Increased regional Hurst exponent reflects response inhibition related neural complexity alterations in pediatric bipolar disorder patients during an emotional Go-Nogo task.

Fractal patterns have been shown to change in resting- and task-state blood oxygen level-dependent signals in bipolar disorder patients. However, fractal characteristics of brain blood oxygen level-dependent signals when responding to external emotional stimuli in pediatric bipolar disorder remain unclear. Blood oxygen level-dependent signals of 20 PBD-I patients and 17 age- and sex-matched healthy controls were extracted while performing an emotional Go-Nogo task. Neural responses relevant to the task and Hurst exponent of the blood oxygen level-dependent signals were assessed. Correlations between clinical indices and Hurst exponent were estimated. Significantly increased activations were found in regions covering the frontal lobe, parietal lobe, temporal lobe, insula, and subcortical nuclei in PBD-I patients compared to healthy controls in contrast of emotional versus neutral distractors. PBD-I patients exhibited higher Hurst exponent in regions that involved in action control, such as superior frontal gyrus, inferior frontal gyrus, inferior temporal gyrus, and insula, with Hurst exponent of frontal orbital gyrus correlated with onset age. The present study exhibited overactivation, increased self-similarity and decreased complexity in cortical regions during emotional Go-Nogo task in patients relative to healthy controls, which provides evidence of an altered emotional modulation of cognitive control in pediatric bipolar disorder patients. Hurst exponent may be a fractal biomarker of neural activity in pediatric bipolar disorder.

Highly Stretchable, Self-Healing, and Sensitive E-Skins at -78 °C for Polar Exploration.

Ultralow temperature-tolerant electronic skins (e-skins) can endow polar robots with tactile feedback for exploring in extremely cold polar environments. However, it remains a challenge to develop e-skins that enable sensitive touch sensation and self-healing at ultralow temperatures. Herein, we describe the development of a sensitive robotic hand e-skin that can stretch, self-heal, and sense at temperatures as low as -78 °C. The elastomeric substrate of this e-skin is based on poly(dimethylsiloxane) supramolecular polymers and multistrength dynamic H-bonds, in particular with quadruple H-bonding motifs (UPy). The structure-performance relationship of the elastomer at ultralow temperatures is investigated. The results show that elastomers with side-chain UPy units exhibit higher stretchability (∼3257%) and self-healing efficiency compared to those with main-chain UPy units. This is attributed to the lower binding energy variation and lower potential well. Based on the elastomer with side-chain UPy and man-made electric ink, a sensitive robotic hand e-skin for usage at -78 °C is constructed to precisely sense the shape of objects and specific symbols, and its sensation can completely self-recover after being damaged. The findings of this study contribute to the concept of using robotic hands with e-skins in polar environments that make human involvement limited, dangerous, or impossible.

Evidence of the Monopolar-Dipolar Crossover Regime: A Multiscale Study of Ferroelastic Domains by In Situ Microscopy Techniques.

The elastic interaction between kinks (and antikinks) within domain walls plays a pivotal role in shaping the domain structure, and their dynamics. In bulk materials, kinks interact as elastic monopoles, dependent on the distance between walls (d-1) and typically characterized by a rigid and straight domain configuration. In this work the evolution of the domain structure is investigated, as the sample size decreases, by the means of in situ heating microscopy techniques on free-standing samples. As the sample size decreases, a significant transformation is observed: domain walls exhibit pronounced curvature, accompanied by an increase in both domain wall and junction density. This transformation is attributed to the pronounced influence of kinks, inducing sample warping, where "dipole-dipole" interactions are dominant (d-2). Moreover, a critical thickness range that delineates a crossover between the monopolar and dipolar regimens is experimentally identified and corroborated by atomic simulations. These findings are relevant for in situ TEM studies and for the development of novel devices based on free-standing ferroic thin films and nanomaterials.

Edge-Type Hyperintense Intracranial Artery Plaque: A Potential MRI Biomarker of Stroke Recurrence.

BACKGROUND: Identifying patients at high risk of stroke recurrence is important for stroke prevention and treatment. PURPOSE: To explore the characteristics of T1 hyperintense plaques (HIP) and their relationship with stroke recurrence in patients with symptomatic intracranial atherosclerotic stenosis (sICAS). STUDY TYPE: Retrospective. POPULATION: One hundred fifty-seven patients with moderate-to-severe (≥50%) nonocclusive sICAS and MRI studies (42 females and 115 males, mean age 58.69 ± 10.68 years). FIELD STRENGTH/SEQUENCE: 3D higher-resolution black-blood T1-weighted fast-spin-echo sequence at 3.0 T. ASSESSMENT: HIP (signal intensity [SI] of plaque-to-adjacent gray matter >1.0 on non-contrast T1-weighted images) and non-HIP plaques were identified. HIP plaques were categorized as edge type (high SI adjacent to lumen) and non-edge type (high SI within plaque). Clinical and imaging features of different plaque types were compared. Stroke recurrence was assessed through telephone or medical records at 3 and 6 months, and then once a year post-MRI. The relationship between edge type and non-edge types HIP with stroke recurrence was analyzed. STATISTICAL TESTS: Student's t test, Mann-Whitney U-test, chi square test and Fisher's exact test to compare features between plaque types. Kaplan-Meier curves (with log-rank tests) and Cox proportional hazards regression to assess relationship between stroke recurrence and different plaque types. A two-tailed P-value of <0.05 was considered statistically significant. RESULTS: Of 157 culprit lesions, 87 (55%) were HIPs (43 edge type, 44 non-edge type) and 70 (45%) were non-HIPs. Plaque thickness, area, and volume were significantly higher for HIPs than for non-HIPs. Among patients with HIPs, edge type was significantly more likely in the posterior circulation (53.5% vs. 27.3%), and had significantly higher plaque thickness, length, area, volume, plaque burden, and remodeling index than non-edge type. Edge-type HIP was significantly more common than non-edge HIP in patients with diabetes mellitus (51.2% vs. 29.5%) and dyslipidemia (79.1% vs. 54.5%). During median follow-up of 27 months, 33 patients experienced stroke recurrence. Recurrence was associated with edge-type HIP (adjusted hazard ratio = 2.83; 95% confidence interval: 1.40-5.69), both in the overall cohort (34.9% vs. 15.8%) and in patients with HIP (34.9% vs. 9.0%). Age ≥60 years and edge-type HIP had a significant interaction. DATA CONCLUSIONS: Hyperintense plaque may be categorized as edge type or non-edge type. Edge-type HIP may be a potential MRI biomarker of stroke recurrence. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Distinguishing Intracranial Diabetes-Related Atherosclerotic Plaques: A High-Resolution Magnetic Resonance Imaging-Based Radiomics Study.

INTRODUCTION: Diabetes markedly affects the formation and development of intracranial atherosclerosis. The study was aimed at evaluating whether radiomics features can help distinguish plaques primarily associated with diabetes. MATERIALS AND METHODS: We retrospectively analyzed patients who were admitted to our center because of acute ischemic stroke due to intracranial atherosclerosis between 2016 and 2022. Clinical data, blood biomarkers, conventional plaque features, and plaque radiomics features were collected for all patients. Odds ratios (ORs) with 95% confidence intervals (CIs) were determined from logistic regression models. The receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) were used to describe diagnostic performance. The DeLong test was used to compare differences between models. RESULTS: Overall, 157 patients (115 men; mean age, 58.7 ± 10.7 years) were enrolled. Multivariate logistic regression analysis showed that plaque length (OR: 1.17; 95% CI: 1.07-1.28) and area (OR: 1.13; 95% CI: 1.02-1.24) were independently associated with diabetes. On combining plaque length and area as a conventional model, the AUCs of the training and validation cohorts for identifying diabetes patients were 0.789 and 0.720, respectively. On combining radiomics features on T1WI and contrast-enhanced T1WI sequences, a better diagnostic value was obtained in the training and validation cohorts (AUC: 0.889 and 0.861). The DeLong test showed the model combining radiomics and conventional plaque features performed better than the conventional model in both cohorts (p < 0.05). CONCLUSIONS: The use of radiomics features of intracranial plaques on high-resolution magnetic resonance imaging can effectively distinguish culprit plaques with diabetes as the primary pathological cause, which will provide new avenues of research into plaque formation and precise treatment.

Cortical thickness alterations are associated with astrocytes and excitatory neuron-specific transcriptome signatures in pediatric bipolar disorder.

Bipolar disorder (BD) is a heritable psychiatric disorder with a complex etiology that is often associated with cortical alterations. Morphometric studies in adults with BD are well established; however, few have examined cortical changes in pediatric BD (PBD). Additionally, the correlation between cortical thickness (CT) changes in PBD and gene expression remains elusive. Here, we performed an integrative analysis using neuroimaging data from 58 PBD individuals and the Allen human brain transcriptomic dataset. We applied partial least squares (PLS) regression analysis on structural MRI data and cortical gene expression, enrichment and specific cell type analysis to investigate the genetic correlates of CT alterations in PBD. We found the expression levels of PBD-related genes showed significant spatial correlations with CT differences. Further enrichment and specific cell type analysis revealed that transcriptome signatures associated with cortical thinning were enriched in synaptic signaling, ion channels, astrocytes, and excitatory neurons. Neurodevelopmental patterns of these genes showed significantly increased expression in the cerebellum, cortex, and subcortical regions during the adolescence period. These results highlight neurodevelopmental transcriptional changes could account for most of the observed correlations with CT differences in PBD, which offers a novel perspective to understand biological conceptualization mechanisms for the genetic correlates of CT alterations.

Relationship between SLC6A2 gene polymorphisms and brain volume in Han Chinese adults who lost their sole child.

BACKGROUND: Norepinephrine transporter (NET) is encoded by the SLC6A2 gene and is a potential target for studying the pathogenesis of PTSD. To the best of our knowledge, no prior investigations have examined SLC6A2 polymorphism-related neuroimaging abnormalities in PTSD patients. METHODS: In 218 Han Chinese adults who had lost their sole child, we investigated the association between the T-182 C SLC6A2 genotype and gray matter volume (GMV). Participants included 57 PTSD sufferers and 161 non-PTSD sufferers, and each group was further separated into three subgroups based on each participant's SLC6A2 genotype (TT, CT, and CC). All participants received magnetic resonance imaging (MRI) and clinical evaluation. To assess the effects of PTSD diagnosis, genotype, and genotype × diagnosis interaction on GMV, 2 × 3 full factorial designs were used. Pearson's correlations were used to examine the association between GMV and CAPS, HAMD, and HAMA. RESULTS: The SLC6A2 genotype showed significant main effects on GMV of the left superior parietal gyrus (SPG) and the bilateral middle cingulate gyrus (MCG). Additionally, impacts of the SLC6A2 genotype-diagnosis interaction were discovered in the left superior frontal gyrus (SFG). The CAPS, HAMA, and HAMD scores, as well as the genotype main effect and diagnostic SLC6A2 interaction, did not significantly correlate with each other. CONCLUSION: These findings indicate a modulatory effect that the SLC6A2 polymorphism exerts on the SPG and MCG, irrespective of PTSD diagnosis. We found evidence to suggest that the SLC6A2 genotype-diagnosis interaction on SFG may potentially contribute to PTSD pathogenesis in adults who lost their sole child.

Structural basis for ligand binding modes of CTP synthase.

Cytidine triphosphate synthase (CTPS), which comprises an ammonia ligase domain and a glutamine amidotransferase domain, catalyzes the final step of de novo CTP biosynthesis. The activity of CTPS is regulated by the binding of four nucleotides and glutamine. While glutamine serves as an ammonia donor for the ATP-dependent conversion of UTP to CTP, the fourth nucleotide GTP acts as an allosteric activator. Models have been proposed to explain the mechanisms of action at the active site of the ammonia ligase domain and the conformational changes derived by GTP binding. However, actual GTP/ATP/UTP binding modes and relevant conformational changes have not been revealed fully. Here, we report the discovery of binding modes of four nucleotides and a glutamine analog 6-diazo-5-oxo-L-norleucine in Drosophila CTPS by cryo-electron microscopy with near-atomic resolution. Interactions between GTP and surrounding residues indicate that GTP acts to coordinate reactions at both domains by directly blocking ammonia leakage and stabilizing the ammonia tunnel. Additionally, we observe the ATP-dependent UTP phosphorylation intermediate and determine interacting residues at the ammonia ligase. A noncanonical CTP binding at the ATP binding site suggests another layer of feedback inhibition. Our findings not only delineate the structure of CTPS in the presence of all substrates but also complete our understanding of the underlying mechanisms of the allosteric regulation and CTP synthesis.

Cortical morphometric vulnerability to generalised epilepsy reflects chromosome- and cell type-specific transcriptomic signatures.

AIMS: Generalised epilepsy is thought to involve distributed brain networks. However, the molecular and cellular factors that render different brain regions more vulnerable to epileptogenesis remain largely unknown. We aimed to investigate epilepsy-related morphometric similarity network (MSN) abnormalities at the macroscale level and their relationships with microscale gene expressions at the microscale level. METHODS: We compared the MSN of genetic generalised epilepsy with generalised tonic-clonic seizure patients (GGE-GTCS, n = 101) to demographically matched healthy controls (HC, n = 150). Cortical MSNs were estimated by combining seven morphometric features derived from structural magnetic resonance imaging for each individual. Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen Human Brain Atlas. RESULTS: GGE-GTCS patients exhibited decreased regional MSNs in primary motor, prefrontal and temporal regions and increases in occipital, insular and posterior cingulate cortices, when compared with the HC. These case-control neuroimaging differences were validated using split-half analyses and were not affected by medication or drug response effects. When assessing associations with gene expression, genes associated with GGE-GTCS-related MSN differences were enriched in several biological processes, including 'synapse organisation', 'neurotransmitter transport' pathways and excitatory/inhibitory neuronal cell types. Collectively, the GGE-GTCS-related cortical vulnerabilities were associated with chromosomes 4, 5, 11 and 16 and were dispersed bottom-up at the cellular, pathway and disease levels, which contributed to epileptogenesis, suggesting diverse neurobiologically relevant enrichments in GGE-GTCS. CONCLUSIONS: By bridging the gaps between transcriptional signatures and in vivo neuroimaging, we highlighted the importance of using MSN abnormalities of the human brain in GGE-GTCS patients to investigate disease-relevant genes and biological processes.

Exploration of thoracoabdominal aortic mixed reality optimisation and its clinical application value in type A aortic dissection.

OBJECTIVES: This study aimed to explore the feasibility of low-dose computed tomography (CT)-based mixed reality and its clinical role in type A aortic dissection (TAAD) operations. METHODS: Eighty-seven patients diagnosed with TAAD were prospectively enrolled and underwent thoracoabdominal aorta mixed reality. They were randomly divided into a low-dose mixed reality group, a conventional mixed reality group and a conventional thoracoabdominal aorta computed tomography angiography (CTA) group. Three-dimensional modelling, mixed reality and CT reconstruction technology were selected. The radiation dose and image quality were compared using Student's t test. Doctors with different seniorities evaluated the clinical application value of thoracoabdominal aorta mixed reality using a Likert scale. The consistency was assessed using the Cohen kappa coefficient (k). The Pearson chi-square test was used to test the correlation of perioperative index results in TAAD operations. RESULTS: Low-dose CT technology can be effectively applied to thoracoabdominal aorta mixed reality and reduces the radiation dose by approximately 59% and the operation time and auxiliary cardiopulmonary bypass time by approximately 22% and 29%, respectively. The subjective scores of doctors with different seniorities on the clinical application value of thoracoabdominal aorta mixed reality were higher than those of thoracoabdominal aorta CTA (all p > 0.05). CONCLUSIONS: Low-dose CT can be effectively used in thoracoabdominal aortic mixed reality to reduce the radiation dose while ensuring quality. Low-dose thoracoabdominal aortic mixed reality has clinical application value and can effectively reduce the operation time and auxiliary cardiopulmonary bypass time in TAAD operations. KEY POINTS: • Low-dose CT technology can ensure the mixed reality quality of the thoracoabdominal aorta with a radiation dose reduction of approximately 59%. • Compared with thoracoabdominal aorta CTA, low-dose thoracoabdominal aorta mixed reality can reduce the operation time and auxiliary cardiopulmonary bypass time by approximately 20% and 29%, respectively, in TAAD operations. • The application value of low-dose thoracoabdominal aorta mixed reality in operation scheme formulation, operation risk assessment, operation navigation and diagnosis and treatment under safe distance was greater than that of thoracoabdominal aorta CTA in TAAD.

Lower-extremity fatigue fracture detection and grading based on deep learning models of radiographs.

OBJECTIVES: To identify the feasibility of deep learning-based diagnostic models for detecting and assessing lower-extremity fatigue fracture severity on plain radiographs. METHODS: This retrospective study enrolled 1151 X-ray images (tibiofibula/foot: 682/469) of fatigue fractures and 2842 X-ray images (tibiofibula/foot: 2000/842) without abnormal presentations from two clinical centers. After labeling the lesions, images in a center (tibiofibula/foot: 2539/1180) were allocated at 7:1:2 for model construction, and the remaining images from another center (tibiofibula/foot: 143/131) for external validation. A ResNet-50 and a triplet branch network were adopted to construct diagnostic models for detecting and grading. The performances of detection models were evaluated with sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), while grading models were evaluated with accuracy by confusion matrix. Visual estimations by radiologists were performed for comparisons with models. RESULTS: For the detection model on tibiofibula, a sensitivity of 95.4%/85.5%, a specificity of 80.1%/77.0%, and an AUC of 0.965/0.877 were achieved in the internal testing/external validation set. The detection model on foot reached a sensitivity of 96.4%/90.8%, a specificity of 76.0%/66.7%, and an AUC of 0.947/0.911. The detection models showed superior performance to the junior radiologist, comparable to the intermediate or senior radiologist. The overall accuracy of the diagnostic model was 78.5%/62.9% for tibiofibula and 74.7%/61.1% for foot in the internal testing/external validation set. CONCLUSIONS: The deep learning-based models could be applied to the radiological diagnosis of plain radiographs for assisting in the detection and grading of fatigue fractures on tibiofibula and foot. KEY POINTS: • Fatigue fractures on radiographs are relatively difficult to detect, and apt to be misdiagnosed. • Detection and grading models based on deep learning were constructed on a large cohort of radiographs with lower-extremity fatigue fractures. • The detection model with high sensitivity would help to reduce the misdiagnosis of lower-extremity fatigue fractures.

Coordinatized lesion location analysis empowering ROI-based radiomics diagnosis on brain gliomas.

OBJECTIVES: To assess the value of coordinatized lesion location analysis (CLLA), in empowering ROI-based imaging diagnosis of gliomas by improving accuracy and generalization performances. METHODS: In this retrospective study, pre-operative contrasted T1-weighted and T2-weighted MR images were obtained from patients with gliomas from three centers: Jinling Hospital, Tiantan Hospital, and the Cancer Genome Atlas Program. Based on CLLA and ROI-based radiomic analyses, a fusion location-radiomics model was constructed to predict tumor grades, isocitrate dehydrogenase (IDH) status, and overall survival (OS). An inter-site cross-validation strategy was used for assessing the performances of the fusion model on accuracy and generalization with the value of area under the curve (AUC) and delta accuracy (ACC) (ACCtesting-ACCtraining). Comparisons of diagnostic performances were performed between the fusion model and the other two models constructed with location and radiomics analysis using DeLong's test and Wilcoxon signed ranks test. RESULTS: A total of 679 patients (mean age, 50 years ± 14 [standard deviation]; 388 men) were enrolled. Based on tumor location probabilistic maps, fusion location-radiomics models (averaged AUC values of grade/IDH/OS: 0.756/0.748/0.768) showed the highest accuracy in contrast to radiomics models (0.731/0.686/0.716) and location models (0.706/0.712/0.740). Notably, fusion models ([median Delta ACC: - 0.125, interquartile range: 0.130]) demonstrated improved generalization than that of radiomics model ([- 0.200, 0.195], p = 0.018). CONCLUSIONS: CLLA could empower ROI-based radiomics diagnosis of gliomas by improving the accuracy and generalization of the models. CLINICAL RELEVANCE STATEMENT: This study proposed a coordinatized lesion location analysis for glioma diagnosis, which could improve the performances of the conventional ROI-based radiomics model in accuracy and generalization. KEY POINTS: • Using coordinatized lesion location analysis, we mapped anatomic distribution patterns of gliomas with specific pathological and clinical features and constructed glioma prediction models. • We integrated coordinatized lesion location analysis into ROI-based analysis of radiomics to propose new fusion location-radiomics models. • Fusion location-radiomics models, with the advantages of being less influenced by variabilities, improved accuracy, and generalization performances of ROI-based radiomics models on predicting the diagnosis of gliomas.

Immediate visual reproduction negatively correlates with brain entropy of parahippocampal gyrus and inferior occipital gyrus in bipolar II disorder adolescents.

BACKGROUND: Brain entropy reveals complexity and irregularity of brain, and it has been proven to reflect brain complexity alteration in disease states. Previous studies found that bipolar disorder adolescents showed cognitive impairment. The relationship between complexity of brain neural activity and cognition of bipolar II disorder (BD-II) adolescents remains unclear. METHODS: Nineteen BD-II patients (14.63 ±1.57 years old) and seventeen age-gender matched healthy controls (HCs) (14.18 ± 1.51 years old) were enlisted. Entropy values of all voxels of the brain in resting-state functional MRI data were calculated and differences of them between BD-II and HC groups were evaluated. After that, correlation analyses were performed between entropy values of brain regions showing significant entropy differences and clinical indices in BD-II adolescents. RESULTS: Significant differences were found in scores of immediate visual reproduction subtest (VR-I, p = 0.003) and Stroop color-word test (SCWT-1, p = 0.015; SCWT-2, p = 0.004; SCWT-3, p = 0.003) between the two groups. Compared with HCs, BD-II adolescents showed significant increased brain entropy in right parahippocampal gyrus and right inferior occipital gyrus. Besides, significant negative correlations between brain entropy values of right parahippocampal gyrus, right inferior occipital gyrus and immediate visual reproduction subtest scores were observed in BD-II adolescents. CONCLUSIONS: The findings of the present study suggested that the disrupted function of corticolimbic system is related with cognitive abnormality of BD-II adolescents. And from the perspective temporal dynamics of brain system, the current study, brain entropy may provide available evidences for understanding the underlying neural mechanism in BD-II adolescents.

Enhanced anti-glioma efficacy of biodegradable periodic mesoporous organosilica nanoparticles through target delivery of chemotherapeutics.

Glioma is the most common malignant tumor of the brain and enhancing the efficacy of chemotherapy in glioma is critical for improving patients' prognosis. In this study, a glioma-targeting drug delivery system is constructed using biodegradable periodic mesoporous organosilica nanoparticles (PMO) that are modified with lactoferrin (Lf) ligands. The obtained PMO is doped with thioether groups and can be degraded in the high concentration of glutathione in tumor cells. The surface area and pore volume of PMO are 772 cm2/g and 0.98 cm3/g, respectively and the loading capacity of doxorubicin (Dox) is as high as 20%. The results of the confocal laser scanning microscope show that the uptake of PMO-Lf@Dox by C6 cells is higher than PMO@Dox. The quantitative analysis of the flow cytometer further demonstrates that more PMO-Lf@Dox enter C6 cells, indicating that the modification of lactoferrin can significantly increase the uptake of C6 cells. Finally, the therapeutic efficacy results show that Lf-modified PMO enhances the inhibitory effect of Dox on C6 cells when incubated for 24 h and 72 h. In summary, this lactoferrin receptor-mediated PMO drug carrier with biodegradability in glutathione in tumor cells can be used to enhance drug delivery into glioma without long-term accumulation in vivo. In this study, a glioma-targeting drug delivery system is constructed using periodic mesoporous organosilica nanoparticles (PMO) that modified with lactoferrin (Lf) ligands. This lactoferrin receptor-mediated PMO drug carrier can be used to enhance drug delivery into brain glioma.

MRI features of neuronal intranuclear inclusion disease, combining visual and quantitative imaging investigations.

OBJECTIVE: To observe the radiological characteristics of Neuronal Intranuclear Inclusion Disease (NIID) on lesion locations and diffusion property using quantitative imaging analysis. METHODS: Visual inspection and quantitative analyses were performed on MRI data from 31 retrospectively included patients with NIID. Frequency heatmaps of lesion locations on T2WI and DWI were generated using voxel-wise analysis. Gray matter volume (GMV), white matter volume (WMV) and diffusion property of apparent diffusion coefficient (ADC) values of patients were voxel-wisely compared with healthy controls. Moreover, the ADC values within the DWI-detected lesion were compared with those within the adjacent cortical gray matter and white matter. Voxel-based lesion symptom mapping (VLSM) techniques, were used to determine the relationship between DWI lesion location and disease durations. RESULTS: By visual inspection on the imaging findings, we proposed an "cockscomb flower sign" for describing the radiological feature of DWI hyperintensity within the corticomedullary junction. A "T2WI-DWI mismatch of spatial distribution" pattern was also revealed with visual inspection and frequency heatmaps, for describing the feature of a wider lesion distribution covering white matter shown on T2WI than that on DWI. Voxel-based morphometry comparison revealed that wildly reduced GMV and WMV, both the lesion areas detected by DWI and T2WI demonstrated ADC increase in patients. Furthermore, the ADC values within the DWI-detected lesion were intermediate between the adjacent cortex and the deep white matter with highest ADC. VLSM analysis revealed that frontal lobe, parietal lobe and internal capsule damage were associated with higher NIID durations. CONCLUSION: NIID features with "cockscomb flower-like" DWI hyperintensity in area of corticomedullary junction, based on a "T2WI-DWI mismatch of spatial distribution" of lesion locations. The pathological substrate of corticomedullary junction hyperintensity on DWI, can not be explained as diffusion restriction. These typical radiological features of brain MRI would be helpful for diagnosis of NIID.

18F-Alfatide II for the evaluation of axillary lymph nodes in breast cancer patients: comparison with 18F-FDG.

PURPOSE: 18F-Alfatide II has been translated into clinical use and been proven to have good performance in identifying breast cancer. In this study, we investigated 18F-Alfatide II for evaluation of axillary lymph nodes (ALN) in breast cancer patients and compared the performance with 18F-FDG. METHODS: A total of 44 female patients with clinically suspected breast cancer were enrolled and underwent 18F-Alfatide II and 18F-FDG PET/CT within a week. Tracer uptakes in ALN were evaluated by visual analysis, semi-quantitative analysis with maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), and SUVmax ratio of target/non-target (T/NT). RESULTS: Among 44 patients, 37 patients were pathologically diagnosed with breast cancer with metastatic (17 cases) or non-metastatic (20 cases) ALN. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of visual analysis were 70.6%, 90%, 81.1%, 85.7%, and 78.3% for 18F-Alfatide II, 64.7%, 90%, 78.4%, 84.6%, and 75% for 18F-FDG, respectively. By combining 18F-Alfatide II and 18F-FDG, the sensitivity significantly increased to 82.4%, the specificity was 85%, the accuracy increased to 83.8%, the PPV was 82.4%, and the NPV significantly increased to 85.0%. Three cases of luminal B subtype were false negative for both 18F-Alfatide II and 18F-FDG. The other 2 false negative cases of 18F-Alfatide II were triple-negative subtype and 3 false negative cases of 18F-FDG were luminal B subtype too. The AUCs of three semi-quantitative parameters (SUVmax, SUVmean, T/NT) for 18F-Alfatide II were between 0.8 and 0.9, whereas those for 18F-FDG were more than 0.9. 18F-Alfatide II T/NT had the highest Youden index (76.5%), specificity (100%), accuracy (89.2%), and PPV (100%) among these semi-quantitative parameters. 18F-Alfatide II uptake as well as 18F-FDG uptake in metastatic axillary lymph nodes (MALN) was significantly higher than that in benign axillary lymph nodes (BALN). Both 18F-Alfatide II and 18F-FDG did not show difference in primary tumor uptake irrespective of ALN status. CONCLUSION: 18F-Alfatide II can be used in breast cancer patients to detect metastatic ALN, however, like 18F-FDG, with high specificity but relatively low sensitivity. The combination of 18F-Alfatide II and 18F-FDG can significantly improve sensitivity and NPV. 18F-Alfatide II T/NT may serve as the most important semi-quantitative parameter to evaluate ALN.

Combined 18F-FDG and 18F-Alfatide II PET May Predict Luminal B (HER2 Negative) Subtype and Nonluminal Subtype of Invasive Breast Cancer.

Noninvasive PET molecular imaging using radiopharmaceuticals is important to classify breast cancer in the clinic. The aim of this study was to investigate the combination of 18F-FDG and 18F-Alfatide II for predicting molecular subtypes of invasive breast cancer. Forty-four female patients with clinically suspected breast cancer were recruited and underwent 18F-FDG and 18F-Alfatide II PET/CT within a week. Tracer uptake in breast lesions was assessed using the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), and SUVmax ratio of 18F-FDG to 18F-Alfatide II (FAR). Invasive breast cancer lesions were further classified as luminal A subtype, luminal B subtype, human epidermal growth factor receptor-2 (HER2) overexpressing subtype, and triple negative subtype according to the expression of the estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki-67. Among 44 patients, 35 patients were pathologically diagnosed with invasive breast cancer. The SUVmax and SUVmean of 18F-FDG were significantly higher in the ER-negative group than those in the ER-positive group, as well as in the PR-negative group than those in the PR-positive group. However, the SUVmax and SUVmean of 18F-Alfatide II were higher in the ER-positive group and the PR-positive group. By combining 18F-FDG and 18F-Alfatide II, the FAR was lower in the ER-positive group and the PR-positive group. The HER2 overexpressing subtype showed the highest SUVmax and SUVmean for 18F-FDG while the luminal B (HER2 negative) subtype revealed the lowest values. The luminal B (HER2 negative) subtype showed the highest 18F-Alfatide II SUVmax, while the triple negative subtype showed the lowest 18F-Alfatide II SUVmax. The FAR was the lowest in the luminal B (HER2 negative) subtype and much higher in the HER2 overexpressing and triple negative subtypes. FAR less than 1 predicted the luminal B (HER2 negative) subtype with high specificity (93.1%) and NPV (90%). FAR greater than 3 predicted the HER2 overexpressing subtype and triple negative subtype (namely, the nonluminal subtype) with very high specificity (100%) and PPV (100%). In summary, FAR, the combined PET parameter of 18F-FDG and 18F-Alfatide II, can be used to predict molecular subtypes of invasive breast cancer, especially for the luminal B (HER2 negative) subtype and the nonluminal subtype.

Antimicrobial Lignin-Based Polyurethane/Ag Composite Foams for Improving Wound Healing.

Antimicrobial materials are an urgent need for modern wound care in the clinic. Although traditional polyurethane foams have proven to be clinically valuable for wound treatment, their petroleum-originated preparation and bioinert nature have restricted their efficacy in biomedical applications. Here, we propose a simple one-step foaming method to prepare lignin-based polyurethane foams (LPUFs) in which fully biobased polyether polyols partially replace traditional petroleum-based raw materials. The trace amount of phenolic hydroxyl groups (about 4 mmol) in liquefied lignin acts as a direct reducing agent and capping agent to silver ions (less than 0.3 mmol), in situ forming silver nanoparticles (Ag NPs) within the LPUF skeleton. This newly proposed lignin polyurethane/Ag composite foam (named as Ag NP-LPUF) shows improved mechanical, thermal, and antibacterial properties. It is worth mentioning that the Ag NP-LPUF exhibits more than 99% antibacterial rate against Escherichia coli within 1 h and Staphylococcus aureus within 4 h. Evaluations in mice indicate that the antimicrobial composite foams can effectively promote wound healing of full-thickness skin defects. As a proof of concept, this antibacterial and biodegradable foam exhibits significant potential for clinical translation in wound care dressings.

Review of net water uptake in the management of acute ischemic stroke.

CT densitometry-based methods to directly quantify net water uptake in ischemic brain tissue have been increasingly applied recently. There is potential for net water uptake to be used as an imaging biomarker for the pathophysiology of infarcted lesions. This review is aimed at summarizing the potential and current status of the application of net water uptake as a biomarker in the management of ischemic stroke and future directions in this context. Specifically, we provide a brief overview of the principle and different methods of net water uptake measurement, followed by a discussion of the role of net water uptake in predicting malignant brain edema and hemorrhagic transformation, evaluating lesion age, and predicting the efficacy of reperfusion therapy and long-term clinical prognosis. Artificial intelligence will help address the lack of automation and standardization in the measurement of net water absorption. Further validation of net water uptake in a prospective multicenter setting is necessary. KEY POINTS: • NWU can be used as a quantitative imaging biomarker for developing malignant brain edema in anterior and posterior circulation strokes. • The difference in NWU in edema arrest or reversibility suggests that rapid and successful revascularization can influence the progression of ischemic edema. • NWU can be used to predict the age of a lesion, with predictive power comparable to that of DWI/FLAIR mismatch.

Automated quantitative lesion water uptake in acute stroke is a predictor of malignant cerebral edema.

OBJECTIVES: Net water uptake (NWU) has been shown to have a linear relationship with brain edema. Based on an automated-Alberta Stroke Program Early Computed Tomography Score (ASPECTS) technique, we automatically derived NWU from baseline multimodal computed tomography (CT), namely ASPECTS-NWU. We aimed to determine if ASPECTS-NWU can predict the development of malignant cerebral edema (MCE). METHODS: One hundred and forty-six patients with large-vessel occlusion were retrospectively enrolled. Quantitative NWU based on automated-ASPECTS was measured both on nonenhanced CT (NECT) and CT angiography (CTA), namely NECT-ASPECT-NWU and CTA-ASPECTS-NWU. The correlation between ASPECTS-NWU and cerebral edema (CED) grades was calculated using Spearman rank correlation. Univariate logistic regression was used to assess the effect of radiological and clinical features on MCE, and a multivariable model with significant factors from the univariate regression analysis was built. Receiver operating characteristic (ROC) was obtained and area under curve (AUC) was compared. RESULTS: CTA-ASPECTS-NWU had a moderate positive correlation with CED grades (r = 0.62; 95% confidence interval [CI], 0.51-0.71; p < 0.001). The CTA-ASPECTS-NWU performed better than the NECT-ASPECTS-NWU with AUC: 0.88 vs. 0.71 (p < 0.001). Multivariable logistic regression model integrating CTA-ASPECTS-NWU, collateral score, and age showed the CTA-ASPECTS-NWU was an independent predictor of MCE with an AUC of 0.94 (95% CI: 0.90-0.98; p < 0.001). CONCLUSIONS: This study demonstrates that ASPECTS-NWU is a quantitative predictor of MCE after large-vessel occlusion of the middle cerebral artery territory. The multivariable logistic regression model may enhance the identification of patients with MCE needing anti-edematous treatment. KEY POINTS: • The automated-ASPECTS technique can automatically detect the affected regions with early ischemic changes and NWU could be manually calculated. • The CTA-ASPECTS-NWU performs better than the NECT-ASPECTS-NWU on predicting the development of MCE. • The multivariable logistic regression model may enhance the identification of patients with MCE needing anti-edematous treatment.