Neuromelanin-sensitive magnetic resonance imaging: Possibilities and promises as an imaging biomarker for Parkinson's disease.

Parkinson's disease (PD) is an age-related progressive neurodegenerative disorder characterized by both motor and non-motor symptoms resulting from the death of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and noradrenergic neurons in the locus coeruleus (LC). The current diagnosis of PD primarily relies on motor symptoms, often leading to diagnoses in advanced stages, where a significant portion of SNpc dopamine neurons has already succumbed. Therefore, the identification of imaging biomarkers for early-stage PD diagnosis and disease progression monitoring is imperative. Recent studies propose that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) holds promise as an imaging biomarker. In this review, we summarize the latest findings concerning NM-MRI characteristics at various stages in patients with PD and those with atypical parkinsonism. In conclusion, alterations in neuromelanin within the LC are associated with non-motor symptoms and prove to be a reliable imaging biomarker in the prodromal phase of PD. Furthermore, NM-MRI demonstrates efficacy in differentiating progressive supranuclear palsy (PSP) from PD and multiple system atrophy with predominant parkinsonism. The spatial patterns of changes in the SNpc can be indicative of PD progression and aid in distinguishing between PSP and synucleinopathies. We recommend that patients with PD and individuals at risk for PD undergo regular NM-MRI examinations. This technology holds the potential for widespread use in PD diagnosis.

A Lightweight Convolutional Neural Network Based on Dynamic Level-Set Loss Function for Spine MR Image Segmentation.

BACKGROUND: Spine MR image segmentation is important foundation for computer-aided diagnostic (CAD) algorithms of spine disorders. Convolutional neural networks segment effectively, but require high computational costs. PURPOSE: To design a lightweight model based on dynamic level-set loss function for high segmentation performance. STUDY TYPE: Retrospective. POPULATION: Four hundred forty-eight subjects (3163 images) from two separate datasets. Dataset-1: 276 subjects/994 images (53.26% female, mean age 49.02 ± 14.09), all for disc degeneration screening, 188 had disc degeneration, 67 had herniated disc. Dataset-2: public dataset with 172 subjects/2169 images, 142 patients with vertebral degeneration, 163 patients with disc degeneration. FIELD STRENGTH/SEQUENCE: T2 weighted turbo spin echo sequences at 3T. ASSESSMENT: Dynamic Level-set Net (DLS-Net) was compared with four mainstream (including U-net++) and four lightweight models, and manual label made by five radiologists (vertebrae, discs, spinal fluid) used as segmentation evaluation standard. Five-fold cross-validation are used for all experiments. Based on segmentation, a CAD algorithm of lumbar disc was designed for assessing DLS-Net's practicality, and the text annotation (normal, bulging, or herniated) from medical history data were used as evaluation standard. STATISTICAL TESTS: All segmentation models were evaluated with DSC, accuracy, precision, and AUC. The pixel numbers of segmented results were compared with manual label using paired t-tests, with P < 0.05 indicating significance. The CAD algorithm was evaluated with accuracy of lumbar disc diagnosis. RESULTS: With only 1.48% parameters of U-net++, DLS-Net achieved similar accuracy in both datasets (Dataset-1: DSC 0.88 vs. 0.89, AUC 0.94 vs. 0.94; Dataset-2: DSC 0.86 vs. 0.86, AUC 0.93 vs. 0.93). The segmentation results of DLS-Net showed no significant differences with manual labels in pixel numbers for discs (Dataset-1: 1603.30 vs. 1588.77, P = 0.22; Dataset-2: 863.61 vs. 886.4, P = 0.14) and vertebrae (Dataset-1: 3984.28 vs. 3961.94, P = 0.38; Dataset-2: 4806.91 vs. 4732.85, P = 0.21). Based on DLS-Net's segmentation results, the CAD algorithm achieved higher accuracy than using non-cropped MR images (87.47% vs. 61.82%). DATA CONCLUSION: The proposed DLS-Net has fewer parameters but achieves similar accuracy to U-net++, helps CAD algorithm achieve higher accuracy, which facilitates wider application. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Transcriptome analysis reveals how cadmium promotes root development and accumulates in Apocynum venetum, a promising plant for greening cadmium-contaminated soil.

Cadmium (Cd) contamination poses a substantial threat the environment, necessitating effective remediation strategies. Phytoremediation emerges as a cost-efficient and eco-friendly approach for reducing Cd levels in the soil. In this study, the suitability of A. venetum for ameliorating Cd-contaminated soils was evaluated. Mild Cd stress promoted seedling and root growth, with the root being identified as the primary tissue for Cd accumulation. The Cd content of roots ranged from 0.35 to 0.55 mg/g under treatment with 10-50 µM CdCl2·2.5 H2O, and the bioaccumulation factor ranged from 28.78 to 84.43. Transcriptome sequencing revealed 20,292 unigenes, and 7507 nonredundant differentially expressed genes (DEGs) were identified across five comparison groups. DEGs belonging to the "MAPK signaling pathway-plant," "monoterpenoid biosynthesis," and "flavonoid biosynthesis pathway" exhibited higher expression levels in roots compared to stems and leaves. In addition, cytokinin-related DEGs, ROS scavenger genes, such as P450, glutathione-S-transferase (GST), and superoxide dismutase (SOD), and the cell wall biosynthesis-related genes, CSLG and D-GRL, were also upregulated in the root tissue, suggesting that Cd promotes root development. Conversely, certain ABC transporter genes, (e.g, NRAMP5), and some vacuolar iron transporters, predominantly expressed in the roots, displayed a strong correlation with Cd content, revealing the mechanism underlying the compartmentalized storage of Cd in the roots. KEGG enrichment analysis of DEGs showed that the pathways associated with the biosynthesis of flavonoids, lignin, and some terpenoids were significantly enriched in the roots under Cd stress, underscoring the pivotal role of these pathways in Cd detoxification. Our study suggests A. venetum as a potential Cd-contaminated phytoremediation plant and provides insights into the molecular-level mechanisms of root development promotion and accumulation mechanism in response to Cd stress.

LSW-Net: Lightweight Deep Neural Network Based on Small-World properties for Spine MR Image Segmentation.

BACKGROUND: Segmenting spinal tissues from MR images is important for automatic image analysis. Deep neural network-based segmentation methods are efficient, yet have high computational costs. PURPOSE: To design a lightweight model based on small-world properties (LSW-Net) to segment spinal MR images, suitable for low-computing-power embedded devices. STUDY TYPE: Retrospective. POPULATION: A total of 386 subjects (2948 images) from two independent sources. Dataset I: 214 subjects/779 images, all for disk degeneration screening, 147 had disk degeneration, 52 had herniated disc. Dataset II: 172 subjects/2169 images, 142 patients with vertebral degeneration, 163 patients with disc degeneration. 70% images in each dataset for training, 20% for validation, and 10% for testing. FIELD STRENGTH/SEQUENCE: T1- and T2-weighted turbo spin echo sequences at 3 T. ASSESSMENT: Segmentation performance of LSW-Net was compared with four mainstream (including U-net and U-net++) and five lightweight models using five radiologists' manual segmentations (vertebrae, disks, spinal fluid) as reference standard. LSW-Net was also deployed on NVIDIA Jetson nano to compare the pixels number in segmented vertebrae and disks. STATISTICAL TESTS: All models were evaluated with accuracy, precision, Dice similarity coefficient (DSC), and area under the receiver operating characteristic (AUC). Pixel numbers segmented by LSW-Net on the embedded device were compared with manual segmentation using paired t-tests, with P < 0.05 indicating significance. RESULTS: LSW-Net had 98.5% fewer parameters than U-net but achieved similar accuracy in both datasets (dataset I: DSC 0.84 vs. 0.87, AUC 0.92 vs. 0.94; dataset II: DSC 0.82 vs. 0.82, AUC 0.88 vs. 0.88). LSW-Net showed no significant differences in pixel numbers for vertebrae (dataset I: 5893.49 vs. 5752.61, P = 0.21; dataset II: 5073.42 vs. 5137.12, P = 0.56) and disks (dataset I: 1513.07 vs. 1535.69, P = 0.42; dataset II: 1049.74 vs. 1087.88, P = 0.24) segmentation on an embedded device compared to manual segmentation. DATA CONCLUSION: Proposed LSW-Net achieves high accuracy with fewer parameters than U-net and can be deployed on embedded device, facilitating wider application. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: 1.

Preliminary MRI Study of Extracellular Volume Fraction for Identification of Lymphovascular Space Invasion of Cervical Cancer.

BACKGROUND: Lymphovascular space invasion (LVSI) is a risk factor for poor prognosis of cervical cancer. Preoperative identification of LVSI is very difficult. PURPOSE: To evaluate the potential of extracellular volume (ECV) fraction based on T1 mapping in preoperative identification of LVSI in cervical cancer compared with dynamic contrast-enhanced MRI (DCE-MRI). STUDY TYPE: Retrospective. SUBJECTS: A total of 79 patients (median age 54 years) with cervical cancer were classified into LVSI group (n = 29) and without LVSI group (n = 50) according to postoperative pathology. FIELD STRENGTH/SEQUENCE: A 3-T, noncontrast and contrast-enhanced T1 mapping performed with volume interpolated breath hold examination (VIBE) sequence, DCE-MRI applied with 3D T1-weighted VIBE sequence. ASSESSMENT: Regions of interest along the medial edge of the lesion were drawn on slices depicting the maximum cross-section of the tumor. The noncontrast and contrast-enhanced T1 value of the tumor and arteries in the same slice were measured, and ECV was calculated from T1 values. The parametric maps (Ktrans , kep , and ve ) derived from DCE-MRI standard Toft's model were evaluated. STATISTICAL TESTS: ECV, Ktrans , kep , and ve between groups with and without LVSI were compared using Student's t-test. The receiver operating characteristic (ROC) curve and DeLong test were used to evaluate and compare the diagnostic performance of ECV, Ktrans , kep , and ve for differentiating LVSI. P < 0.05 was considered statistically significant. RESULTS: The ECV and Ktrans of the LVSI group were significantly higher than that of non-LVSI group (52.86% vs. 36.77%, 0.239 vs. 0.176, respectively), and no significant differences in Kep or ve values were observed (P = 0.071 and P = 0.168, respectively). The ECV fraction showed significantly higher area under ROC curve than Ktrans for differentiating LVSI (0.874 vs. 0.655, respectively). DATA CONCLUSION: ECV measurements based on T1 mapping might improve the discrimination between patients with and without LVSI in cervical cancer, showing better performance for this purpose than DCE-MRI. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Vibration and Noise Analysis and Experimental Study of Rail Conveyor.

The rail conveyor is a new type of energy-saving system for the long-distance transportation of bulk materials. Operating noise is an urgent problem that the current model faces. It will cause noise pollution and affect the health of workers. In this paper, the factors causing vibration and noise are analyzed by modeling the wheel-rail system and the supporting truss structure. Based on the built test platform, the system vibration of the vertical steering wheel, the track support truss, and the track connection were measured, and the vibration characteristics at different positions were analyzed. Based on the established noise and vibration model, the distribution and occurrence rules of system noise under different operating speeds and fastener stiffness conditions were obtained. The experimental results show that the vibration amplitude of the frame near the head of the conveyor is the largest. The amplitude under the condition of 2 m/s running speed at the same position is 4 times that under the condition of 1 m/s. At different welds of the track, the width and depth of the rail gap have a great influence on the vibration impact, which is mainly due to the impact of the uneven impedance at the track gap, and the greater the running speed, the more obvious the vibration impact. The simulation results show the trend of noise generation, the speed of the trolley, and the stiffness of the track fasteners have a positive effect on the generation of noise in the low-frequency region. The research results of this paper will play an important role in the noise and vibration analysis of rail conveyors and help to optimize the structure design of the track transmission system.

Radiomics model based on multi-sequence MR images for predicting preoperative immunoscore in rectal cancer.

PURPOSE: To establish and validate a radiomics model based on multi-sequence magnetic resonance (MR) images for preoperative prediction of immunoscore in rectal cancer. MATERIALS AND METHODS: This retrospective study included 133 patients with pathologically confirmed rectal cancer after surgical resection who underwent MR examination before treatment within two weeks. All patients were randomly divided into training cohort (n = 92) and validation (n = 41) cohort according to a ratio of 7:3. The volumes of interest were manually delineated in the T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) images, from which a total of 804 radiomics features were extracted. Thereafter, we used Spearman correlation analysis and gradient boosting decision tree (GBDT) algorithm to select the strongest features, and the radiomics scores were established using multivariate logistic regression algorithm, including two single-mode models and two dual-mode models. The predictive performance and the clinical usefulness of the model were assessed by the receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA). RESULTS: Integrated model A based on T2WI and ADC images showed a better predictive performance, which yielded an AUC of 0.770 (95% CI 0.673-0.867) in the training cohort and 0.768 (95% CI 0.619-0.917) in the validation cohort. Calibration curve showed good agreement between predicted results of the model and actual events, and DCA indicated good clinical usefulness. Moreover, stratification analysis proved that the integrated model A had strong robustness. CONCLUSIONS: Integrated model A based on T2WI and ADC images has the potential to be used as a non-invasive tool for preoperative prediction of immunoscore in rectal cancer. It may be useful in evaluating prognosis and guiding individualized immunotherapy of patients.

Anatomical correlation between left atrium pulmonary vein ablation targets of atrial fibrillation and adjacent bronchi and pulmonary arteries by MSCT.

BACKGROUND: The ablation targets of atrial fibrillation (AF) are adjacent to bronchi and pulmonary arteries (PAs). We used computed tomography (CT) to evaluate the anatomical correlation between left atrium (LA)-pulmonary vein (PV) and adjacent structures. METHODS: Data were collected from 126 consecutive patients using coronary artery CT angiography. The LA roof was divided into three layers and nine points. The minimal spatial distances from the nine points and four PV orifices to the adjacent bronchi and PAs were measured. The distances from the PV orifices to the nearest contact points of the PVs, bronchi, and PAs were measured. RESULTS: The anterior points of the LA roof were farther to the bronchi than the middle or posterior points. The distances from the nine points to the PAs were shorter than those to the bronchi (5.19 ± 3.33 mm vs 8.62 ± 3.07 mm; P < .001). The bilateral superior PV orifices, especially the right superior PV orifices were closer to the PAs than the inferior PV orifices (left superior PV: 7.59 ± 4.14 mm; right superior PV: 4.43 ± 2.51 mm; left inferior PV: 24.74 ± 5.26 mm; right inferior PV: 22.33 ± 4.75 mm) (P < .001). CONCLUSIONS: The right superior PV orifices were closer to the bronchi and PAs than other PV orifices. The ablation at the mid-posterior LA roof had a higher possibility to damage bronchi. CT is a feasible method to assess the anatomical adjacency in vivo, which might provide guidance for AF ablation.

Texture analysis of MR images to identify the differentiated degree in hepatocellular carcinoma: a retrospective study.

BACKGROUND: To explore the clinical value of texture analysis of MR images (multiphase Gd-EOB-DTPA-enhanced MRI and T2 weighted imaging (T2WI) to identify the differentiated degree of hepatocellular carcinoma (HCC). METHOD: One hundred four participants were enrolled in this retrospective study. Each participant performed preoperative Gd-EOB-DTPA-enhanced MR scanning. Texture features were analyzed by MaZda, and B11 program was used for data analysis and classification. The diagnosis efficiencies of texture features and conventional imaging features in identifying the differentiated degree of HCC were assessed by receiver operating characteristic analysis. The relationship between texture features and differentiated degree of HCC was evaluated by Spearman's correlation coefficient. RESULTS: The grey-level co-occurrence matrix -based texture features were most frequently extracted and the nonlinear discriminant analysis was excellent with the misclassification rate ranging from 3.33 to 14.93%. The area under the curve (AUC) of the combined texture features between poorly- and well-differentiated HCC, poorly- and moderately-differentiated HCC, moderately- and well-differentiated HCC was 0.812, 0.879 and 0.808 respectively, while the AUC of tumor size was 0.649, 0.660 and 0.517 respectively. The tumor size was significantly different between poorly- and moderately-HCC (p = 0.014). The COMBINE AUC values were not increased with tumor size combined. CONCLUSIONS: Texture analysis of Gd-EOB-DTPA-enhanced MRI and T2WI was valuable and might be a promising method in identifying the differentiated degree of HCC. The poorly-differentiated HCC was more heterogeneous than well- and moderately-differentiated HCC.

Effects of granule size on physicochemical and digestive properties of potato powder.

BACKGROUND: Potato powder, a rich source of high-quality protein and starch, plays an important role in the production of functional foods. In this study, ball-mill processed potato powders with different particle sizes (278, 208, 129, and 62 µm) were analyzed in terms of physicochemical, pasting, rheological, and digestive properties. RESULTS: Scanning electron microscopy and laser diffraction analysis of the samples revealed mono-model particle-size distributions. X-ray diffraction analysis confirmed structure destruction of starch pellets. Proximate composition and physical property analysis showed an increase in the water, ash, protein, and starch content. Meanwhile, the water solubility index and swelling power values were found to increase with decreasing grain size, and so were the brightness (L*) and redness (b*) values of the potato powders. With particle size reduced to 129 µm, large changes were observed in gelatinization properties, such as peak viscosity, trough viscosity, breakdown viscosity, and final viscosity. Oscillatory rheology results also showed that, with the decrease in particle size, the storage modulus (G') and loss modulus (G″) improved, with highest storage modulus (G') observed in the 129 µm particle size. The hydrolysis rate and glycemic index also increased in the 129 µm potato powder. CONCLUSION: The results provide information that could be useful for improving quality characteristics by using specific grain sizes in the development of potato-based products such as gluten-free products and ethnic food products with particular functional and rheological properties. © 2020 Society of Chemical Industry.

Specific "Unlocking" of a Nanozyme-Based Butterfly Effect To Break the Evolutionary Fitness of Chaotic Tumors.

Chaos and the natural evolution of tumor systems can lead to the failure of tumor therapies. Herein, we demonstrate that iridium oxide nanoparticles (IrOx ) possess acid-activated oxidase and peroxidase-like functions and wide pH-dependent catalase-like properties. The integration of glucose oxidase (GOD) unlocked the oxidase and peroxidase activities of IrOx by the production of gluconic acid from glucose by GOD catalysis in cancer cells, and the produced H2 O2 was converted into O2 to compensate its consumption in GOD catalysis owing to the catalase-like function of the nanozyme, thus resulting in the continual consumption of glucose and the self-supply of substrates to generate superoxide anion and hydroxyl radical. Moreover, IrOx can constantly consume glutathione (GSH) by self-cyclic valence alternation of IrIV and IrIII . These cascade reactions lead to a "butterfly effect" of initial starvation therapy and the subsequent pressure of multiple reactive oxygen species (ROS) to completely break the self-adaption of cancer cells.

Assessment of active and inactive sacroiliitis in patients with ankylosing spondylitis using quantitative dynamic contrast-enhanced MRI.

PURPOSE: To investigate the feasibility of using quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) to differentiate the active and inactive stage of sacroiliitis and the correlation between quantitative parameters and disease activity as measured by clinical scores. MATERIALS AND METHODS: Forty-two patients with ankylosing spondylitis underwent DCE-MRI on a 3.0T MRI unit. According to the results of the blood sedimentation rate (ESR), C-reactive protein (CRP), and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the patients were grouped into inactive and active groups. Pharmacokinetic models were used to generate the semiquantitative and quantitative hemodynamic parameters of DCE-MRI. The between-group differences were analyzed using the Wilcoxon rank sum test, and the correlations between the pharmacokinetic parameters and BASDAI score were analyzed using Spearman's correlation coefficient. The efficacies of different parameters in differentiating the active and inactive phase of sacroiliitis were evaluated and compared using receiver operator characteristics (ROC) curve analysis. RESULTS: Ktrans , Kep , Ve , time to peak (TTP), max concentration (MAX Conc), and area under the curve (AUC) of the active group were significantly higher than those of the inactive stage group (P < 0.05). There were significant correlations between all parameters and BASDAI (P < 0.05). AUC of the receiver operator characteristics curve (AUCR ) of different parameters were not statistically different (P >0.05), except between AUC and MAX Conc (P = 0.0012). CONCLUSION: Quantitative DCE-MRI parameters can differentiate between active and inactive ankylosing spondylitis. Among those, Ktrans had the highest correlation coefficient with the BASDAI score. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:71-78.

FeIII -Doped Two-Dimensional C3 N4 Nanofusiform: A New O2 -Evolving and Mitochondria-Targeting Photodynamic Agent for MRI and Enhanced Antitumor Therapy.

Local hypoxia in tumors, as well as the short lifetime and limited action region of 1 O2 , are undesirable impediments for photodynamic therapy (PDT), leading to a greatly reduced effectiveness. To overcome these adversities, a mitochondria-targeting, H2 O2 -activatable, and O2 -evolving PDT nanoplatform is developed based on FeIII -doped two-dimensional C3 N4 nanofusiform for highly selective and efficient cancer treatment. The ultrahigh surface area of 2D nanosheets enhances the photosensitizer (PS) loading capacity and the doping of FeIII leads to peroxidase mimetics with excellent catalytic performance towards H2 O2 in cancer cells to generate O2 . As such tumor hypoxia can be overcome and the PDT efficacy is improved, whilst at the same time endowing the PDT theranostic agent with an effective T 1 -weighted in vivo magnetic resonance imaging (MRI) ability. Conjugation with a mitochondria-targeting agent could further increase the sensitivity of cancer cells to 1 O2 by enhanced mitochondria dysfunction. In vitro and in vivo anticancer studies demonstrate an outstanding therapeutic effectiveness of the developed PDT agent, leading to almost complete destruction of mouse cervical tumor. This development offers an attractive theranostic agent for in vivo MRI and synergistic photodynamic therapy toward clinical applications.

Imaging of Pericardiophrenic Bundles Using Multislice Spiral Computed Tomography for Phrenic Nerve Anatomy.

INTRODUCTION: Phrenic nerve injury and diaphragmatic stimulation are common complications following arrhythmia ablation and pacing therapies. Preoperative comprehension of phrenic nerve anatomy via non-invasive CT imaging may help to minimize the electrophysiological procedure-related complications. METHODS: Coronary CT angiography data of 121 consecutive patients were collected. Imaging of left and right pericardiophrenic bundles was performed with volume rendering and multi-planar reformation techniques. The shortest spatial distances between phrenic nerves and key electrophysiology-related structures were determined. The frequencies of the shortest distances ≤5 mm, >5 mm and direct contact between phrenic nerves and adjacent structures were calculated. RESULTS: Left and right pericardiophrenic bundles were identified in 86.8% and 51.2% of the patients, respectively. The right phrenic nerve was <5 mm from right superior and inferior pulmonary veins in 92.0% and 3.2% of the patients, respectively. The percentage of right phrenic nerve, <5 mm from right atrium, superior caval vein, and superior caval vein-right atrium junction was 87.1%, 100%, and 62.9%, respectively. Left phrenic nerve was <5 mm from left atrial appendage, great cardiac vein, anterior and posterior interventricular veins, and left ventricular posterior veins in 81.9%, 1.0%, 39.1%, 28.6%, and 91.4% of the patients, respectively. Merely 0.06% left phrenic nerve had a distance <5 mm with left superior pulmonary vein, and none left phrenic nerve showed a distance <5 mm with left inferior pulmonary vein. CONCLUSION: One-stop enhanced CT scanning enabled detection of phrenic nerve anatomy, which might facilitate avoidance of the phrenic nerve-related complications in interventional electrophysiology.

Utility of virtual unenhanced images and split-bolus injection using spectral multidetector CT for the assessment of renal cell carcinoma conspicuity and radiation dose.

OBJECTIVE: The aim of this study was to evaluate the radiation dose and renal cell carcinoma conspicuity with virtual unenhanced images and split-bolus injection from spectral multidetector CT (MDCT). MATERIAL AND METHODS: This prospective study was approved by the Ethics Committee, and informed consent was obtained. Ninety suspected patients of renal cell carcinoma diagnosed by abdominal ultrasonography and CEUS were randomly divided into two groups by a radiographer. Patients of the first group underwent spectral MDCT with virtual unenhanced imaging and split-bolus injection, while patients in the second group underwent conventional unenhanced as well as tri-phasic enhanced CT. Group A (split-bolus spectral MDCT group): The contrast material was administered at a dose of 1.5 mL/kg body weight at a flow rate of 4 mL/s, with a ratio of 7 to 5 before the CT scan with an interval of 60 seconds. Virtual unenhanced images were generated using a standard three-material decomposition algorithm, and the best mono-energy (keV) was calculated to show the tumour, renal artery and renal vein. Group B (conventional tri-phasic enhanced CT group): the contrast agent was injected with a dose of 1.5 mL/kg body weight at a flow rate of 4 mL/s. The corticomedullary phase scanning was performed once the arterial CT value reached 100 HU; the nephrographic phase was scanned 60 seconds later. And the excretory phase was scanned 5 min after onset of contrast injection. The LKR (lesion kidney ratio), CNR, and CT value of the corticomedullary and nephrographic phase were measured. The opacification of the renal collection system (including calices, infundibula and renal pelvis) was scored. The radiation dose was recorded. Statistical analysis was performed using Student's t-test, Fisher's exact test, the Mann-Whitney U-test, and k statistics. RESULTS: There were no statistically significant differences between the two groups in age, sex and body mass index (BMI), but there was significant difference in treatment methods. The best mono-energy was 58 keV for showing the tumour and renal artery and 67 keV for showing the renal vein. There were no differences in the mean attenuations of normal renal parenchyma, renal tumour, CNR, and imaging quality between true unenhanced images and virtual unenhanced images from the combined corticomedullary and nephrographic phase. The LKR of the mono-energy at 58 keV from the combined corticomedullary and nephrographic phase was significantly better than the corticomedullary phase of the conventional enhanced CT scan (0.74±0.18 vs 1.08±0.34, P<.01), but there was no difference in CNR (2.31±1.74 vs 2.79±1.83, P>.05). There were no differences in the CT values of the renal tumour, normal renal parenchyma and renal artery between the two groups (P>.05). The CT value of the renal vein at mono-energy (67 keV) (200.55±43.38) from the combined corticomedullary and nephrographic phase was higher than the conventional CT scan (140.90±42.64) in the nephrographic phase. The Kappa scores of the rate of the renal collection system for the conventional CT and spectral CT were 0.68 (95% confidence interval [CI]: 0.35-0.89) and 0.54 (95% CI: 0.30-0.88), respectively. The radiation dose (735±162 mGy·cm) of Group A was significantly less than that of Group B (1032±324 mGy·cm) (P<.01). CONCLUSION: Conspicuity with virtual unenhanced imaging and split-bolus injection from spectral multidetector CT is better than or equal to the conventional three-phase enhanced CT scan in showing the RCC, renal artery and renal vein, while the radiation dose can be reduced by 28.78%.

Correlation of the UGT1A4 gene polymorphism with serum concentration and therapeutic efficacy of lamotrigine in Han Chinese of Northern China.

OBJECTIVE: The pharmacokinetics of lamotrigine (LTG) varies significantly among individuals and particularly among different ethnic groups. This is in part due to the presence of genetic polymorphisms affecting genes that metabolize LTG. UGT1A4 is a major metabolizing enzyme of LTG. The aim of this study was to investigate the effect of two UGT1A4 gene polymorphisms, UGT1A4 (70C > A) and UGT1A4 (142 T > G), on the levels and efficacy of LTG in Han Chinese patients with epilepsy. METHODS: The study cohort comprised 106 Han Chinese patients patients with epilepsy who were receiving LTG monotherapy. Blood samples were taken and LTG levels measured. The presence of UGT1A4 (70C > A) and UGT1A4 (142 T > G) was determined. The therapeutic efficacy of LTG at the 1-year time-point was assessed. RESULTS: All patients were homozygous for the CC genotype of UGT1A4 (70C > A), while the distribution of UGT1A4 (142 T > G) varied among patients. Two patients had a single nucleotide deletion at position 127 (UGT1A4 127delA). To evaluate the effect of the UGT1A4 (142 T > G) polymorphism on LTG pharmacokinetics, patients were divided into two groups. Group A included patients with the 142TG or 142GG polymorphism and Group B patients had the 142TT polymorphism. The normalized blood concentration and the efficacy of LTG were higher in Group B patients than in Group A patients (P < 0.05). The two patients with UGT1A4 127delA genotype had extremely high blood levels of LTG, and treatment was discontinued in one of these patients due to a severe LTG-associated rash. CONCLUSION: Patients with the UGT1A4 142TT polymorphism had a higher blood LTG concentration and better therapeutic efficacy, suggesting that this polymorphism influences LTG activity. The UGT1A4 127delA polymorphism significantly affected LTG levels and increased one of our patient's susceptibility to LTG-related adverse events.

SALW-Net: a lightweight convolutional neural network based on self-adjusting loss function for spine MR image segmentation.

Segmentation of intervertebral discs and vertebrae from spine magnetic resonance (MR) images is essential to aid diagnosis algorithms for lumbar disc herniation. Convolutional neural networks (CNN) are effective methods, but often require high computational costs. Designing a lightweight CNN is more suitable for medical sites lacking high-computing power devices, yet due to the unbalanced pixel distribution in spine MR images, the segmentation is often sub-optimal. To address this issue, a lightweight spine segmentation CNN based on a self-adjusting loss function, which is named SALW-Net, is proposed in this study. For SALW-Net, the self-adjusting loss function could dynamically adjust the loss weights of the two branches according to the differences in segmentation results and labels during the training; thus, the ability for learning unbalanced pixels is enhanced. Two separate datasets are used to evaluate the proposed SALW-Net. Specifically, the proposed SALW-Net has fewer parameter numbers than U-net (only 2%) but achieves higher evaluation scores than that of U-net (the average DSC score of SALW-Net is 0.8781, and that of U-net is 0.8482). In addition, the practicality validation for SALW-Net is also proceeding, including deploying the model on a lightweight device and producing an aid diagnosis algorithm based on segmentation results. This means our SALW-Net has clinical application potential for assisted diagnosis in low computational power scenarios.

Polydopamine-encapsulated zinc peroxide nanoparticles to target the metabolism-redox circuit against tumor adaptability for mild photothermal therapy.

Regulating the metabolism-redox circuit of cancer cells has emerged as an attractive strategy to improve the therapeutic outcome, while often confronting the glaring issue of resistance due to the multiple adaptive responses of tumor cells. This study presents a simple yet efficient approach to regulate this circuit simultaneously against tumor adaptability by utilizing polydopamine-encapsulated zinc peroxide nanoparticles (ZnO2@PDA NPs). The nanoparticles could deliver large amounts of Zn2+ and H2O2 into tumor cells to unfold an intracellular self-amplifying loop for breaking the balance in zinc and redox homeostasis by H2O2-mediated endogenous Zn2+ release from metallothioneins due to its oxidation by H2O2 and Zn2+-induced in situ H2O2 production by disturbing mitochondrial respiration, ultimately disrupting tumor adaptability to exogenous stimuli. The elevated levels of Zn2+ and H2O2 also inhibited adenosine triphosphate (ATP) generation from glycolysis and mitochondrial respiration to disrupt energy adaptability. Furthermore, insufficient ATP supply could reduce glutathione and heat shock protein expression, thereby sensitizing oxidative stress and enabling PDA-mediated mild photothermal therapy (PTT). Consequently, this trinity nanoplatform, which integrated dual-starvation therapy, amplified oxidative stress, and mild PTT, demonstrated outstanding therapeutic effects and a facile strategy.

A CT based radiomics analysis to predict the CN0 status of thyroid papillary carcinoma: a two- center study.

OBJECTIVES: To develop and validate radiomics model based on computed tomography (CT) for preoperative prediction of CN0 status in patients with papillary thyroid carcinoma (PTC). METHODS: A total of 548 pathologically confirmed LNs (243 non-metastatic and 305 metastatic) two distinct hospitals were retrospectively assessed. A total of 396 radiomics features were extracted from arterial-phase CT images, where the strongest features containing the most predictive potential were further selected using the least absolute shrinkage and selection operator (LASSO) regression method. Delong test was used to compare the AUC values of training set, test sets and cN0 group. RESULTS: The Rad-score showed good discriminating performance with Area Under the ROC Curve (AUC) of 0.917(95% CI, 0.884 to 0.950), 0.892 (95% CI, 0.833 to 0.950) and 0.921 (95% CI, 868 to 0.973) in the training, internal validation cohort and external validation cohort, respectively. The test group of CN0 with a AUC of 0.892 (95% CI, 0.805 to 0.979). The accuracy was 85.4% (sensitivity = 81.3%; specificity = 88.9%) in the training cohort, 82.9% (sensitivity = 79.0%; specificity = 88.7%) in the internal validation cohort, 85.4% (sensitivity = 89.7%; specificity = 83.8%) in the external validation cohort, 86.7% (sensitivity = 83.8%; specificity = 91.3%) in the CN0 test group.The calibration curve demonstrated a significant Rad-score (P-value in H-L test > 0.05). The decision curve analysis indicated that the rad-score was clinically useful. CONCLUSIONS: Radiomics has shown great diagnostic potential to preoperatively predict the status of cN0 in PTC.

Arterial Stiffness and Obesity as Predictors of Diabetes: Longitudinal Cohort Study.

BACKGROUND: Previous studies have confirmed the separate effect of arterial stiffness and obesity on type 2 diabetes; however, the joint effect of arterial stiffness and obesity on diabetes onset remains unclear. OBJECTIVE: This study aimed to propose the concept of arterial stiffness obesity phenotype and explore the risk stratification capacity for diabetes. METHODS: This longitudinal cohort study used baseline data of 12,298 participants from Beijing Xiaotangshan Examination Center between 2008 and 2013 and then annually followed them until incident diabetes or 2019. BMI (waist circumference) and brachial-ankle pulse wave velocity were measured to define arterial stiffness abdominal obesity phenotype. The Cox proportional hazard model was used to estimate the hazard ratio (HR) and 95% CI. RESULTS: Of the 12,298 participants, the mean baseline age was 51.2 (SD 13.6) years, and 8448 (68.7%) were male. After a median follow-up of 5.0 (IQR 2.0-8.0) years, 1240 (10.1%) participants developed diabetes. Compared with the ideal vascular function and nonobese group, the highest risk of diabetes was observed in the elevated arterial stiffness and obese group (HR 1.94, 95% CI 1.60-2.35). Those with exclusive arterial stiffness or obesity exhibited a similar risk of diabetes, and the adjusted HRs were 1.63 (95% CI 1.37-1.94) and 1.64 (95% CI 1.32-2.04), respectively. Consistent results were observed in multiple sensitivity analyses, among subgroups of age and fasting glucose level, and alternatively using arterial stiffness abdominal obesity phenotype. CONCLUSIONS: This study proposed the concept of arterial stiffness abdominal obesity phenotype, which could improve the risk stratification and management of diabetes. The clinical significance of arterial stiffness abdominal obesity phenotype needs further validation for other cardiometabolic disorders.