A monofunctional Pt(II) complex combats triple negative breast cancer by triggering lysosome-dependent cell death.

Monofunctional Pt(II) complexes with potent efficacy to overcome the drawbacks of current platinum drugs represent a promising therapeutic approach for triple negative breast cancer (TNBC). A heterocyclic-ligated monofunctional Pt(II) complex PtL with a unique action of mode was designed and investigated. PtL induced DNA single-strand breaks and caused genomic instability in TNBC cells. Mechanism studies demonstrated that PtL disrupted lysosomal acidity and function, which in turn triggered lysosome-dependent cell death. Furthermore, PtL showed convincing suppression in the tube forming and cell migratory abilities against the metastatic potential of TNBC cells. The synthesis and investigation of PtL revealed its potential value as an anti-TNBC drug and extended the family of monofunctional Pt(II) complexes.

U-fiber analysis: a toolbox for automated quantification of U-fibers and white matter hyperintensities.

Background: Whether white matter hyperintensities (WMHs) involve U-fibers is of great value in understanding the different etiologies of cerebral white matter (WM) lesions. However, clinical practice currently relies only on the naked eye to determine whether WMHs are in the vicinity of U-fibers, and there is a lack of good neuroimaging tools to quantify WMHs and U-fibers. Methods: Here, we developed a multimodal neuroimaging toolbox named U-fiber analysis (UFA) that can automatically extract WMHs and quantitatively characterize the volume and number of WMHs in different brain regions. In addition, we proposed an anatomically constrained U-fiber tracking scheme and quantitatively characterized the microstructure diffusion properties, fiber length, and number of U-fibers in different brain regions to help clinicians to quantitatively determine whether WMHs in the proximal cortex disrupt the microstructure of U-fibers. To validate the utility of the UFA toolbox, we analyzed the neuroimaging data from 246 patients with cerebral small vessel disease (cSVD) enrolled at Zhongshan Hospital between March 2018 and November 2019 in a cross-sectional study. Results: According to the manual judgment of the clinician, the patients with cSVD were divided into a WMHs involved U-fiber group (U-fiber-involved group, 51 cases) and WMHs not involved U-fiber group (U-fiber-spared group, 163 cases). There were no significant differences between the U-fiber-spared group and the U-fiber-involved group in terms of age (P=0.143), gender (P=0.462), education (P=0.151), Mini-Mental State Examination (MMSE) scores (P=0.151), and Montreal Cognitive Assessment (MoCA) scores (P=0.411). However, patients in the U-fiber-involved group had higher Fazekas scores (P<0.001) and significantly higher whole brain WMHs (P=0.046) and deep WMH volumes (P<0.001) compared to patients in the U-fiber-spared group. Moreover, the U-fiber-involved group had higher WMH volumes in the bilateral frontal [P(left) <0.001, P(right) <0.001] and parietal lobes [P(left) <0.001, P(right) <0.001]. On the other hand, patients in the U-fiber-involved group had higher mean diffusivity (MD) and axial diffusivity (AD) in the bilateral parietal [P(left, MD) =0.048, P(right, MD) =0.045, P(left, AD) =0.015, P(right, AD) =0.015] and right frontal-parietal regions [P(MD) =0.048, P(AD) =0.027], and had significantly reduced mean fiber length and number in the right parietal [P(length) =0.013, P(number) =0.028] and right frontal-parietal regions [P(length) =0.048] compared to patients in the U-fiber-spared group. Conclusions: Our results suggest that WMHs in the proximal cortex may disrupt the microstructure of U-fibers. Our tool may provide new insights into the understanding of WM lesions of different etiologies in the brain.

The effects of P2 segment of posterior cerebral artery to thalamus blood supply pattern on gait in cerebral small vessel disease: A 7 T MRI based study.

Gait disturbance is a manifestation of cerebral small vessel disease (CSVD). The posterolateral thalamus (PL), whose blood is mainly supplied by the P2 segment of posterior cerebral artery (P2-PCA), plays pivotal roles in gait regulation. We investigated the influence of the distance between P2-PCA and PL on gait with varying CSVD burden. 71 participants were divided into low and high CSVD burden groups. The distance from P2-PCA to PL was measured using 7 T TOF-MRA and categorized into an immediate or distant PCA-to-thalamus pattern. Functional connectivity (FC) and voxel-based morphometry were assessed to evaluate functional and structural alterations. In the low CSVD burden group, immediate PCA-to-thalamus supply strongly correlates with longer step length and higher wave phase time percent, and exhibited enhanced FCs in left supplementary motor area, right precentral cortex (PreCG.R). While in the high CSVD burden group, no association between PCA-to-thalamus pattern and gait was found, and we observed reduced FC in PreCG.R with immediate PCA-to-thalamus pattern. Higher CSVD burden was associated with decreased gray matter density in bilateral thalamus. However, no significant structural thalamic change was observed between the two types of PCA-to-thalamus patterns in all patients. Our study demonstrated patients with immediate PCA-to-thalamus supply exhibited better gait performance in low CSVD burden populations, which also correlated with enhanced FCs in motor-related cortex, indicating the beneficial effects of the immediate PCA-to-thalamus supply pattern. In the higher burden CSVD populations, the effects of PCA-to-thalamus pattern on gait are void, attributable to the CSVD-related thalamic destruction and impairment of thalamus-related FC.

Strychni Semen Combined with Atractylodes Macrocephala Koidz Attenuates Rheumatoid Arthritis by Regulating Apoptosis.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease that can lead to joint pain and disability, and seriously impact patients' quality of life. Strychni Semen combined with Atractylodes Macrocephala koidz (SA) have pronounced curative effect on RA, and there is no poisoning of Strychni Semen (SS). However, its pharmacological mechanisms are still unclear. OBJECTIVE: In this study, we aimed to investigate the pharmacological mechanisms of Strychni Semen combined with Atractylodes Macrocephala Koidz (SA) for the treatment of RA. METHODS: We used network pharmacology to screen the active components of SA and predict the targets and pathways involved. Results originating from network pharmacology were then verified by animal experiments. RESULTS: Network pharmacology identified 81 active ingredients and 141 targets of SA; 2640 disease-related genes were also identified. The core targets of SA for the treatment of RA included ALB, IL-6, TNF and IL-1ß. A total of 354 gene ontology terms were identified by Gene ontology (GO) enrichment analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis results showed that SA was closely associated with TNF signaling pathways in the treatment of RA. Furthermore, according to the predicted results of network pharmacology, we established a rat model of Adjuvant arthritis (AA) for in vivo experiments. Analysis showed that each treatment group led to an improvement in paw swelling, immune organ coefficient and synovial tissue morphology in AA rats to different degrees, inhibit the expression levels of IL-1ß, TNF-α and IL-6, upregulated the levels of Fas, Bax and Caspase 3, down-regulated the expression levels of Fas-L, Bcl-2 and p53. CONCLUSION: SA has an anti-RA effect, the mechanism underlying the therapeutic action of SA in AA rats was related to the regulation of apoptosis signaling pathways.

Application of fluorescence micro-optical sectioning tomography in the cerebrovasculature and applicable vascular labeling methods.

Fluorescence micro-optical sectioning tomography (fMOST) is a three-dimensional (3d) imaging method at the mesoscopic level. The whole-brain of mice can be imaged at a high resolution of 0.32 × 0.32 × 1.00 µm3. It is useful for revealing the fine morphology of intact organ tissue, even for positioning the single vessel connected with a complicated vascular network across different brain regions in the whole mouse brain. Featuring its 3d visualization of whole-brain cross-scale connections, fMOST has a vast potential to decipher brain function and diseases. This article begins with the background of fMOST technology including a widespread 3D imaging methods comparison and the basic technical principal illustration, followed by the application of fMOST in cerebrovascular research and relevant vascular labeling techniques applicable to different scenarios.

Flexible Ultrasound Transducer With Embedded Optical Shape Sensing Fiber for Biomedical Imaging Applications.

Flexible ultrasound transducers (FUTs), capable of conforming to irregular surfaces, have become a research hotspot in the field of medical imaging. With these transducers, high-quality ultrasound images can be obtained only if strict design criteria are fulfilled. Moreover, the relative positions of array elements must be determined, which are important for ultrasound beamforming and image reconstruction. These two major characteristics present great challenges to the design and fabrication of FUTs compared to that for traditional rigid probes. In this study, an optical shape-sensing fiber was embedded into a 128-element flexible linear array transducer to acquire the real-time relative positions of array elements to produce high-quality ultrasound images. Minimum concave and convex bend diameters of approximately 20 and 25 mm, respectively, were achieved. The transducer was flexed 2000 times, and yet no obvious damage was observed. Stable electrical and acoustic responses confirmed its mechanical integrity. The developed FUT exhibited an average center frequency of 6.35 MHz, and average -6-dB bandwidth of 69.2%. The array profile and element positions measured by the optic shape-sensing system were instantly transferred to the imaging system. Phantom experiments for both spatial resolution and contrast-to-noise ratio proved that FUTs can maintain satisfactory imaging capability despite bending to sophisticated geometries. Finally, color Doppler images and Doppler spectra of the peripheral arteries of healthy volunteers were obtained in real time.

Disrupted Topological Organization of White Matter Network in Angelman Syndrome.

BACKGROUND: Angelman syndrome (AS) is a genetic disorder that affects neurodevelopment. The investigation of changes in the brain white matter network, which would contribute to a better understanding of the pathogenesis of AS brain, was lacking. PURPOSE: To investigate both local and global alterations of white matter in patients with AS. STUDY TYPE: Prospective. SUBJECTS: A total of 29 AS patients (6.6 ± 1.4 years, 15 [52%] females) and 19 age-matched healthy controls (HC) (7.0 ± 1.5 years, 10 [53%] females). FIELD STRENGTH/SEQUENCE: A 3-T, three-dimensional (3D) T1-weighted imaging by using gradient-echo-based sequence, single shell diffusion tensor imaging by using spin-echo-based echo-planar imaging. ASSESSMENT: Network metrics including global efficiency (Eg ), local efficiency (Eloc ), small world coefficient (Swc), rich-club coefficient (Φ), and nodal degree (ND) were estimated from diffusion MR (dMR) data. Connections among highly connected (hub) regions and less connected (peripheral) regions were also assessed. Correlation between the topological parameters and age for each group was also calculated to assess the development of the brain. STATISTICAL TESTS: Linear regression model, permutation test. P values estimated from the regression model for each brain region were adjusted by false discovery rate (FDR) correction. RESULTS: AS patients showed significantly lower Eg and higher swc compared to HC. Φn significantly increased at higher k-levels in AS patients. In addition, the connections among hub regions and peripheral regions were significantly interrupted in AS patients. DATA CONCLUSION: The AS brain showed diminished connectivity, reflected by reduced network efficiency compared to HC. Compared to densely connected regions, less connected regions were more vulnerable in AS. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Association of Serum Interleukin-8 and Serum Amyloid A With Anxiety Symptoms in Patients With Cerebral Small Vessel Disease.

Objective: Cerebral small vessel disease (CSVD) is a clinical syndrome caused by pathological changes in small vessels. Anxiety is a common symptom of CSVD. Previous studies have reported the association between inflammatory factors and anxiety in other diseases, but this association in patients with CSVD remains uncovered. Our study aimed to investigate whether serum inflammatory factors correlated with anxiety in patients with CSVD. Methods: A total of 245 CSVD patients confirmed using brain magnetic resonance imaging (MRI) were recruited from December 2019 to December 2021. Hamilton Anxiety Rating Scale (HAMA) was used to assess the anxiety symptoms of CSVD patients. Patients with HAMA scores ≥7 were considered to have anxiety symptoms. The serum levels of interleukin-1ß (IL-1ß), IL-2R, IL-6, IL-8, IL-10, tumor necrosis factor-α (TNF-α), serum amyloid A (SAA), C-reactive protein (CRP), high-sensitivity C-reactive protein (hs-CRP) and erythrocyte sedimentation rate (ESR) were detected. We compared levels of inflammatory factors between the anxiety and non-anxiety groups. Logistic regression analyses examined the correlation between inflammatory factors and anxiety symptoms. We further performed a gender subgroup analysis to investigate whether this association differed by gender. Results: In the fully adjusted multivariate logistic regression analysis model, we found that lower levels of IL-8 were linked to a higher risk of anxiety symptoms. Moreover, higher levels of SAA were linked to a lower risk of anxiety symptoms. Our study identified sex-specific effects, and the correlation between IL-8 and anxiety symptoms remained significant among males, while the correlation between SAA and anxiety symptoms remained significant among females. Conclusions: In this study, we found a suggestive association between IL-8, SAA, and anxiety symptoms in CSVD participants. Furthermore, IL-8 and SAA may have a sex-specific relationship with anxiety symptoms.

Multiple B-Value Model-Based Residual Network (MORN) for Accelerated High-Resolution Diffusion-Weighted Imaging.

Single-Shot Echo Planar Imaging (SSEPI) based Diffusion Weighted Imaging (DWI) has shortcomings such as low resolution and severe distortions. In contrast, Multi-Shot EPI (MSEPI) provides optimal spatial resolution but increases scan time. This study proposed a Multiple b-value mOdel-based Residual Network (MORN) model to reconstruct multiple b-value high-resolution DWI from undersampled k-space data simultaneously. We incorporated Parallel Imaging (PI) into a residual U-net to reconstruct multiple b-value multi-coil data with the supervision of MUltiplexed Sensitivity-Encoding (MUSE) reconstructed Multi-Shot DWI (MSDWI). Moreover, asymmetric concatenations among different b-values and the combined loss to back propagate helped the feature transfer. After training and validation of the MORN in a dataset of 32 healthy cases, additional assessments were performed on 6 patients with different tumor types. The experimental results demonstrated that the MORN model outperformed conventional PI reconstruction (i.e. SENSE) and two state-of-the-art deep learning methods (SENSE-GAN and VSNet) in terms of PSNR (Peak Signal-to-Noise Ratio), SSIM (Structual SIMilarity) and apparent diffusion coefficient maps. In addition, using the pre-trained model under DWI, the MORN achieved consistent fractional anisotrophy and mean diffusivity reconstructed from multiple diffusion directions. Hence, the proposed method shows potential in clinical application according to the observations on tumor patients as well as images of multiple diffusion directions.

Modification of cerebrovascular morphologies during different stages of life.

To expand previous understanding of age-related vascular changes, we examined the association between aging and characteristics of cerebral arteries among 1133 participants aged 35 to 75 years recruited from Shanghai, China. Characteristics of the cerebral vessels including arterial branch density, mean radius, and mean tortuosity were quantified using MR angiography. The radius, tortuosity, and length of the basilar artery (BA) and the M1 segment of middle cerebral artery (MCA) were also accessed. Linear regression model was used to examine the association between age and vasculature features. The sample was divided into four subgroups by age and the association was analyzed in each subgroup. Age was found to be a significant predictor for cerebrovascular modifications after adjusting for vascular risk factors. Further analysis in subgroup revealed that the associations were due to the predominate effect of the vascular modifications happened during the younger years (35-54 years). The radius of either BA or MCA was associated with aging only in subjects aged 45-54 years. In conclusion, rapid alterations in all three morphological features assessed have been noticed to be associated with aging in the 45-54 subgroup, suggesting the potential importance of the 5th decade for early preservation method for vascular aging.

EPI phase error correction with deep learning (PEC-DL) at 7 T.

PURPOSE: The phase mismatch between odd and even echoes in EPI causes Nyquist ghost artifacts. Existing ghost correction methods often suffer from severe residual artifacts and are ineffective with k-space undersampling data. This study proposed a deep learning-based method (PEC-DL) to correct phase errors for DWI at 7 Tesla. METHODS: The acquired k-space data were divided into 2 independent undersampled datasets according to their readout polarities. Then the proposed PEC-DL network reconstructed 2 ghost-free images using the undersampled data without calibration and navigator data. The network was trained with fully sampled images and applied to two- and fourfold accelerated data. Healthy volunteers and patients with Moyamoya disease were recruited to validate the efficacy of the PEC-DL method. RESULTS: The PEC-DL method was capable to mitigate the ghost artifacts in DWI in healthy volunteers as well as patients with Moyamoya disease. The fourfold accelerated results showed much less distortion in the lesions of the Moyamoya patient using high b-value DWI and the corresponding ADC maps. The ghost-to-signal ratios were significantly lower in PEC-DL images compared to conventional linear phase corrections, mini-entropy, and PEC-GRAPPA algorithms. CONCLUSION: The proposed method can effectively eliminate ghost artifacts for full sampled and up to fourfold accelerated EPI data without calibration and navigator data.

Optical Property Mapping of Apples and the Relationship With Quality Properties.

This paper reports on the measurement of optical property mapping of apples at the wavelengths of 460, 527, 630, and 710 nm using spatial-frequency domain imaging (SFDI) technique, for assessing the soluble solid content (SSC), firmness, and color parameters. A laboratory-based multispectral SFDI system was developed for acquiring SFDI of 140 "Golden Delicious" apples, from which absorption coefficient (µ a ) and reduced scattering coefficient (µ s ') mappings were quantitatively determined using the three-phase demodulation coupled with curve-fitting method. There was no noticeable spatial variation in the optical property mapping based on the resulting effect of different sizes of the region of interest (ROI) on the average optical properties. Support vector machine (SVM), multiple linear regression (MLR), and partial least square (PLS) models were developed based on µ a , µ s ' and their combinations (µ a × µ s ' and µ eff ) for predicting apple qualities, among which SVM outperformed the best. Better prediction results for quality parameters based on the µ a were observed than those based on the µ s ', and the combinations further improved the prediction performance, compared to the individual µ a or µ s '. The best prediction models for SSC and firmness parameters [slope, flesh firmness (FF), and maximum force (Max.F)] were achieved based on the µ a × µ s ', whereas those for color parameters of b* and C* were based on the µ eff , with the correlation coefficients of prediction as 0.66, 0.68, 0.73, 0.79, 0.86, and 0.86, respectively.

Day to Day Blood Pressure Variability Associated With Cerebral Arterial Dilation and White Matter Hyperintensity.

BACKGROUND: Previous studies suggested blood pressure variability (BPV) might help reveal interactions between blood pressure fluctuation and white matter lesions, and the impact of elevated BPV on white matter hyperintensity (WMH) or cerebral arterial dilation is unclear. METHODS: This retrospective observational study involved 2634 stroke-free individuals (68.6±11.1 years, 50.3% female), who underwent magnetic resonance imaging and magnetic resonance angiography scans, from a single center in Shanghai, China. Measurements for variability of blood pressure were made based on 7 days blood pressure recordings. WMHs were quantified from T2-FLAIR images and further classified as periventricular WMH or deep WMH. M1 segment of middle cerebral artery dilation was assessed from magnetic resonance angiography images. General linear model was used to examine the associations. RESULTS: Both increased systolic and diastolic BPV were associated with increased WMH volume (systolic: ß=0.02 [95% CI, 0.004-0.03], P=0.01; diastolic: ß=0.05 [95% CI, 0.03-0.08], P<0.001). Only periventricular WMH was associated with BPV (systolic: ß=0.02 [95% CI, 0.005-0.04], P=0.01; diastolic: ß=0.06 [95% CI, 0.04-0.09], P<0.001). MCA dilation was found in 125 individuals (4.75%). Systolic BPV was associated with MCA dilation only in the hypertensive individuals (ß=0.11 [95% CI, 0.06-0.17], P<0.001). Increased WMH volume was found associated with dilated MCA (ß=0.17 [95% CI, 0.11-0.23], P<0.001). CONCLUSIONS: Increased BPV might be one of the pathophysiological phenomena involving in the small vessel disease independent of hypertension. Increased BPV might independently contribute to intracranial arterial dilation. Management of BPV might be a target to preserve cerebrovascular wellness.

High On-Treatment Platelet Reactivity as Predictor of Long-term Clinical Outcomes in Stroke Patients with Antiplatelet Agents.

The purpose was to explore the value of high on-treatment platelet reactivity (HTPR) in predicting long-term clinical outcomes for stroke patients. The platelet reactivity was assayed after being treated with either 75 mg clopidogrel or 100 mg aspirin daily with VerifyNow System in stroke patients. HTPR for clopidogrel was defined as PRU ≥ 208, and that for aspirin was defined as ARU ≥ 550. CYP2C19 genotyping was performed using the Sequenom MassARRAY iPLEX platform. The primary endpoint was a composite of recurrent ischemic stroke, transient ischemic attack, myocardial infarction, or ischemic vascular death. The safety endpoint was bleeding. In the clopidogrel group, among 345 patients recruited, 174 of them were categorized as HTPR. A total of 270 patients were followed up for 54 months. There was a significant association between HTPR and the primary endpoint (HRadj 2.13 [95% CI, 1.43-3.15], p < 0.001). Among the 314 participants genotyped for CYP2C19, 187 (59.6%) were classified as CYP2C19 loss-of-function allele carriers. Patients with at least 1 loss-of-function allele were more likely to present with HTPR (ORadj 2.61 [95%CI, 1.43-4.77], p = 0.008), and had a higher risk of the primary endpoint (HRadj 2.05 [95% CI, 1.30, 3.25], p = 0.002). In the aspirin group, among 140 patients recruited, 28 of them were categorized as HTPR. A total of 121 patients were followed up for 30 months. Similarly, there was a significant association between HTPR and the primary endpoint (HRadj 3.28 [95% CI, 1.52-7.71], p = 0.002). HTPR is an independent risk factor for ischemic events during long-term follow-up in stroke patients. Platelet function testing is helpful to evaluate the effect of antiplatelet therapy for stroke patients.

Deep learning based multiplexed sensitivity-encoding (DL-MUSE) for high-resolution multi-shot DWI.

PURPOSE: A phase correction method for high-resolution multi-shot (MSH) diffusion weighted imaging (DWI) is proposed. The efficacy and generalization capability of the method were validated on both healthy volunteers and patients. THEORY AND METHODS: Conventionally, inter-shot phase variations for MSH echo-planar imaging (EPI) DWI are corrected by model-based algorithms. However, many acquisition imperfections are hard to measure accurately for conventional model-based methods, making the phase estimation and artifacts suppression unreliable. We propose a deep learning multiplexed sensitivity-encoding (DL-MUSE) framework to improve the phase estimations based on convolutional neural network (CNN) reconstruction. Aliasing-free single-shot (SSH) DW images, which have been used routinely in clinical settings, were used for training before the aliasing correction of MSH-DWI images. A dual-channel U-net comprising multiple convolutional layers was used for the phase estimation of MSH-EPI. The network was trained on a dataset containing 30 healthy volunteers and tested on another dataset of 52 healthy subjects and 15 patients with lesions or tumors with different shot numbers (4, 6 and 8). To further validate the generalization capability of our network, we acquired a dataset with different numbers of shots, TEs, partial Fourier factors, resolutions, ETLs, FOVs, coil numbers, and image orientations from two sites. We also compared the reconstruction performance of our proposed method with that of the conventional MUSE and SSH-EPI qualitatively and quantitatively. RESULTS: Our results show that DL-MUSE is capable of correcting inter-shot phase errors with high and robust performance. Compared to conventional model-based MUSE, our method, by applying deep learning-based phase corrections, showed reduced distortion, noise level, and signal loss in high b-value DWIs. The improvements of image quality become more evident as the shot number increases from 4 to 8, especially in those central regions of the images, where g-factor artifacts are severe. Furthermore, the proposed method could provide the information about the orientation of the white matter with better consistency and achieve finer fibers delineation compared to the SSH-EPI method. Besides, the experiments on volunteers and patients from two different sites demonstrated the generalizability of our proposed method preliminarily. CONCLUSION: A deep learning-based reconstruction algorithm for MSH-EPI images, which helps improve image quality greatly, was proposed. Results from healthy volunteers and tumor patients demonstrated the feasibility and generalization performances of our method for high-resolution MSH-EPI DWI, which can be used for routine clinical applications as well as neuroimaging research.