PENCIL imaging: A novel approach for neuromelanin sensitive MRI in Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) is associated with the loss of neuromelanin (NM) and increased iron in the substantia nigra (SN). Magnetization transfer contrast (MTC) is widely used for NM visualization but has limitations in brain coverage and scan time. This study aimed to develop a new approach called Proton-density Enhanced Neuromelanin Contrast in Low flip angle gradient echo (PENCIL) imaging to visualize NM in the SN. METHODS: This study included 30 PD subjects and 50 healthy controls (HCs) scanned at 3T. PENCIL and MTC images were acquired. NM volume in the SN pars compacta (SNpc), normalized image contrast (Cnorm), and contrast-to-noise ratio (CNR) were calculated. The change of NM volume in the SNpc with age was analyzed using the HC data. A group analysis compared differences between PD subjects and HCs. Receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculations were used to evaluate the diagnostic performance of NM volume and CNR in the SNpc. RESULTS: PENCIL provided similar visualization and structural information of NM compared to MTC. In HCs, PENCIL showed higher NM volume in the SNpc than MTC, but this difference was not observed in PD subjects. PENCIL had higher CNR, while MTC had higher Cnorm. Both methods revealed a similar pattern of NM volume in SNpc changes with age. There were no significant differences in AUCs between NM volume in SNpc measured by PENCIL and MTC. Both methods exhibited comparable diagnostic performance in this regard. CONCLUSIONS: PENCIL imaging provided improved CNR compared to MTC and showed similar diagnostic performance for differentiating PD subjects from HCs. The major advantage is PENCIL has rapid whole-brain coverage and, when using STAGE imaging, offers a one-stop quantitative assessment of tissue properties.

Enhancing Nigrosome-1 Sign Identification via Interpretable AI using True Susceptibility Weighted Imaging.

BACKGROUND: Nigrosome 1 (N1), the largest nigrosome region in the ventrolateral area of the substantia nigra pars compacta, is identifiable by the "N1 sign" in long echo time gradient echo MRI. The N1 sign's absence is a vital Parkinson's disease (PD) diagnostic marker. However, it is challenging to visualize and assess the N1 sign in clinical practice. PURPOSE: To automatically detect the presence or absence of the N1 sign from true susceptibility weighted imaging by using deep-learning method. STUDY TYPE: Prospective. POPULATION/SUBJECTS: 453 subjects, including 225 PD patients, 120 healthy controls (HCs), and 108 patients with other movement disorders, were prospectively recruited including 227 males and 226 females. They were divided into training, validation, and test cohorts of 289, 73, and 91 cases, respectively. FIELD STRENGTH/SEQUENCE: 3D gradient echo SWI sequence at 3T; 3D multiecho strategically acquired gradient echo imaging at 3T; NM-sensitive 3D gradient echo sequence with MTC pulse at 3T. ASSESSMENT: A neuroradiologist with 5 years of experience manually delineated substantia nigra regions. Two raters with 2 and 36 years of experience assessed the N1 sign on true susceptibility weighted imaging (tSWI), QSM with high-pass filter, and magnitude data combined with MTC data. We proposed NINet, a neural model, for automatic N1 sign identification in tSWI images. STATISTICAL TESTS: We compared the performance of NINet to the subjective reference standard using Receiver Operating Characteristic analyses, and a decision curve analysis assessed identification accuracy. RESULTS: NINet achieved an area under the curve (AUC) of 0.87 (CI: 0.76-0.89) in N1 sign identification, surpassing other models and neuroradiologists. NINet localized the putative N1 sign within tSWI images with 67.3% accuracy. DATA CONCLUSION: Our proposed NINet model's capability to determine the presence or absence of the N1 sign, along with its localization, holds promise for enhancing diagnostic accuracy when evaluating PD using MR images. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Diagnosing Parkinson's disease by combining neuromelanin and iron imaging features using an automated midbrain template approach.

BACKGROUND AND PURPOSE: Early diagnosis of Parkinson's disease (PD) is still a clinical challenge. Most previous studies using manual or semi-automated methods for segmenting the substantia nigra (SN) are time-consuming and, despite raters being well-trained, individual variation can be significant. In this study, we used a template-based, automatic, SN subregion segmentation pipeline to detect the neuromelanin (NM) and iron features in the SN and SN pars compacta (SNpc) derived from a single 3D magnetization transfer contrast (MTC) gradient echo (GRE) sequence in an attempt to develop a comprehensive imaging biomarker that could be used to diagnose PD. MATERIALS AND METHODS: A total of 100 PD patients and 100 age- and sex-matched healthy controls (HCs) were imaged on a 3T scanner. NM-based SN (SNNM) boundaries and iron-based SN (SNQSM) boundaries and their overlap region (representing the SNpc) were delineated automatically using a template-based SN subregion segmentation approach based on quantitative susceptibility mapping (QSM) and NM images derived from the same MTC-GRE sequence. All PD and HC subjects were evaluated for the nigrosome-1 (N1) sign by two raters independently. Receiver Operating Characteristic (ROC) analyses were performed to evaluate the utility of SNNM volume, SNQSM volume, SNpc volume and iron content with a variety of thresholds as well as the N1 sign in diagnosing PD. Correlation analyses were performed to study the relationship between these imaging measures and the clinical scales in PD. RESULTS: In this study, we verified the value of the fully automatic template based midbrain deep gray matter mapping approach in differentiating PD patients from HCs. The automatic segmentation of the SN in PD patients led to satisfactory DICE similarity coefficients and volume ratio (VR) values of 0.81 and 1.17 for the SNNM, and 0.87 and 1.05 for the SNQSM, respectively. For the HC group, the average DICE similarity coefficients and VR values were 0.85 and 0.94 for the SNNM, and 0.87 and 0.96 for the SNQSM, respectively. The SNQSM volume tended to decrease with age for both the PD and HC groups but was more severe for the PD group. For diagnosing PD, the N1 sign performed reasonably well by itself (Area Under the Curve (AUC) = 0.783). However, combining the N1 sign with the other quantitative measures (SNNM volume, SNQSM volume, SNpc volume and iron content) resulted in an improved diagnosis of PD with an AUC as high as 0.947 (using an SN threshold of 50ppb and an NM threshold of 0.15). Finally, the SNQSM volume showed a negative correlation with the MDS-UPDRS III (R2 = 0.1, p = 0.036) and the Hoehn and Yahr scale (R2 = 0.04, p = 0.013) in PD patients. CONCLUSION: In summary, this fully automatic template based deep gray matter mapping approach performs well in the segmentation of the SN and its subregions for not only HCs but also PD patients with SN degeneration. The combination of the N1 sign with other quantitative measures (SNNM volume, SNQSM volume, SNpc volume and iron content) resulted in an AUC of 0.947 and provided a comprehensive set of imaging biomarkers that, potentially, could be used to diagnose PD clinically.

Visualizing the deep cerebellar nuclei using quantitative susceptibility mapping: An application in healthy controls, Parkinson's disease patients and essential tremor patients.

The visualization and identification of the deep cerebellar nuclei (DCN) (dentate [DN], interposed [IN] and fastigial nuclei [FN]) are particularly challenging. We aimed to visualize the DCN using quantitative susceptibility mapping (QSM), predict the contrast differences between QSM and T2* weighted imaging, and compare the DCN volume and susceptibility in movement disorder populations and healthy controls (HCs). Seventy-one Parkinson's disease (PD) patients, 39 essential tremor patients, and 80 HCs were enrolled. The PD patients were subdivided into tremor dominant (TD) and postural instability/gait difficulty (PIGD) groups. A 3D strategically acquired gradient echo MR imaging protocol was used for each subject to obtain the QSM data. Regions of interest were drawn manually on the QSM data to calculate the volume and susceptibility. Correlation analysis between the susceptibility and either age or volume was performed and the intergroup differences of the volume and magnetic susceptibility in all the DCN structures were evaluated. For the most part, all the DCN structures were clearly visualized on the QSM data. The susceptibility increased as a function of volume for both the HC group and disease groups in the DN and IN (p < .001) but not the FN (p = .74). Only the volume of the FN in the TD-PD group was higher than that in the HCs (p = .012), otherwise, the volume and susceptibility among these four groups did not differ significantly. In conclusion, QSM provides clear visualization of the DCN structures. The results for the volume and susceptibility of the DCN can be used as baseline references in future studies of movement disorders.

An automatic interpretable deep learning pipeline for accurate Parkinson's disease diagnosis using quantitative susceptibility mapping and T1-weighted images.

Parkinson's disease (PD) diagnosis based on magnetic resonance imaging (MRI) is still challenging clinically. Quantitative susceptibility maps (QSM) can potentially provide underlying pathophysiological information by detecting the iron distribution in deep gray matter (DGM) nuclei. We hypothesized that deep learning (DL) could be used to automatically segment all DGM nuclei and use relevant features for a better differentiation between PD and healthy controls (HC). In this study, we proposed a DL-based pipeline for automatic PD diagnosis based on QSM and T1-weighted (T1W) images. This consists of (1) a convolutional neural network model integrated with multiple attention mechanisms which simultaneously segments caudate nucleus, globus pallidus, putamen, red nucleus, and substantia nigra from QSM and T1W images, and (2) an SE-ResNeXt50 model with an anatomical attention mechanism, which uses QSM data and the segmented nuclei to distinguish PD from HC. The mean dice values for segmentation of the five DGM nuclei are all >0.83 in the internal testing cohort, suggesting that the model could segment brain nuclei accurately. The proposed PD diagnosis model achieved area under the the receiver operating characteristic curve (AUCs) of 0.901 and 0.845 on independent internal and external testing cohorts, respectively. Gradient-weighted class activation mapping (Grad-CAM) heatmaps were used to identify contributing nuclei for PD diagnosis on patient level. In conclusion, the proposed approach can potentially be used as an automatic, explainable pipeline for PD diagnosis in a clinical setting.

Subthalamic and pallidal stimulation in Parkinson's disease induce distinct brain topological reconstruction.

The subthalamic nucleus (STN) and globus pallidus internus (GPi) are the two most common and effective target brain areas for deep brain stimulation (DBS) treatment of advanced Parkinson's disease. Although DBS has been shown to restore functional neural circuits of this disorder, the changes in topological organization associated with active DBS of each target remain unknown. To investigate this, we acquired resting-state functional magnetic resonance imaging (fMRI) data from 34 medication-free patients with Parkinson's disease that had DBS electrodes implanted in either the subthalamic nucleus or internal globus pallidus (n = 17 each), in both ON and OFF DBS states. Sixteen age-matched healthy individuals were used as a control group. We evaluated the regional information processing capacity and transmission efficiency of brain networks with and without stimulation, and recorded how stimulation restructured the brain network topology of patients with Parkinson's disease. For both targets, the variation of local efficiency in motor brain regions was significantly correlated (p < 0.05) with improvement rate of the Uniform Parkinson's Disease Rating Scale-III scores, with comparable improvements in motor function for the two targets. However, non-motor brain regions showed changes in topological organization during active stimulation that were target-specific. Namely, targeting the STN decreased the information transmission of association, limbic and paralimbic regions, including the inferior frontal gyrus angle, insula, temporal pole, superior occipital gyri, and posterior cingulate, as evidenced by the simultaneous decrease of clustering coefficient and local efficiency. GPi-DBS had a similar effect on the caudate and lenticular nuclei, but enhanced information transmission in the cingulate gyrus. These effects were not present in the DBS-OFF state for GPi-DBS, but persisted for STN-DBS. Our results demonstrate that DBS to the STN and GPi induce distinct brain network topology reconstruction patterns, providing innovative theoretical evidence for deciphering the mechanism through which DBS affects disparate targets in the human brain.

Automatic detection of neuromelanin and iron in the midbrain nuclei using a magnetic resonance imaging-based brain template.

Parkinson disease (PD) is a chronic progressive neurodegenerative disorder characterized pathologically by early loss of neuromelanin (NM) in the substantia nigra pars compacta (SNpc) and increased iron deposition in the substantia nigra (SN). Degeneration of the SN presents as a 50 to 70% loss of pigmented neurons in the ventral lateral tier of the SNpc at the onset of symptoms. Also, using magnetic resonance imaging (MRI), iron deposition and volume changes of the red nucleus (RN), and subthalamic nucleus (STN) have been reported to be associated with disease status and rate of progression. Further, the STN serves as an important target for deep brain stimulation treatment in advanced PD patients. Therefore, an accurate in-vivo delineation of the SN, its subregions and other midbrain structures such as the RN and STN could be useful to better study iron and NM changes in PD. Our goal was to use an MRI template to create an automatic midbrain deep gray matter nuclei segmentation approach based on iron and NM contrast derived from a single, multiecho magnetization transfer contrast gradient echo (MTC-GRE) imaging sequence. The short echo TE = 7.5 ms data from a 3D MTC-GRE sequence was used to find the NM-rich region, while the second echo TE = 15 ms was used to calculate the quantitative susceptibility map for 87 healthy subjects (mean age ± SD: 63.4 ± 6.2 years old, range: 45-81 years). From these data, we created both NM and iron templates and calculated the boundaries of each midbrain nucleus in template space, mapped these boundaries back to the original space and then fine-tuned the boundaries in the original space using a dynamic programming algorithm to match the details of each individual's NM and iron features. A dual mapping approach was used to improve the performance of the morphological mapping of the midbrain of any given individual to the template space. A threshold approach was used in the NM-rich region and susceptibility maps to optimize the DICE similarity coefficients and the volume ratios. The results for the NM of the SN as well as the iron containing SN, STN, and RN all indicate a strong agreement with manually drawn structures. The DICE similarity coefficients and volume ratios for these structures were 0.85, 0.87, 0.75, and 0.92 and 0.93, 0.95, 0.89, 1.05, respectively, before applying any threshold on the data. Using this fully automatic template-based deep gray matter mapping approach, it is possible to accurately measure the tissue properties such as volumes, iron content, and NM content of the midbrain nuclei.

Speech silence character as a diagnostic biomarker of early cognitive decline and its functional mechanism: a multicenter cross-sectional cohort study.

BACKGROUND: Language deficits frequently occur during the prodromal stages of Alzheimer's disease (AD). However, the characteristics of linguistic impairment and its underlying mechanism(s) remain to be explored for the early diagnosis of AD. METHODS: The percentage of silence duration (PSD) of 324 subjects was analyzed, including patients with AD, amnestic mild cognitive impairment (aMCI), and normal controls (NC) recruited from the China multi-center cohort, and the diagnostic efficiency was replicated from the Pitt center cohort. Furthermore, the specific language network involved in the fragmented speech was analyzed using task-based functional magnetic resonance. RESULTS: In the China cohort, PSD increased significantly in aMCI and AD patients. The area under the curve of the receiver operating characteristic curves is 0.74, 0.84, and 0.80 in the classification of NC/aMCI, NC/AD, and NC/aMCI+AD. In the Pitt center cohort, PSD was verified as a reliable diagnosis biomarker to differentiate mild AD patients from NC. Next, in response to fluency tasks, clusters in the bilateral inferior frontal gyrus, precentral gyrus, left inferior temporal gyrus, and inferior parietal lobule deactivated markedly in the aMCI/AD group (cluster-level P < 0.05, family-wise error (FWE) corrected). In the patient group (AD+aMCI), higher activation level of the right pars triangularis was associated with higher PSD in in both semantic and phonemic tasks. CONCLUSIONS: PSD is a reliable diagnostic biomarker for the early stage of AD and aMCI. At as early as aMCI phase, the brain response to fluency tasks was inhibited markedly, partly explaining why PSD was elevated simultaneously.

Loss of 2 Akt (Protein Kinase B) Isoforms in Hematopoietic Cells Diminished Monocyte and Macrophage Survival and Reduces Atherosclerosis in Ldl Receptor-Null Mice.

Objective- Macrophages express 3 Akt (protein kinase B) isoforms, Akt1, Akt2, and Akt3, which display isoform-specific functions but may be redundant in terms of Akt survival signaling. We hypothesize that loss of 2 Akt isoforms in macrophages will suppress their ability to survive and modulate the development of atherosclerosis. Approach and Results- To test this hypothesis, we reconstituted male Ldlr-/- mice with double Akt2/Akt3 knockout hematopoietic cells expressing only the Akt1 isoform (Akt1only). There were no differences in body weight and plasma lipid levels between the groups after 8 weeks of the Western diet; however, Akt1only→ Ldlr-/- mice developed smaller (57.6% reduction) atherosclerotic lesions with more apoptotic macrophages than control mice transplanted with WT (wild type) cells. Next, male and female Ldlr-/- mice were reconstituted with double Akt1/Akt2 knockout hematopoietic cells expressing the Akt3 isoform (Akt3only). Female and male Akt3only→ Ldlr-/- recipients had significantly smaller (61% and 41%, respectively) lesions than the control WT→ Ldlr-/- mice. Loss of 2 Akt isoforms in hematopoietic cells resulted in markedly diminished levels of white blood cells, B cells, and monocytes and compromised viability of monocytes and peritoneal macrophages compared with WT cells. In response to lipopolysaccharides, macrophages with a single Akt isoform expressed low levels of inflammatory cytokines; however, Akt1only macrophages were distinct in expressing high levels of antiapoptotic Il10 compared with WT and Akt3only cells. Conclusions- Loss of 2 Akt isoforms in hematopoietic cells, preserving only a single Akt1 or Akt3 isoform, markedly compromises monocyte and macrophage viability and diminishes early atherosclerosis in Ldlr-/- mice.

Macrophage IKKα Deficiency Suppresses Akt Phosphorylation, Reduces Cell Survival, and Decreases Early Atherosclerosis.

OBJECTIVE: The IκB kinase (IKK) is an enzyme complex that initiates the nuclear factor κB transcription factor cascade, which is important in regulating multiple cellular responses. IKKα is directly associated with 2 major prosurvival pathways, PI3K/Akt and nuclear factor κB, but its role in cell survival is not clear. Macrophages play critical roles in the pathogenesis of atherosclerosis, yet the impact of IKKα signaling on macrophage survival and atherogenesis remains unclear. APPROACH AND RESULTS: Here, we demonstrate that genetic IKKα deficiency, as well as pharmacological inhibition of IKK, in mouse macrophages significantly reduces Akt S(473) phosphorylation, which is accompanied by suppression of mTOR complex 2 signaling. Moreover, IKKα null macrophages treated with lipotoxic palmitic acid exhibited early exhaustion of Akt signaling compared with wild-type cells. This was accompanied by a dramatic decrease in the resistance of IKKα(-/-) monocytes and macrophages to different proapoptotic stimuli compared with wild-type cells. In vivo, IKKα deficiency increased macrophage apoptosis in atherosclerotic lesions and decreased early atherosclerosis in both female and male low-density lipoprotein receptor (LDLR)(-/-) mice reconstituted with IKKα(-/-) hematopoietic cells and fed with the Western diet for 8 weeks compared with control LDLR(-/-) mice transplanted with wild-type cells. CONCLUSIONS: Hematopoietic IKKα deficiency in mouse suppresses Akt signaling, compromising monocyte/macrophage survival and this decreases early atherosclerosis.

Loss of Macrophage Low-Density Lipoprotein Receptor-Related Protein 1 Confers Resistance to the Antiatherogenic Effects of Tumor Necrosis Factor-α Inhibition.

OBJECTIVE: Antiatherosclerotic effects of tumor necrosis factor-α (TNF-α) blockade in patients with systemic inflammatory states are not conclusively demonstrated, which suggests that effects depend on the cause of inflammation. Macrophage LRP1 (low-density lipoprotein receptor-related protein 1) and apoE contribute to inflammation through different pathways. We studied the antiatherosclerosis effects of TNF-α blockade in hyperlipidemic mice lacking either LRP1 (MΦLRP1(-/-)) or apoE from macrophages. APPROACH AND RESULTS: Lethally irradiated low-density lipoprotein receptor (LDLR)(-/-) mice were reconstituted with bone marrow from either wild-type, MΦLRP1(-/-), apoE(-/-) or apoE(-/-)/MΦLRP1(-/-)(DKO) mice, and then treated with the TNF-α inhibitor adalimumab while fed a Western-type diet. Adalimumab reduced plasma TNF-α concentration, suppressed blood ly6C(hi) monocyte levels and their migration into the lesion, and reduced lesion cellularity and inflammation in both wild-type→LDLR(-/-) and apoE(-/-)→LDLR(-/-) mice. Overall, adalimumab reduced lesion burden by 52% to 57% in these mice. Adalimumab reduced TNF-α and blood ly6C(hi) monocyte levels in MΦLRP1(-/-)→LDLR(-/-) and DKO→LDLR(-/-) mice, but it did not suppress ly6C(hi) monocyte migration into the lesion or atherosclerosis progression. CONCLUSIONS: Our results show that TNF-α blockade exerts antiatherosclerotic effects that are dependent on the presence of macrophage LRP1.

Jnk1 Deficiency in Hematopoietic Cells Suppresses Macrophage Apoptosis and Increases Atherosclerosis in Low-Density Lipoprotein Receptor Null Mice.

OBJECTIVE: The c-Jun NH2-terminal kinases (JNK) are regulated by a wide variety of cellular stresses and have been implicated in apoptotic signaling. Macrophages express 2 JNK isoforms, JNK1 and JNK2, which may have different effects on cell survival and atherosclerosis. APPROACH AND RESULTS: To dissect the effect of macrophage JNK1 and JNK2 on early atherosclerosis, Ldlr(-/-) mice were reconstituted with wild-type, Jnk1(-/-), and Jnk2(-/-) hematopoietic cells and fed a high cholesterol diet. Jnk1(-/-)→Ldlr(-/-) mice have larger atherosclerotic lesions with more macrophages and fewer apoptotic cells than mice transplanted with wild-type or Jnk2(-/-) cells. Moreover, genetic ablation of JNK to a single allele (Jnk1(+/-)/Jnk2(-/-) or Jnk1(-/-)/Jnk2(+/-)) in marrow of Ldlr(-/-) recipients further increased atherosclerosis compared with Jnk1(-/-)→Ldlr(-/-) and wild-type→Ldlr(-/-) mice. In mouse macrophages, anisomycin-mediated JNK signaling antagonized Akt activity, and loss of Jnk1 gene obliterated this effect. Similarly, pharmacological inhibition of JNK1, but not JNK2, markedly reduced the antagonizing effect of JNK on Akt activity. Prolonged JNK signaling in the setting of endoplasmic reticulum stress gradually extinguished Akt and Bad activity in wild-type cells with markedly less effects in Jnk1(-/-) macrophages, which were also more resistant to apoptosis. Consequently, anisomycin increased and JNK1 inhibitors suppressed endoplasmic reticulum stress-mediated apoptosis in macrophages. We also found that genetic and pharmacological inhibition of phosphatase and tensin homolog abolished the JNK-mediated effects on Akt activity, indicating that phosphatase and tensin homolog mediates crosstalk between these pathways. CONCLUSIONS: Loss of Jnk1, but not Jnk2, in macrophages protects them from apoptosis, increasing cell survival, and this accelerates early atherosclerosis.

Local effects of human PCSK9 on the atherosclerotic lesion.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) promotes atherosclerosis by increasing low-density lipoprotein (LDL) cholesterol levels through degradation of hepatic LDL receptor (LDLR). Studies have described the systemic effects of PCSK9 on atherosclerosis, but whether PCSK9 has local and direct effects on the plaque is unknown. To study the local effect of human PCSK9 (hPCSK9) on atherosclerotic lesion composition, independently of changes in serum cholesterol levels, we generated chimeric mice expressing hPCSK9 exclusively from macrophages, using marrow from hPCSK9 transgenic (hPCSK9tg) mice transplanted into apoE(-/-) and LDLR(-/-) mice, which were then placed on a high-fat diet (HFD) for 8 weeks. We further characterized the effect of hPCSK9 expression on the inflammatory responses in the spleen and by mouse peritoneal macrophages (MPM) in vitro. We found that MPMs from transgenic mice express both murine (m) Pcsk9 and hPCSK9 and that the latter reduces macrophage LDLR and LRP1 surface levels. We detected hPCSK9 in the serum of mice transplanted with hPCSK9tg marrow, but did not influence lipid levels or atherosclerotic lesion size. However, marrow-derived PCSK9 progressively accumulated in lesions of apoE(-/-) recipient mice, while increasing the infiltration of Ly6C(hi) inflammatory monocytes by 32% compared with controls. Expression of hPCSK9 also increased CD11b- and Ly6C(hi) -positive cell numbers in spleens of apoE(-/-) mice. In vitro, expression of hPCSK9 in LPS-stimulated macrophages increased mRNA levels of the pro-inflammatory markers Tnf and Il1b (40% and 45%, respectively) and suppressed those of the anti-inflammatory markers Il10 and Arg1 (30% and 44%, respectively). All PCSK9 effects were LDLR-dependent, as PCSK9 protein was not detected in lesions of LDLR(-/-) recipient mice and did not affect macrophage or splenocyte inflammation. In conclusion, PCSK9 directly increases atherosclerotic lesion inflammation in an LDLR-dependent but cholesterol-independent mechanism, suggesting that therapeutic PCSK9 inhibition may have vascular benefits secondary to LDL reduction.

Macrophage SR-BI mediates efferocytosis via Src/PI3K/Rac1 signaling and reduces atherosclerotic lesion necrosis.

Macrophage apoptosis and efferocytosis are key determinants of atherosclerotic plaque inflammation and necrosis. Bone marrow transplantation studies in ApoE- and LDLR-deficient mice revealed that hematopoietic scavenger receptor class B type I (SR-BI) deficiency results in severely defective efferocytosis in mouse atherosclerotic lesions, resulting in a 17-fold higher ratio of free to macrophage-associated dead cells in lesions containing SR-BI(-/-) cells, 5-fold more necrosis, 65.2% less lesional collagen content, nearly 7-fold higher dead cell accumulation, and 2-fold larger lesion area. Hematopoietic SR-BI deletion elicited a maladaptive inflammatory response [higher interleukin (IL)-1ß, IL-6, and TNF-α lower IL-10 and transforming growth factor ß]. Efferocytosis of apoptotic thymocytes was reduced by 64% in SR-BI(-/-) versus WT macrophages, both in vitro and in vivo. In response to apoptotic cells, macrophage SR-BI bound with phosphatidylserine and induced Src phosphorylation and cell membrane recruitment, which led to downstream activation of phosphoinositide 3-kinase (PI3K) and Ras-related C3 botulinum toxin substrate 1 (Rac1) for engulfment and clearance of apoptotic cells, as inhibition of Src decreased PI3K, Rac1-GTP, and efferocytosis in WT cells. Pharmacological inhibition of Rac1 reduced macrophage efferocytosis in a SR-BI-dependent fashion, and activation of Rac1 corrected the defective efferocytosis in SR-BI(-/-) macrophages. Thus, deficiency of macrophage SR-BI promotes defective efferocytosis signaling via the Src/PI3K/Rac1 pathway, resulting in increased plaque size, necrosis, and inflammation.

Identification of small proline-rich repeat protein 3 as a novel atheroprotective factor that promotes adaptive Akt signaling in vascular smooth muscle cells.

OBJECTIVE: Atherosclerosis is the primary driver of cardiovascular disease, the leading cause of death worldwide. Identification of naturally occurring atheroprotective genes has become a major goal for the development of interventions that will limit atheroma progression and associated adverse events. To this end, we have identified small proline-rich repeat protein (SPRR3) as selectively upregulated in vascular smooth muscle cells (VSMCs) of atheroma-bearing arterial tissue versus healthy arterial tissue. In this study, we sought to determine the role of SPRR3 in atheroma pathophysiology. APPROACH AND RESULTS: We found that atheroprone apolipoprotein E-null mice lacking SPRR3 developed significantly greater atheroma burden. To determine the cellular driver(s) of this increase, we evaluated SPRR3-dependent changes in bone marrow-derived cells, endothelial cells, and VSMCs. Bone marrow transplant of SPRR3-expressing cells into SPRR3(-/-)apolipoprotein E-deficient recipients failed to rescue atheroma burden. Similarly, endothelial cells did not exhibit a response to SPRR3 loss. However, atheromas from SPRR3-deficient mice exhibited increased TUNEL (terminal deoxynucleotidyl transferase dUTP nick end labeling)-positive VSMCs compared with control. Cell death in SPRR3-deficient VSMCs was significantly increased in vitro. Conversely, SPRR3-overexpressing VSMCs exhibited reduced apoptosis compared with control. We also observed a PI3K (phosphatidylinositol 3-kinase)/Akt-dependent positive association between SPRR3 expression and levels of active Akt in VSMCs. The survival advantage seen in SPRR3-overexpressing VSMCs was abrogated after the addition of a PI3K/Akt pathway inhibitor. CONCLUSIONS: These results indicate that SPRR3 protects the lesion from VSMC loss by promoting survival signaling in plaque VSMCs, thereby significantly decreasing atherosclerosis progression. As the first identified atheroma-specific VSMC prosurvival factor, SPRR3 represents a potential target for lesion-specific modulation of VSMC survival.

Macrophage deficiency of Akt2 reduces atherosclerosis in Ldlr null mice.

Macrophages play crucial roles in the formation of atherosclerotic lesions. Akt, a serine/threonine protein kinase B, is vital for cell proliferation, migration, and survival. Macrophages express three Akt isoforms, Akt1, Akt2, and Akt3, but the roles of Akt1 and Akt2 in atherosclerosis in vivo remain unclear. To dissect the impact of macrophage Akt1 and Akt2 on early atherosclerosis, we generated mice with hematopoietic deficiency of Akt1 or Akt2. After 8 weeks on Western diet, Ldlr(-/-) mice reconstituted with Akt1(-/-) fetal liver cells (Akt1(-/-)→Ldlr(-/-)) had similar atherosclerotic lesion areas compared with control mice transplanted with WT cells (WT→Ldlr(-/-)). In contrast, Akt2(-/-)→Ldlr(-/-) mice had dramatically reduced atherosclerotic lesions compared with WT→Ldlr(-/-) mice of both genders. Similarly, in the setting of advanced atherosclerotic lesions, Akt2(-/-)→Ldlr(-/-) mice had smaller aortic lesions compared with WT→Ldlr(-/-) and Akt1(-/-)→Ldlr(-/-) mice. Importantly, Akt2(-/-)→Ldlr(-/-) mice had reduced numbers of proinflammatory blood monocytes expressing Ly-6C(hi) and chemokine C-C motif receptor 2. Peritoneal macrophages isolated from Akt2(-/-) mice were skewed toward an M2 phenotype and showed decreased expression of proinflammatory genes and reduced cell migration. Our data demonstrate that loss of Akt2 suppresses the ability of macrophages to undergo M1 polarization reducing both early and advanced atherosclerosis.

Active Fault-Tolerant and Attack-Resilient Control for a Renewable Microgrid Against Power-Loss Faults and Data Integrity Attacks.

The next-generation power grid evolves from the development of fundamental cyber-physical energy systems called smart microgrids. In order to improve the reliability, safety, and security of smart microgrids and achieve a more cost-effective operation, innovative approaches for physical fault diagnosis and fault-tolerant control (FTC) as well as intrusion detection and attack-resilient control (ARC) should be investigated. Given that, this article considers a smart hybrid renewable-based microgrid with different types of distributed generation units, including solar photovoltaic (PV) array, wind turbines, and battery energy storage system. Novel active FTC and ARC strategies are designed for pulse-width modulation (PWM) converters at microgrid level. The proposed fault-tolerant controller is based on an optimal fuzzy gain-scheduling technique that is used to accommodate the adverse impacts of PV power-loss faults. Also, the proposed attack-resilient controller relies on the estimated values of sensor measurements during the occurrence of data integrity cyber-attacks. To access and evaluate the microgrid's real-time health status, both FTC and ARC strategies employ an integrated model-based intrusion detection and fault diagnosis (IDFD) system that is designed using a fuzzy modeling and identification technique. Finally, the effectiveness of the proposed solutions is demonstrated via a series of simulations in MATLAB/Simulink using an advanced microgrid benchmark.

Statistical Machine Learning for Power Flow Analysis Considering the Influence of Weather Factors on Photovoltaic Power Generation.

It is generally accepted that the impact of weather variation is gradually increasing in modern distribution networks with the integration of high-proportion photovoltaic (PV) power generation and weather-sensitive loads. This article analyzes power flow using a novel stochastic weather generator (SWG) based on statistical machine learning (SML). The proposed SML model, which incorporates generative adversarial networks (GANs), probability theory, and information theory, enables the generation and evaluation of simulated hourly weather data throughout the year. The GAN model captures various weather variation characteristics, including weather uncertainties, diurnal variations, and seasonal patterns. Compared to shallow learning models, the proposed deep learning model exhibits significant advantages in stochastic weather simulation. The simulated data generated by the proposed model closely resemble real data in terms of time-series regularity, integrity, and stochasticity. The SWG is applied to model PV power generation and weather-sensitive loads. Then, we actively conduct a power flow analysis (PFA) on a real distribution network in Guangdong, China, using simulated data for an entire year. The results provide evidence that the GAN-based SWG surpasses the shallow machine learning approach in terms of accuracy. The proposed model ensures accurate analysis of weather-related power flow and provides valuable insights for the analysis, planning, and design of distribution networks.

A fault isolation strategy for industrial processes using outlier-degree-based variable contributions.

In industrial process monitoring, it is always a challenging and practical problem to analyze the causes of the system fault by isolating true fault variables from vast amounts of process data. However, the phenomenon of smearing effect occurs by using the traditional contribution analysis-based isolation methods since the defined isolation indices of different variables affect each other. In this paper, a new fault isolation method is proposed based on local outlier factor and improved k-nearest neighbor rule aiming to improve the isolation accuracy. Firstly, the nearest neighbors of each sample are obtained along the direction of a specific variable. Based on the nearest neighbors, the outlier-degree value of the variable is calculated and regarded as the contribution of the variable. Then, the contribution of the variable in all samples are obtained in the same way, among which the maximum one is selected as the isolation threshold value of this variable. During the online monitoring, the contribution of the variable in the newly collected sample is calculated in real time. Once the contribution is greater than the threshold, the variable is judged to be the dominant factor causing the system fault. Two cases on numerical example and Tennessee Eastman process are conducted to evaluate the effectiveness of the proposed method.

Connectivity preservation control for multiple unmanned aerial vehicles in the presence of bounded actuation.

This paper proposes a novel multi-unmanned aerial vehicle (UAV) connectivity preservation controller, suitable for scenarios with bounded actuation and limited communication range. According to the hierarchical control strategy, controllers are designed separately for the position and attitude subsystems. A distributed position controller is developed, integrating an indirect coupling control mechanism. The innovative mechanism associates each UAV with a virtual proxy, facilitating connections among adjacent UAVs through these proxies. This structuring assists in managing the actuator saturation constraints effectively. The artificial potential function is utilized to preserve network connectivity and fulfill coordination among all virtual proxies. Additionally, an attitude controller designed for finite-time convergence guarantees that the attitude subsystem adheres precisely to the attitude specified by the distributed position controller. Simulation results validate the efficacy of this distributed formation controller with connectivity preservation under bounded actuation conditions. The simulation results confirm the effectiveness of the distributed connectivity preservation controller with bounded actuation.