The enhanced connectivity between the frontoparietal, somatomotor network and thalamus as the most significant network changes of chronic low back pain.

The prolonged duration of chronic low back pain (cLBP) inevitably leads to changes in the cognitive, attentional, sensory and emotional processing brain regions. Currently, it remains unclear how these alterations are manifested in the interplay between brain functional and structural networks. This study aimed to predict the Oswestry Disability Index (ODI) in cLBP patients using multimodal brain magnetic resonance imaging (MRI) data and identified the most significant features within the multimodal networks to aid in distinguishing patients from healthy controls (HCs). We constructed dynamic functional connectivity (dFC) and structural connectivity (SC) networks for all participants (n = 112) and employed the Connectome-based Predictive Modeling (CPM) approach to predict ODI scores, utilizing various feature selection thresholds to identify the most significant network change features in dFC and SC outcomes. Subsequently, we utilized these significant features for optimal classifier selection and the integration of multimodal features. The results revealed enhanced connectivity among the frontoparietal network (FPN), somatomotor network (SMN) and thalamus in cLBP patients compared to HCs. The thalamus transmits pain-related sensations and emotions to the cortical areas through the dorsolateral prefrontal cortex (dlPFC) and primary somatosensory cortex (SI), leading to alterations in whole-brain network functionality and structure. Regarding the model selection for the classifier, we found that Support Vector Machine (SVM) best fit these significant network features. The combined model based on dFC and SC features significantly improved classification performance between cLBP patients and HCs (AUC=0.9772). Finally, the results from an external validation set support our hypotheses and provide insights into the potential applicability of the model in real-world scenarios. Our discovery of enhanced connectivity between the thalamus and both the dlPFC (FPN) and SI (SMN) provides a valuable supplement to prior research on cLBP.

Sex differences in functional connectivity and the predictive role of the connectome-based predictive model in Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive decline. Sex differences in the progression of AD exist, but the neural mechanisms are not well understood. The purpose of the current study was to explore sex differences in brain functional connectivity (FC) at different stages of AD and their predictive ability on Montreal Cognitive Assessment (MoCA) scores using connectome-based predictive modeling (CPM). Resting-state functional magnetic resonance imaging was collected from 81 AD patients (44 females), 78 amnestic mild cognitive impairment patients (44 females), and 92 healthy controls (50 females). The FC analysis was conducted and the interaction effect between sex and group was investigated using two-factor variance analysis. The CPM was used to predict MoCA scores. There were sex-by-group interaction effects on FC between the left dorsolateral superior frontal gyrus and left middle temporal gyrus, left precuneus and right calcarine fissure surrounding cortex, left precuneus and left middle occipital gyrus, left middle temporal gyrus and left precentral gyrus, and between the left middle temporal gyrus and right cuneus. In the CPM, the positive network predictive model significantly predicted MoCA scores in both males and females. There were significant sex-by-group interaction effects on FC between the left precuneus and left middle occipital gyrus, and between the left middle temporal gyrus and right cuneus could predict MoCA scores in female patients. Our results suggest that there are sex differences in FC at different stages of AD. The sex-specific FC can further predict MoCA scores at individual level.

The protective effect of vitamin D supplementation as adjunctive therapy to antidepressants on brain structural and functional connectivity of patients with major depressive disorder: a randomized controlled trial.

BACKGROUND: Growing evidence points to the pivotal role of vitamin D in the pathophysiology and treatment of major depressive disorder (MDD). However, there is a paucity of longitudinal research investigating the effects of vitamin D supplementation on the brain of MDD patients. METHODS: We conducted a double-blind randomized controlled trial in 46 MDD patients, who were randomly allocated into either VD (antidepressant medication + vitamin D supplementation) or NVD (antidepressant medication + placebos) groups. Data from diffusion tensor imaging, resting-state functional MRI, serum vitamin D concentration, and clinical symptoms were obtained at baseline and after an average of 7 months of intervention. RESULTS: Both VD and NVD groups showed significant improvement in depression and anxiety symptoms but with no significant differences between the two groups. However, a greater increase in serum vitamin D concentration was found to be associated with greater improvement in depression and anxiety symptoms in VD group. More importantly, neuroimaging data demonstrated disrupted white matter integrity of right inferior fronto-occipital fasciculus along with decreased functional connectivity between right frontoparietal and medial visual networks after intervention in NVD group, but no changes in VD group. CONCLUSIONS: These findings suggest that vitamin D supplementation as adjunctive therapy to antidepressants may not only contribute to improvement in clinical symptoms but also help preserve brain structural and functional connectivity in MDD patients.

Cardiac T1ρ Mapping Values Affected by Age and Sex in a Healthy Chinese Cohort.

BACKGROUND: To facilitate the clinical use of cardiac T1ρ, it is important to understand the impact of age and sex on T1ρ values of the myocardium. PURPOSE: To investigate the impact of age and gender on myocardial T1ρ values. STUDY TYPE: Cross-sectional. POPULATION: Two hundred ten healthy Han Chinese volunteers without cardiovascular risk factors (85 males, mean age 34.4 ± 12.5 years; 125 females, mean age 37.9 ± 14.8 years). FIELD STRENGTH/SEQUENCE: 1.5 T; T1ρ-prepared steady-state free precession (T1ρ mapping) sequence. ASSESSMENT: Basal, mid, and apical short-axis left ventricular T1ρ maps were acquired. T1ρ maps acquired with spin-lock frequencies of 5 and 400 Hz were subtracted to create a myocardial fibrosis index (mFI) map. T1ρ and mFI values across different age decades, sex, and slice locations were compared. STATISTICAL TESTS: Shapiro-Wilk test, Student's t test, Mann-Whitney U test, linear regression analysis, one-way analysis of variance and intraclass correlation coefficient. SIGNIFICANCE: P value <0.05. RESULTS: Women had significantly higher T1ρ and mFI values than men (50.3 ± 2.0 msec vs. 47.7 ± 2.4 msec and 4.7 ± 1.0 msec vs. 4.3 ± 1.1 msec, respectively). Additionally, in males and females combined, there was a significant positive but weak correlation between T1ρ values and age (r = 0.27), while no correlation was observed between the mFI values and age (P = 0.969). DATA CONCLUSION: We report potential reference values for cardiac T1ρ by sex, age distribution, and slice location in a Chinese population. T1ρ was significantly correlated with age and sex, while mFI was only associated with sex. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

The Association of Epicardial Adipose Tissue Volume and Atrial Fibrillation in Patients With Hypertrophic Cardiomyopathy: As Assessed by Cardiac MR.

BACKGROUND: Epicardial adipose tissue (EAT) is a metabolically active visceral fat linked to cardiovascular disease. Prior studies demonstrated the predictive value of EAT volume (EATV) in atrial fibrillation (AF) among hypertrophic obstructive cardiomyopathy patients. PURPOSE: To investigate the association between EATV and AF in hypertrophic cardiomyopathy (HCM). STUDY TYPE: Retrospective. POPULATION: Two hundred and twenty-four HCM patients (including 79 patients with AF and 145 patients without AF, 154 men) and 80 healthy controls (54 men). FIELD STRENGTH/SEQUENCE: 3.0 T scanner; balanced steady-state free precession (SSFP) cine sequence, gradient echo. ASSESSMENT: EAT thickness was assessed in the 4-chamber and basal short-axis planes. EAT volume was calculated by outlining the epicardial border and visceral pericardium layer on short-axis cine images. STATISTICAL TESTS: Shapiro-Wilk test, Student's t test or the Mann-Whitney U test, chi-square test or Fisher's exact test, Multivariate linear regression analyses, Multivariable binary logistic regression analysis. Intraclass correlation coefficient. Significance was determined at P < 0.05. RESULTS: EATV and EAT volume index (EATVI) were significantly greater in HCM patients with AF than those without AF (126.6 ± 25.9 mL vs. 90.5 ± 24.5 mL, and 73.0 ± 15.9 mL/m2 vs. 51.3 ± 13.4 mL/m2). EATVI was associated with AF in multivariable linear regression analysis among HCM patients (ß = 0.62). Multivariable logistic regression analysis revealed that compared to other indicators, the area under curve (AUC) of EATVI was 0.86 (cut-off, 53.9 mL/m2, 95% CI, 0.80-0.89), provided a better performance, with the sensitivity of 96.2% and specificity of 58.6%. The combined model exhibited superior association with AF presence compared to the clinical model (AUC 0.96 vs. 0.76) and the imaging model (AUC 0.96 vs. 0.93). DATA CONCLUSION: EATVI was associated with AF. EATVI was significantly correlated with incident AF, and provided a better performance in HCM patients compared to other indicators. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Value of fractional-order calculus (FROC) model diffusion-weighted imaging combined with simultaneous multi-slice (SMS) acceleration technology for evaluating benign and malignant breast lesions.

BACKGROUND: This study explores the diagnostic value of combining fractional-order calculus (FROC) diffusion-weighted model with simultaneous multi-slice (SMS) acceleration technology in distinguishing benign and malignant breast lesions. METHODS: 178 lesions (73 benign, 105 malignant) underwent magnetic resonance imaging with diffusion-weighted imaging using multiple b-values (14 b-values, highest 3000 s/mm2). Independent samples t-test or Mann-Whitney U test compared image quality scores, FROC model parameters (D,, ), and ADC values between two groups. Multivariate logistic regression analysis identified independent variables and constructed nomograms. Model discrimination ability was assessed with receiver operating characteristic (ROC) curve and calibration chart. Spearman correlation analysis and Bland-Altman plot evaluated parameter correlation and consistency. RESULTS: Malignant lesions exhibited lower D, and ADC values than benign lesions (P < 0.05), with higher values (P < 0.05). In SSEPI-DWI and SMS-SSEPI-DWI sequences, the AUC and diagnostic accuracy of D value are maximal, with D value demonstrating the highest diagnostic sensitivity, while value exhibits the highest specificity. The D and combined model had the highest AUC and accuracy. D and ADC values showed high correlation between sequences, and moderate. Bland-Altman plot demonstrated unbiased parameter values. CONCLUSION: SMS-SSEPI-DWI FROC model provides good image quality and lesion characteristic values within an acceptable time. It shows consistent diagnostic performance compared to SSEPI-DWI, particularly in D and values, and significantly reduces scanning time.

Hoffmann's sign in cervical spondylotic myelopathy patients: pathological insights from neuroimaging.

OBJECTIVE: Hoffmann's sign testing is a commonly used physical examination in clinical practice for patients with cervical spondylotic myelopathy (CSM). However, the pathophysiological mechanisms underlying its occurrence and development have not been thoroughly investigated. Therefore, the present study aimed to explore whether a positive Hoffmann's sign (PHS) in CSM patients is associated with spinal cord and brain remodeling and to identify potential neuroimaging biomarkers with diagnostic value. METHODS: Seventy-six patients with CSM and 40 sex- and age-matched healthy controls (HCs) underwent multimodal MRI. Based on the results of the Hoffmann's sign examination, patients were divided into two groups: those with a PHS (n = 38) and those with a negative Hoffmann's sign (NHS; n = 38). Quantification of spinal cord and brain structural and functional parameters of the participants was performed using various methods, including functional connectivity analysis, voxel-based morphometry, and atlas-based analysis based on functional MRI and structural MRI data. Furthermore, this study conducted a correlation analysis between neuroimaging metrics and neurological function and utilized a support vector machine (SVM) algorithm for the classification of PHS and NHS. RESULTS: In comparison with the NHS and HC groups, PHS patients exhibited significant reductions in the cross-sectional area and fractional anisotropy (FA) of the lateral corticospinal tract (CST), reticulospinal tract (RST), and fasciculus cuneatus, concomitant with bilateral reductions in the volume of the lateral pallidum. The functional connectivity analysis indicated a reduction in functional connectivity between the left lateral pallidum and the right angular gyrus in the PHS group. The correlation analysis indicated a significant positive association between the CST and RST FA and the volume of the left lateral pallidum in PHS patients. Furthermore, all three variables exhibited a positive correlation with the patients' motor function. Finally, using multimodal neuroimaging metrics in conjunction with the SVM algorithm, PHS and NHS were classified with an accuracy rate of 85.53%. CONCLUSIONS: This research revealed a correlation between structural damage to the pallidum and RST and the presence of Hoffmann's sign as well as the motor function in patients with CSM. Features based on neuroimaging indicators have the potential to serve as biomarkers for assessing the extent of neuronal damage in CSM patients.

Added Value of Frequency of Imaging Markers for Prediction of Outcome After Intracerebral Hemorrhage: A Secondary Analysis of Existing Data.

BACKGROUND: Frequency of imaging markers (FIM) has been identified as an independent predictor of hematoma expansion in patients with intracerebral hemorrhage (ICH), but its impact on clinical outcome of ICH is yet to be determined. The aim of the present study was to investigate this association. METHODS: This study was a secondary analysis of our prior research. The data for this study were derived from six retrospective cohorts of ICH from January 2018 to August 2022. All consecutive study participants were examined within 6 h of stroke onset on neuroimaging. FIM was defined as the ratio of the number of imaging markers on noncontrast head tomography (i.e., hypodensities, blend sign, and island sign) to onset-to-neuroimaging time. The primary poor outcome was defined as a modified Rankin Scale score of 3-6 at 3 months. RESULTS: A total of 1253 patients with ICH were included for final analysis. Among those with available follow-up results, 713 (56.90%) exhibited a poor neurologic outcome at 3 months. In a univariate analysis, FIM was associated with poor prognosis (odds ratio 4.36; 95% confidence interval 3.31-5.74; p < 0.001). After adjustment for age, Glasgow Coma Scale score, systolic blood pressure, hematoma volume, and intraventricular hemorrhage, FIM was still an independent predictor of worse prognosis (odds ratio 3.26; 95% confidence interval 2.37-4.48; p < 0.001). Based on receiver operating characteristic curve analysis, a cutoff value of 0.28 for FIM was associated with 0.69 sensitivity, 0.66 specificity, 0.73 positive predictive value, 0.62 negative predictive value, and 0.71 area under the curve for the diagnosis of poor outcome. CONCLUSIONS: The metric of FIM is associated with 3-month poor outcome after ICH. The novel indicator that helps identify patients who are likely within the 6-h time window at risk for worse outcome would be a valuable addition to the clinical management of ICH.

The interplay between extracellular and intracellular auxin signaling in plants.

The phytohormone auxin exerts control over remarkable developmental processes in plants. It moves from cell to cell, resulting in the creation of both extracellular auxin and intracellular auxin, which are recognized by distinct auxin receptors. These two auxin signaling systems govern different auxin responses while working together to regulate plant development. In this review, we outline the latest research advancements in unraveling these auxin signaling pathways, encompassing auxin perception and signaling transductions. We emphasize the interaction between extracellular auxin and intracellular auxin, which contributes to the intricate role of auxin in plant development.

The Application of Intraoperative Ultrasound with Burr Hole Probe in Minimally Invasive Diagnosis and Treatment in Neurosurgery.

OBJECTIVE: To summarize the preliminary application experience of intraoperative ultrasound with burr hole probe in minimally invasive neurosurgery and to explore its application value. METHODS: Thirty-one patients who underwent intraoperative ultrasound guided puncture with burr hole probe in our center from August 2018 to May 2024 were collected, including 16 cases of ventriculoperitoneal shunt operation, 6 cases of assisted stereotactic needle biopsy, 3 cases of intracranial pressure probe implantation in lateral ventricle, 3 cases of brain abscess puncture for external drainage, and 3 cases of intracranial cyst puncture and peritoneal drainage. During the procedures, the burr hole probe was used to locate the intracranial targets and guide the puncture. The postoperative computed tomography (CT) scans or combined postoperative pathological results could verify the accuracy of puncture. In addition, the intervention effect and recovery status of patients were also recorded. RESULTS: The intraoperative ultrasound with burr hole probe could clearly display all the purposed targets and accurately guide the puncture procedures in all cases. All patients achieved satisfactory diagnostic and therapeutic results without new neurological dysfunction and serious complications. CONCLUSIONS: The intraoperative ultrasound with burr hole probe is an effective device for demonstrating intracranial structures. It not only enables minimally invasive and precise diagnosis or treatment of many neurosurgical diseases, but also is simple and safe to operate, which has important promotional value in the neurosurgery.

Homogeneous to heterogeneous redox mediator enhancing ferrate(VI) oxidation of sulfamethoxazole: Role of ferrate(VI) activation and electron shuttle.

Ferrate (Fe(VI)) is a promising oxidant for water remediation, yet it has limited reactivity towards certain recalcitrant but important emerging contaminants, such as sulfamethoxazole. Here, this study demonstrates that nitroxide redox mediators, specifically 9-azabicyclo[3.3.1]nonasne N-oxyl (ABNO), can catalyze Fe(VI) reaction with sulfamethoxazole by functioning both as Fe(VI) activator and electron shuttle. The underlying mechanism is explained as: (i) Fe(VI) activation: a series of one-electron transfers between Fe(VI) and ABNO produces highly reactive Fe(V)/Fe(IV) and ABNO+; (ii) electron shuttle: the newly formed active ABNO+ reacts with the sulfamethoxazole, contributing to its removal. Concurrently, ABNOH is generated and subsequently converted back to ABNO by reactive species, thereby completing the redox cycle. The as-developed heterogeneous redox mediator, ABNO@SiO2, retained its catalytic properties and effectively catalyzed Fe(VI) to remove sulfamethoxazole at environmentally relevant pH levels.

Based on Gadolinium Ethoxybenzyl DTPA-Enhanced MRI: Diagnostic Performance of the Category-Modified LR-5 Criteria in Patients At Risk for Hepatocellular Carcinoma.

Introduction: We aimed to modify the LR-5 strategy to improve the diagnostic sensitivity for hepatocellular carcinoma (HCC) in high-risk patients while maintaining specificity. Methods: This study retrospectively analyzed 412 patients with 445 liver observations who underwent preoperative gadolinium ethoxybenzyl DTPA (GD-EOB-DTPA)-enhanced MRI followed by surgical procedures or biopsies. All observations were classified according to LI-RADS v2018, and the classifications were adjusted by modifying major features (MF)(substituting threshold growth with a more HCC-specific ancillary features (AF): presence of blood products within the mass, arterial phase hyperenhancement (APHE) was interpreted with hypointensity on precontrast imaging- isointensity in arterial phase (AP) and extending washout to transitional phase (TP)(2 min)). The specificity, sensitivity, and positive predictive value (PPV) were assessed to compare LR-5 (definitely HCC) diagnostic efficacy between LI-RADS version 2018 and modified LI-RADS. Results: Apart from nonenhancing "capsule", the interreader agreement of MFs and HCC-specific AFs between the two readers reached substantial or excellent ranges (κ values ranging from 0.631 to 0.911). According to LI-5 v2018, the specificity, sensitivity and PPV of HCC were 90.74%, 82.35%, and 98.17%, respectively. Based on a more HCC-specific AF, signal intensity in AP and TP (2 min), the sensitivity of the three modified strategies were 86.19%, 93.09%, 96.67% (P < .05)), while maintaining high specificity and PPV rates at 88.89% and 98.25% (P > .05) Conclusion: Further investigation into the efficacy of threshold growth as a MF is warranted. By utilizing GD-EOB-DTPA-enhanced MRI, enhancing the sensitivity of the modified LR-5 category may be achieved without compromising specificity and PPV in diagnosing HCC among high-risk patients.

Network Localization of State and Trait of Auditory Verbal Hallucinations in Schizophrenia.

BACKGROUND AND HYPOTHESIS: Neuroimaging studies investigating the neural substrates of auditory verbal hallucinations (AVH) in schizophrenia have yielded mixed results, which may be reconciled by network localization. We sought to examine whether AVH-state and AVH-trait brain alterations in schizophrenia localize to common or distinct networks. STUDY DESIGN: We initially identified AVH-state and AVH-trait brain alterations in schizophrenia reported in 48 previous studies. By integrating these affected brain locations with large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we then leveraged novel functional connectivity network mapping to construct AVH-state and AVH-trait dysfunctional networks. STUDY RESULTS: The neuroanatomically heterogeneous AVH-state and AVH-trait brain alterations in schizophrenia localized to distinct and specific networks. The AVH-state dysfunctional network comprised a broadly distributed set of brain regions mainly involving the auditory, salience, basal ganglia, language, and sensorimotor networks. Contrastingly, the AVH-trait dysfunctional network manifested as a pattern of circumscribed brain regions principally implicating the caudate and inferior frontal gyrus. Additionally, the AVH-state dysfunctional network aligned with the neuromodulation targets for effective treatment of AVH, indicating possible clinical relevance. CONCLUSIONS: Apart from unifying the seemingly irreproducible neuroimaging results across prior AVH studies, our findings suggest different neural mechanisms underlying AVH state and trait in schizophrenia from a network perspective and more broadly may inform future neuromodulation treatment for AVH.

Changes in subclinical cardiac abnormalities 1 Year after recovering from COVID-19 in patients without clinical cardiac findings.

Aim: To evaluate the subclinical cardiac involvement in COVID-19 patients without clinical cardiac evidence using cardiac MR imaging. Material and methods: Participants recovered from COVID-19 without cardiac symptoms and no cardiovascular medical history were enrolled in a prospective cohort study. They underwent baseline cardiac MR and follow-up cardiac MR > 300 days after discharge (n = 20). The study also included healthy controls (n = 20). Extracellular volume fraction (ECV), native T1, and 2D strain data were assessed and compared. Results: The ECV values of participants at baseline [30.0% (28.3%-32.5%)] and at follow-up [31.0% (28.0%-32.8%)] were increased compared to the healthy control group [27.0% (25.3%-28.0%)] (both p < 0.001). However, the ECV increase from baseline cardiac MR to follow-up cardiac MR was not significant (p = 0.378). There was a statistically significant difference in global native T1 between baseline [1140 (1108.3-1192.0) ms] and follow-up [1176.0 (1113.0-1206.3) ms] (p = 0.016). However, no native T1 difference was found between the healthy controls [1160.7 (1119.6-1195.4) ms] and the baseline (p = 0.394) or follow-up group (p = 0.168). The global T2 was 41(40-42) ms at follow-up which was within the normal range. In addition, We found a recovery in 2D GLS among COVID-19 participants between baseline and follow-up [-12.4(-11.7 to -14.3)% vs. -17.2(-16.2 to -18.3)%; p＜0.001]. Conclusion: Using cardiac MR myocardial tissue and strain imaging parameters, 35% of people without cardiac symptoms or clinical evidence of myocardial injury still had subclinical myocardial tissue characteristic abnormalities at 300 days, but 2D GLS had recovered.

Cenozoic Indo-Pacific warm pool controlled by both atmospheric CO2 and paleogeography.

The Indo-Pacific warm pool (IPWP) is crucial for regional and global climates. However, the development of the IPWP and its effect on the regional climate during the Cenozoic remain unclear. Here, using a compilation of sea surface temperature (SST) records (mainly since the middle Miocene) and multimodel paleoclimate simulations, our results indicated that the extent, intensity and warmest temperature position of the IPWP changed markedly during the Cenozoic. Specifically, its extent decreased, its intensity weakened, and its warmest temperature position shifted from the Indian to western Pacific Ocean over time. The atmospheric CO2 dominated its extent and intensity, while paleogeography, by restricting the distribution of the Indian Ocean and the width of the tropical seaways, controlled the shift in its warmest temperature position. In particular, the eastward shift to the western Pacific Ocean from the middle to late Miocene inferred from compiled SST records likely resulted from the constriction of tropical seaways. Furthermore, by changing the atmospheric thermal structure and atmospheric circulation, the reduced extent and intensity of the IPWP decreased the annual precipitation in the western Indian Ocean, eastern Asia and Australia, while the shift in the warmest temperature position from the Indian to western Pacific Ocean promoted aridification in Australia. Qualitative model-data agreements are obtained for both the IPWP SST and regional climate. From the perspective of past warm climates with high concentrations of atmospheric CO2, the expansion and strengthening of the IPWP will occur in a warmer future and favor excessive precipitation in eastern Asia and Australia.

Myocardial involvement characteristics by cardiac MR imaging in neurological and non-neurological Wilson disease patients.

OBJECTIVES: To explore the characteristics of myocardial involvement in Wilson Disease (WD) patients by cardiac magnetic resonance (CMR). METHODS: We prospectively included WD patients and age- and sex-matched healthy population. We applied CMR to analyze cardiac function, strain, T1 maps, T2 maps, extracellular volume fraction (ECV) maps, and LGE images. Subgroup analyzes were performed for patients with WD with predominantly neurologic manifestations (WD-neuro +) or only hepatic manifestations (WD-neuro -). RESULTS: Forty-one WD patients (age 27.9 ± 8.0 years) and 40 healthy controls (age 25.4 ± 2.9 years) were included in this study. Compared to controls, the T1, T2, and ECV values were significantly increased in the WD group (T1 1085.1 ± 39.1 vs. 1046.5 ± 33.1 ms, T2 54.2 ± 3.3 ms vs. 51.5 ± 2.6 ms, ECV 31.8 ± 3.6% vs. 24.3 ± 3.7%) (all p < 0.001). LGE analysis revealed that LGE in WD patients was predominantly localized to the right ventricular insertion point and interventricular septum. Furthermore, the WD-neuro + group showed more severe myocardial damage compared to WD-neuro - group. The Unified Wilson Disease Rating Scale score was significantly correlated with ECV (Pearson's r = 0.64, p < 0.001). CONCLUSIONS: CMR could detect early myocardial involvement in WD patients without overt cardiac function dysfunction. Furthermore, characteristics of myocardial involvement were different between WD-neuro + and WD-neuro - , and myocardial involvement might be more severe in WD-neuro + patients. CRITICAL RELEVANCE STATEMENT: Cardiac magnetic resonance enables early detection of myocardial involvement in Wilson disease patients, contributing to the understanding of distinct myocardial characteristics in different subgroups and potentially aiding in the assessment of disease severity. KEY POINTS: • CMR detects WD myocardial involvement with increased T1, T2, ECV. • WD-neuro + patients show more severe myocardial damage and correlation with ECV. • Differences of myocardial characteristics exist between WD-neuro + and WD-neuro - patients.

Automatic quality assessment of knee radiographs using knowledge graphs and convolutional neural networks.

BACKGROUND: X-ray radiography is a widely used imaging technique worldwide, and its image quality directly affects diagnostic accuracy. Therefore, X-ray image quality control (QC) is essential. However, subjectively assessing image quality is inefficient and inconsistent, especially when large amounts of image data are being evaluated. Thus, subjective assessment cannot meet current QC needs. PURPOSE: To meet current QC needs and improve the efficiency of image quality assessment, a complete set of quality assessment criteria must be established and implemented using artificial intelligence (AI) technology. Therefore, we proposed a multi-criteria AI system for automatically assessing the image quality of knee radiographs. METHODS: A knee radiograph QC knowledge graph containing 16 "acquisition technique" labels representing 16 image quality defects and five "clarity" labels representing five grades of clarity were developed. Ten radiographic technologists conducted three rounds of QC based on this graph. The single-person QC results were denoted as QC1 and QC2, and the multi-person QC results were denoted as QC3. Each technologist labeled each image only once. The ResNet model structure was then used to simultaneously perform classification (detection of image quality defects) and regression (output of a clarity score) tasks to construct an image QC system. The QC3 results, comprising 4324 anteroposterior and lateral knee radiographs, were used for model training (70% of the images), validation (10%), and testing (20%). The 865 test set data were used to evaluate the effectiveness of the AI model, and an AI QC result, QC4, was automatically generated by the model after training. Finally, using a double-blind method, the senior QC expert reviewed the final QC results of the test set with reference to the results QC3 and QC4 and used them as a reference standard to evaluate the performance of the model. The precision and mean absolute error (MAE) were used to evaluate the quality of all the labels in relation to the reference standard. RESULTS: For the 16 "acquisition technique" features, QC4 exhibited the highest weighted average precision (98.42% ± 0.81%), followed by QC3 (91.39% ± 1.35%), QC2 (87.84% ± 1.68%), and QC1 (87.35% ± 1.71%). For the image clarity features, the MAEs between QC1, QC2, QC3, and QC4 and the reference standard were 0.508 ± 0.021, 0.475 ± 0.019, 0.237 ± 0.016, and 0.303 ± 0.018, respectively. CONCLUSIONS: The experimental results show that our automated quality assessment system performed well in classifying the acquisition technique used for knee radiographs. The image clarity quality evaluation accuracy of the model must be further improved but is generally close to that of radiographic technologists. Intelligent QC methods using knowledge graphs and convolutional neural networks have the potential for clinical applications.

Increased straw return promoted soil organic carbon accumulation in China's croplands over the past 40 years.

Quantifying changes in soil organic carbon (SOC) stocks within croplands across a broad spatiotemporal scale in response to anthropogenic and environmental factors offers valuable insights for sustainable agriculture aimed to improve soil health. Using a validated and widely used soil carbon model RothC, we simulated the SOC dynamics across intensive croplands in China that support ∼22 % of the global population using only 7 % of the global cropland area. The modelling results demonstrate that the optimized RothC effectively captures SOC dynamics measured across 29 long-term field trials during 40 years. Between 1980 and 2020, the average SOC at the top 30 cm in croplands increased from 40 Mg C ha-1 to 49 Mg C ha-1, resulting in a national carbon sequestration of 1100 Tg C, with an average carbon sequestration rate of 27 Tg C yr-1. The annual increase rate of SOC (relative to the SOC stock of the previous year), starting at <0.2 % yr-1 in the 1980s, reached around 0.4 % yr-1 in the 1990s and further rose to about 0.8 % yr-1 in the 2000s and 2010s. Notably, the eastern and southern regions, comprising about 40 % of the croplands, contributed about two-thirds of the national SOC gain. In northeast China, SOC slightly decreased from 58 Mg C ha-1 in 1980 to 57 Mg C ha-1 in 2020, resulting in a total decline of 28 Tg C. Increased organic C inputs, particularly from the straw return, was the crucial factor in SOC increase. Future strategies should focus on region-specific optimization of straw management. Specifically, in northeast China, increasing the proportion of straw returned to fields can prevent further SOC decline. In regions with SOC increase, such as the eastern and southern regions, diversified straw utilization (e.g., bioenergy production), could further mitigate greenhouse gas emissions.

Comparing Strain Assessment in Compressed Sensing and Conventional Cine MRI.

The aim of this study is to assess the feasibility of compressed sensing (CS) acceleration methods compared to conventional segmented cine (Seg) cardiac magnetic resonance (CMR) for evaluating left ventricular (LV) function and strain by feature tracking (FT). In this prospective study, 45 healthy volunteers underwent CMR imaging used Seg, threefold (CS3), fourfold (CS4), and eightfold (CS8) CS acceleration. Cine images were scored for quality (1-5 scale). LV volumetric and functional parameters and global longitudinal (GLS), circumferential (GCS), and radial strains (GRS) were quantified. LV volumetric and functional parameters exhibited no differences between Seg and all CS cines (all P > 0.05). The strains were similar for Seg, CS3, and CS4 (all P > 0.05). Similarly, no significant differences were observed in GRS and GCS between Seg and CS8 (all P > 0.05), but the global longitudinal strain was significantly lower for CS8 versus Seg (P < 0.001). Image quality declined with CS acceleration, especially in long-axis views with CS8. CS cine MRI at acceleration factor 4 maintained good image quality and accurate measurements of LV function and strain, although there was a slight reduction in the quality of long-axis images and GLS with CS8. CS acceleration up to a factor of 4 enabled fast CMR evaluations, making it suitable for clinical use.

Brain network localization of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia.

BACKGROUND: Numerous studies have established the presence of gray matter atrophy and brain activation abnormalities during neurocognitive and social cognitive tasks in schizophrenia. Despite a growing consensus that diseases localize better to distributed brain networks than individual anatomical regions, there is still a dearth of literature examining brain network localization of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia. METHODS: To address this gap, we initially identified brain locations of structural and functional abnormalities in schizophrenia from 301 published neuroimaging studies with 8712 schizophrenia individuals and 9275 healthy controls. By applying novel functional connectivity network mapping to large-scale resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 brain abnormality networks of schizophrenia. RESULTS: The gray matter atrophy network of schizophrenia comprised a broadly distributed set of brain areas predominantly implicating the ventral attention, somatomotor, and default networks. The neurocognitive dysfunction network was also composed of widespread brain areas primarily involving the frontoparietal and default networks. By contrast, the social cognitive dysfunction network consisted of circumscribed brain regions mainly implicating the default, subcortical, and visual networks. CONCLUSIONS: Our findings suggest shared and unique brain network substrates of gray matter atrophy, neurocognitive and social cognitive dysfunction in schizophrenia, which may not only refine the understanding of disease neuropathology from a network perspective, but also potentially contribute to more targeted and effective treatments for impairments in different cognitive domains in schizophrenia.