with total sleep deprivation (SD) remains unclear. Twenty-two intensive care unit staff on regularly rotating shift work were implemented with structural and diffusion MRI under both rest wakefulness (RW) and SD conditions. Peripheral blood samples were collected for the measurement of cerebral metabolites. Voxel-based morphometry and diffusion tensor imaging analysis were used to investigate the alterations in the gray matter density (GMD) and mean diffusivity (MD) within the participants. Furthermore, correlation analysis was performed to investigate the relationship between the neuroimaging metrics and hematological parameters. A significant increase in the GMD values was observed in the anterior and peripheral areas of the brain under SD. In contrast, a decrease in the values was observed in the posterior regions, such as the bilateral cerebellum and thalamus. In addition, a significant reduction in the total cerebrospinal fluid volume was observed under SD. The Aß42/Aß40 levels in participants under SD were significantly lower than those under RW. The mean MD increment values extracted from the region of interest (ROI) of the anterior brain were negatively correlated with the increment of plasma Aß42/Aß40 levels (r = -0.658, P = 0.008). The mean GMD decrement values extracted from the posterior ROI were positively correlated with the increment of plasma Aß-40 levels (r = 0.601, P = 0.023). The findings of this study suggest that one night of shift work under SD induces extensive and direction-specific structural alterations of the brain, which are associated with aberrant brain metabolic waste clearance.

Spleen volume-based non-invasive tool for predicting hepatic decompensation in people with compensated cirrhosis (CHESS1701).

Background & Aims: Non-invasive stratification of the liver decompensation risk remains unmet in people with compensated cirrhosis. This study aimed to develop a non-invasive tool (NIT) to predict hepatic decompensation. Methods: This retrospective study recruited 689 people with compensated cirrhosis (median age, 54 years; 441 men) from 5 centres from January 2016 to June 2020. Baseline abdominal computed tomography (CT), clinical features, and liver stiffness were collected, and then the first decompensation was registered during the follow-up. The spleen-based model was designed for predicting decompensation based on a deep learning segmentation network to generate the spleen volume and least absolute shrinkage and selection operator (LASSO)-Cox. The spleen-based model was trained on the training cohort of 282 individuals (Institutions I-III) and was validated in 2 external validation cohorts (97 and 310 individuals from Institutions IV and V, respectively) and compared with the conventional serum-based models and the Baveno VII criteria. Results: The decompensation rate at 3 years was 23%, with a 37.6-month median (IQR 21.1-52.1 months) follow-up. The proposed model showed good performance in predicting decompensation (C-index ≥0.84) and outperformed the serum-based models (C-index comparison test p <0.05) in both the training and validation cohorts. The hazard ratio (HR) for decompensation in individuals with high risk was 7.3 (95% CI 4.2-12.8) in the training and 5.8 (95% CI 3.9-8.6) in the validation (log-rank test, p <0.05) cohorts. The low-risk group had a negligible 3-year decompensation risk (≤1%), and the model had a competitive performance compared with the Baveno VII criteria. Conclusions: This spleen-based model provides a non-invasive and user-friendly method to help predict decompensation in people with compensated cirrhosis in diverse healthcare settings where liver stiffness is not available. Lay summary: People with compensated cirrhosis with larger spleen volume would have a higher risk of decompensation. We developed a spleen-based model and validated it in external validation cohorts. The proposed model might help predict hepatic decompensation in people with compensated cirrhosis when invasive tools are unavailable.

Insulin Resistance and Cognitive Impairment: Evidence From Neuroimaging.

Insulin is a peptide well known for its role in regulating glucose metabolism in peripheral tissues. Emerging evidence from human and animal studies indicate the multifactorial role of insulin in the brain, such as neuronal and glial metabolism, glucose regulation, and cognitive processes. Insulin resistance (IR), defined as reduced sensitivity to the action of insulin, has been consistently proposed as an important risk factor for developing neurodegeneration and cognitive impairment. Although the exact mechanism of IR-related cognitive impairment still awaits further elucidation, neuroimaging offers a versatile set of novel contrasts to reveal the subtle cerebral abnormalities in IR. These imaging contrasts, including but not limited to brain volume, white matter (WM) microstructure, neural function and brain metabolism, are expected to unravel the nature of the link between IR, cognitive decline, and brain abnormalities, and their changes over time. This review summarizes the current neuroimaging studies with multiparametric techniques, focusing on the cerebral abnormalities related to IR and therapeutic effects of IR-targeting treatments. According to the results, brain regions associated with IR pathophysiology include the medial temporal lobe, hippocampus, prefrontal lobe, cingulate cortex, precuneus, occipital lobe, and the WM tracts across the globe. Of these, alterations in the temporal lobe are highly reproducible across different imaging modalities. These structures have been known to be vulnerable to Alzheimer's disease (AD) pathology and are critical in cognitive processes such as memory and executive functioning. Comparing to asymptomatic subjects, results are more mixed in patients with metabolic disorders such as type 2 diabetes and obesity, which might be attributed to a multifactorial mechanism. Taken together, neuroimaging, especially MRI, is beneficial to reveal early abnormalities in cerebral structure and function in insulin-resistant brain, providing important evidence to unravel the underlying neuronal substrate that reflects the cognitive decline in IR. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Increased Resting-State Functional Connectivity of the Hippocampus in Rats With Sepsis-Associated Encephalopathy.

Background: Sepsis-associated encephalopathy (SAE) has been identified as a frequent complication of sepsis, featured by an aberrant level of cognitive and affective functions. The present study is designed to explore the changes in functional connectivity (FC) of the hippocampus in rats with SAE utilizing resting-state functional magnetic resonance imaging (rs-fMRI). Methods: Sprague-Dawley rats were randomly assigned to the SAE and control groups. We acquired rs-fMRI data using a 7T MRI to evaluate hippocampal network functional differences between the two groups with a seed-based approach. Behavioral performance was assessed using the open field test and forced swimming test. Statistical analysis was undertaken to evaluate the correlation between the hippocampal FC and behavioral findings. Results: Compared with the control group, the SAE group showed increased FC between the bilateral hippocampus and thalamus, septum, bed nuclei stria terminalis (BNST), left primary forelimb somatosensory cortex (S1FL), primary motor cortex (M1), and inferior colliculus. Increased FC between the left hippocampus and thalamus, septum, BNST, left S1FL, and inferior colliculus was observed. While with the right hippocampus, FC in thalamus, septum, left S1FL and inferior colliculus was enhanced. Additionally, positive correlations were found between the hippocampal FC and the immobility time in the forced swimming test. Conclusion: Hippocampus-related brain networks have significant alterations in rats with SAE, and the elevated hippocampal resting-state FC was positively related to affective deficits. Changes in FC between the hippocampus and other brain regions could be a potential neuroimaging biomarker of cognitive or mental disorders triggered by SAE.

Alterations to cognitive abilities and functional networks in rats post broad-band intense noise exposure.

This study aimed to investigate the alterations of cognition and functional connectivity post noise, and find the progress and neural substrates of noise induced hearing loss (NIHL)-associated cognitive impairment. We exposed rats to 122 dB broad-band noise for 2 h to induce hearing loss and the auditory function was assessed by measuring auditory brainstem response thresholds. Morris water maze test and resting state MRI were computed at 0 day, 1, 3, 6 months post noise to reveal cognitive ability and neural substrate. The interregional connections in the auditory network and default mode network, as well as the connections using the auditory cortex and cingulate cortex as seeds were also examined addtionally. The deficit in spatial learning/memory was only observed at 6 months after noise exposure. The internal connections in the auditory network and default mode network were enhanced at 0 day and decreased at 6 months post noise. The connectivity using the auditory cortex and cingulate cortex as seeds generally followed the rule of "enhancement-normal-decrease-widely decrease". A new model accounting for arousal, dementia, motor control of NIHL in is proposed. Our study highlights the fundamental flexibility of neural systems, and may also point toward novel therapeutic strategies for treating sensory disorders.

An imaging-based artificial intelligence model for non-invasive grading of hepatic venous pressure gradient in cirrhotic portal hypertension.

The hepatic venous pressure gradient (HVPG) is the gold standard for cirrhotic portal hypertension (PHT), but it is invasive and specialized. Alternative non-invasive techniques are needed to assess the hepatic venous pressure gradient (HVPG). Here, we develop an auto-machine-learning CT radiomics HVPG quantitative model (aHVPG), and then we validate the model in internal and external test datasets by the area under the receiver operating characteristic curves (AUCs) for HVPG stages (≥10, ≥12, ≥16, and ≥20 mm Hg) and compare the model with imaging- and serum-based tools. The final aHVPG model achieves AUCs over 0.80 and outperforms other non-invasive tools for assessing HVPG. The model shows performance improvement in identifying the severity of PHT, which may help non-invasive HVPG primary prophylaxis when transjugular HVPG measurements are not available.

Beyond collaterals: brain frailty additionally improves prediction of clinical outcome in acute ischemic stroke.

OBJECTIVES: We aimed to investigate the additional significance of cerebral small vessel disease (SVD) beyond collaterals in determining the clinical outcome after acute ischemic stroke (AIS). METHODS: We retrospectively reviewed large vessel-involved stroke patients who had baseline CTA within 24 h after symptom onset and had an MRI scan 5 days after admission from October 1, 2018, to October 31, 2021. Collaterals and SVD markers (including atrophy, leukoaraiosis, lacunes, and perivascular space) were graded on CT angiography and MR images, respectively. Modified Rankin Scale (mRS) score at 90 days was recorded, and mRS ≤ 2 was regarded as a good clinical outcome. The associations between SVD markers, collaterals, and mRS were analyzed using logistic and causal mediation regression. RESULTS: We finally enrolled 119 patients (70 ± 13 years). The multivariable regression showed atrophy (evidence: OR 0.05 [95% CI 0.01-0.31], p = 0.002; severe: OR 0.08 [95% CI 0.01-0.44], p = 0.007) and evidence of lacune (OR 0.30 [95% CI 0.08-0.96], p = 0.049) were associated with poor clinical outcomes after correcting covariables. Collaterals mediated 25.74% of the effect of atrophy on poor clinical outcomes (p < 0.001), while lacune impacted clinical outcomes without collaterals' mediation effect (p = 0.54). The classification model with atrophy and lacune had a significantly higher AUC than without markers to distinguish good and poor outcomes (p = 0.036). CONCLUSIONS: Beyond collaterals, brain frailty, specifically assessed by atrophy and lacune, was essential in evaluating stroke patients and could additionally improve the stroke outcome prediction. KEY POINTS: • Beyond collaterals, brain frailty, specifically assessed by brain atrophy and lacune, was still an independent risk factor of unfavorable clinical outcomes after AIS. • Adding brain atrophy and lacune into the model has an extra benefit in predicting stroke outcomes. • The effect of atrophy on stroke outcomes was proportionally mediated through collaterals, but about three-quarters of the effect of brain atrophy and the total effect of lacune directly impacted stroke outcomes without a mediation effect of collaterals.

Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics.

BACKGROUND: Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies. METHODS: Patients with a single HCC of 2-5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop (n = 230) and test (n = 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR (n = 118) and NAR (n = 85) via propensity score matching using patient data from another 2 centers for external validation. RESULTS: The CRR model showed higher area under the curve values (0.835-0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796-0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group (P = 0.005) but not in the clinico-radiologic model predicted high-risk MVI group (P = 0.31). CONCLUSIONS: The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR.

An Investigation of the Impacts of Three Anesthetic Regimens on Task-Functional Magnetic Resonance Imaging and Functional Connectivity Resting-State Functional Magnetic Resonance Imaging in Sprague Dawley and Wistar Rats.

Aim: The aim of this study was to investigate basic task-functional magnetic resonance imaging (fMRI) or resting-state fMRI (rs-fMRI) results on Sprague Dawley (SD) rats and Wistar rats under three anesthetic regimens. Introduction: SD rats and Wistar rats are the two-most commonly used rat strains in medical research and neuroimaging studies. It still lacks a direct comparison of basic task-fMRI and rs-fMRI results between the Wistar rats and SD rats under different anesthetic regimens. Methods: Two rat strains and different time points were adopted to investigate task-fMRI activation and rs-fMRI functional connectivity (FC) results under three kinds of anesthetic regimens (2-2.5% isoflurane only, dexmedetomidine bolus combined with a continuous infusion, and dexmedetomidine bolus combined with 0.3-0.5% isoflurane). The electrical forepaw stimulation method and seed-based FC results were used to compare the task-fMRI brain activation and rs-fMRI FC patterns between the two rat strains. Results: The results showed that Wistar rats had more robust brain activation in task fMRI experiments while exhibiting a less specific interhemispheric FC than that of SD rats under the two dexmedetomidine anesthetic regimens. Moreover, even low-level isoflurane could significantly affect task-fMRI and rs-fMRI results in both rat strains. Conclusions: SD and Wistar rats showed different brain activations and interhemispheric FC patterns under the two dexmedetomidine anesthetic regimens. These results may serve as reference information for small-animal fMRI studies. Impact statement Our study demonstrates different stimulation-induced blood oxygen level-dependent responses and functional connectivity patterns between Sprague Dawley rats and Wistar rats under three anesthetics. This study provides some reference results for different anesthetics' effects on different rat strains in different functional magnetic resonance imaging modalities.

Brain structural differences in temporal lobe and frontal lobe epilepsy patients: A voxel-based morphometry and vertex-based surface analysis.

PURPOSE: Exploration of the effect of chronic recurrent seizures in focal epilepsy on brain volumes has produced many conflicting reports. To determine differences in brain structure in temporal lobe epilepsy (TLE) and extratemporal epilepsy (using frontal lobe epilepsy (FLE) a surrogate) further, we performed a retrospective analysis of a large cohort of patients with seizure-onset zone proven by intracranial monitoring. METHODS: A total of 120 TLE patients, 86 FLE patients, and 54 healthy controls were enrolled in this study. An analysis of variance of voxel-based morphometry (VBM) was used to seek morphometric brain differences among TLE patients, FLE patients, and healthy controls. Additionally, a vertex-based surface analysis was utilized to analyze the hippocampus and thalamus. Significant side-specific differences in hippocampal gray matter volume were present between the left TLE (LTLE), right TLE RTLE (RTLE), and control groups (p<0.05, family-wise error (FWE) corrected). RESULTS: Vertex analyses revealed significant volume reduction in inferior parts of the left hippocampus in the LTLE group and lateral parts of the right hippocampus in the RTLE group compared to controls (p<0.05, FWE corrected). Significant differences were also detected between the LTLE and control group in the bilateral medial and inferior thalamus (p<0.05, FWE corrected). FLE patients did not exhibit focal atrophy of gray matter across the brain. CONCLUSION: Our results highlight the variation in morphometric lateralized changes in the brain between different epilepsy onset zones, providing critical insight into the natural history of people with drug-resistant focal epilepsies.

Disturbed Interhemispheric Functional and Structural Connectivity in Type 2 Diabetes.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with cognitive decline and altered brain structure and function. However, the interhemispheric coordination of T2DM patients is unclear. PURPOSE: To investigate interhemispheric functional and anatomic connectivity in T2DM, and their associations with cognitive performance and endocrine parameters. STUDY TYPE: Prospective. SUBJECTS: 38 T2DM patients and 42 matched controls. FIELD STRENGTH/SEQUENCES: 3.0 T magnetic resonance imaging (MRI) scanner; magnetization-prepared rapid acquisition gradient echo sequence; fluid-attenuated inversion recovery sequence; single-shot, gradient-recalled echo-planar imaging sequence (resting-state functional MRI); and diffusion-weighted spin-echo-based echo-planar sequence (diffusion tensor imaging). ASSESSMENT: Voxel-mirrored homotopic connectivity (VMHC) value was calculated based on the functional images. Fibers passing through the regions with significant VMHC differences were identified using an atlas-guided track recognition. The mean fractional anisotropy (FA), mean diffusivity (MD), and fiber length were extracted and compared between the two groups. Finally, correlational analyses were performed to examine the relationships between abnormal interhemispheric connectivity, cognitive performances, and endocrine parameters. STATISTICAL TESTS: Two-sample t-tests were performed controlling for confounding factors, with partial correlation analysis. False discovery rate (FDR) correction was used for multiple comparisons. A P value <0.05 was considered statistically significant. RESULTS: T2DM patients exhibited significantly decreased VMHC between bilateral lingual gyrus and sensorimotor cortex. The fibers connecting lingual gyrus in patients showed significantly lower FA (P = 0.011) and shorter fiber length (P < 0.001), while the differences in sensorimotor fibers were insignificant (P = 0.096 for FA, P = 0.739 for fiber length and P = 0.150 for MD). The FA value in the lingual fibers was negatively correlated with insulin resistance (IR) level in T2DM group after FDR correction (R = -0.635). DATA CONCLUSION: We noted disruptions in interhemispheric coordination in T2DM patients, involving both functional and anatomical connectivities. IR might be a promising therapeutic target in the intervention of T2DM-related cognitive impairment. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Telmisartan ameliorates cardiac fibrosis and diastolic function in cardiorenal heart failure with preserved ejection fraction.

Chronic kidney disease (CKD) is a major contributor to the development of heart failure with preserved ejection fraction (HFpEF), whereas the underlying mechanism of cardiorenal HFpEF is still elusive. The aim of this study was to investigate the role of cardiac fibrosis in a rat model of cardiorenal HFpEF and explore whether treatment with Telmisartan, an inhibitor of renin-angiotensin-aldosterone system (RAAS), can ameliorate cardiac fibrosis and preserve diastolic function in cardiorenal HFpEF. Male rats were subjected to 5/6 subtotal nephrectomy (SNX) or sham operation (Sham), and rats were allowed four weeks to recover and form a stable condition of CKD. Telmisartan or vehicle was then administered p.o. (8 mg/kg/d) for 12 weeks. Blood pressure, brain natriuretic peptide (BNP), echocardiography, and cardiac magnetic resonance imaging were acquired to evaluate cardiac structural and functional alterations. Histopathological staining, real-time polymerase chain reaction (PCR) and western blot were performed to evaluate cardiac remodeling. SNX rats showed an HFpEF phenotype with increased BNP, decreased early to late diastolic transmitral flow velocity (E/A) ratio, increased left ventricular (LV) hypertrophy and preserved ejection fraction (EF). Pathology revealed increased cardiac fibrosis in cardiorenal HFpEF rats compared with the Sham group, while chronic treatment with Telmisartan significantly decreased cardiac fibrosis, accompanied by reduced markers of fibrosis (collagen I and collagen III) and profibrotic cytokines (α-smooth muscle actin, transforming growth factor-ß1, and connective tissue growth factor). In addition, myocardial inflammation was decreased after Telmisartan treatment, which was in a linear correlation with cardiac fibrosis. Telmisartan also reversed LV hypertrophy and E/A ratio, indicating that Telmisartan can improve LV remodeling and diastolic function in cardiorenal HFpEF. In conclusion, cardiac fibrosis is central to the pathology of cardiorenal HFpEF, and RAAS modulation with Telmisartan is capable of alleviating cardiac fibrosis and preserving diastolic dysfunction in this rat model.

Characterizing Diaschisis-Related Thalamic Perfusion and Diffusion After Middle Cerebral Artery Infarction.

Background and Purpose: Ipsilateral thalamic diaschisis (ITD) initially describes functional depression of the thalamus ipsilateral to a supratentorial lesion, but accumulating evidence has shown morphological changes also occur. Therefore, we aimed to characterize thalamic perfusion and diffusion related to ITD over time and their inter-relationships after middle cerebral artery infarction. Methods: Eighty-five patients with middle cerebral artery infarction who underwent diffusion kurtosis imaging and arterial spin labeling were retrospectively included. ITD was diagnosed as ipsilateral thalamic hypoperfusion present on ≥2 cerebral blood flow maps. The thalamic asymmetrical index was calculated as (ipsilateral value−contralateral value)/contralateral value×100%. Finally, the inter-relationships of thalamic perfusion and diffusion were analyzed. Results: ITD was present in 56/85 patients (65.9%, ITD+). In ITD+ patients, larger abnormal perfusion volume, higher perfusion-infarct mismatch and lower rates of focal hyperperfusion were observed than ITD− patients. Infarction affecting the corona radiata were more frequent among ITD+ patients. Mean kurtosis were slightly but significantly increased within the ipsilateral thalamus compared with the contralateral one in ITD+ patients of subacute and chronic groups, while fractional anisotropy was significantly increased in subacute group but decreased in chronic group for both ITD+ and ITD− patients. Mean diffusivity was significantly increased in ITD+ patients of chronic group. Furthermore, the AICBF was negatively and significantly correlated with AIMK and AIFA in ITD+ patients in subacute group, and AIMD, even after adjustment for abnormal perfusion volume and days from symptoms onset, in chronic group. ITD+ patients had significantly higher National Institutes of Health Stroke Scale and modified Rankin Scale scores at admission and discharge and also showed a trend to independent association with clinical outcome at discharge. Conclusions: The combination of arterial spin labeling and diffusion kurtosis imaging can reveal early, time-specific thalamic perfusion and diffusion changes after middle cerebral artery infarction. ITD-related hypoperfusion was significantly correlated with underlying microstructural alterations.

Comparison of MRI and CT for the Prediction of Microvascular Invasion in Solitary Hepatocellular Carcinoma Based on a Non-Radiomics and Radiomics Method: Which Imaging Modality Is Better?

BACKGROUND: Computed tomography (CT) and magnetic resonance imaging (MRI) are both capable of predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). However, which modality is better is unknown. PURPOSE: To intraindividually compare CT and MRI for predicting MVI in solitary HCC and investigate the added value of radiomics analyses. STUDY TYPE: Retrospective. SUBJECTS: Included were 402 consecutive patients with HCC (training set:validation set = 300:102). FIELD STRENGTH/SEQUENCE: T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted imaging MRI at 3.0T and contrast-enhanced CT. ASSESSMENT: CT- and MR-based radiomics signatures (RS) were constructed using the least absolute shrinkage and selection operator regression. CT- and MR-based radiologic (R) and radiologic-radiomics (RR) models were developed by univariate and multivariate logistic regression. The performance of the RS/models was compared between two modalities. To investigate the added value of RS, the performance of the R models was compared with the RR models in HCC of all sizes and 2-5 cm in size. STATISTICAL TESTS: Model performance was quantified by the area under the receiver operating characteristic curve (AUC) and compared using the Delong test. RESULTS: Histopathologic MVI was identified in 161 patients (training set:validation set = 130:31). MRI-based RS/models tended to have a marginally higher AUC than CT-based RS/models (AUCs of CT vs. MRI, P: RS, 0.801 vs. 0.804, 0.96; R model, 0.809 vs. 0.832, 0.09; RR model, 0.835 vs. 0.872, 0.54). The improvement of RR models over R models in all sizes was not significant (P = 0.21 at CT and 0.09 at MRI), whereas the improvement in 2-5 cm was significant at MRI (P < 0.05) but not at CT (P = 0.16). DATA CONCLUSION: CT and MRI had a comparable predictive performance for MVI in solitary HCC. The RS of MRI only had significant added value for predicting MVI in HCC of 2-5 cm. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Endogenous Regulatory T Cells Promote M2 Macrophage Phenotype in Diabetic Stroke as Visualized by Optical Imaging.

Regulatory T cells (Tregs) play an immunosuppressive role in various diseases, yet their function remains controversial in stroke and obscure in diabetic stroke. In the present study, Tregs were found downregulated in the peripheral blood of type 2 diabetes mellitus (T2DM) stroke models and patients compared with controls. In ischemic stroke mice (both T2DM and wild type), endogenous Tregs boosted by CD28SA increased CD206+ M2 macrophage/microglia cells, decreased infarct volumes, and improved neurological recovery. Our results demonstrated the potential of boosting Tregs for treating T2DM stroke. Furthermore, we utilized an optical imaging probe (IRD-αCD206) to target M2 macrophage/microglia cells and demonstrated its effect in visualizing M2 macrophage/microglia cells in vivo in ischemic brain tissue.