Dilated cardiomyopathy (DCM) is characterized by reduced left ventricular ejection fraction (LVEF) and left or biventricular dilatation. We evaluated sex-specific associations of circulating proteins and metabolites with structural and functional heart parameters in DCM. Plasma samples (297 men, 71 women) were analyzed for proteins using Olink assays (targeted analysis) or LC-MS/MS (untargeted analysis), and for metabolites using LC MS/MS (Biocrates AbsoluteIDQ p180 Kit). Associations of proteins (n = 571) or metabolites (n = 163) with LVEF, measured left ventricular end diastolic diameter (LVEDDmeasured), and the dilation percentage of LVEDD from the norm (LVEDDacc. to HENRY) were examined in combined and sex-specific regression models. To disclose protein-metabolite relations, correlation analyses were performed. Associations between proteins, metabolites and LVEF were restricted to men, while associations with LVEDD were absent in both sexes. Significant metabolites were validated in a second independent DCM cohort (93 men). Integrative analyses demonstrated close relations between altered proteins and metabolites involved in lipid metabolism, inflammation, and endothelial dysfunction with declining LVEF, with kynurenine as the most prominent finding. In DCM, the loss of cardiac function was reflected by circulating proteins and metabolites with sex-specific differences. Our integrative approach demonstrated that concurrently assessing specific proteins and metabolites might help us to gain insights into the alterations associated with DCM.

Cardiomyopathies (CMs), one of the main causes of sudden death among the young population, are a heterogeneous group of myocardial diseases, usually with a genetic cause. Next-Generation Sequencing (NGS) has expanded the genes studied for CMs; however, the yield is still around 50%. The systematic study of Copy Number Variants (CNVs) could contribute to improving our diagnostic capacity. These alterations have already been described as responsible for cardiomyopathies in some cases; however, their impact has been rarely assessed. We analyzed the clinical significance of CNVs in cardiomyopathies by studying 11,647 affected patients, many more than those considered in previously published studies. We evaluated the yield of the systematic study of CNVs in a production context using NGS and a novel CNV detection software tool v2.0 that has demonstrated great efficacy, maximizing sensitivity and avoiding false positives. We obtained a CNV analysis yield of 0.8% that fluctuated depending on the type of cardiomyopathy studied (0.29% HCM, 1.41% DCM, 1.88% ARVC, 1.8% LVNC, 1.45% RCM), and we present the frequency of occurrence for 18 genes that agglutinate the 95 pathogenic/likely pathogenic CNVs detected. We conclude the importance of including in diagnostic tests a systematic study of these genetic alterations for the different cardiomyopathies.

Cardiovascular complications are the most deadly and cost-driving effects of diabetes mellitus (DM). One of them, which is steadily attracting attention among scientists, is diabetes-induced heart failure, also known as diabetic cardiomyopathy (DCM). Despite significant progress in the research concerning the disease, a universally accepted definition is still lacking. The pathophysiology of the processes accelerating heart insufficiency in diabetic patients on molecular and cellular levels also remains elusive. However, the recent interest concerning extracellular vesicles (EVs) has brought promise to further clarifying the pathological events that lead to DCM. In this review, we sum up recent investigations on the involvement of EVs in DCM and show their therapeutic and indicatory potential.

Attention is often viewed as a mental spotlight, which can be scaled like a zoom lens at specific spatial locations and features a center-surround gradient. Here, we demonstrate a neural signature of attention spotlight in signal transmission along the visual hierarchy. fMRI background connectivity analysis was performed between retinotopic V1 and downstream areas to characterize the spatial distribution of inter-areal interaction under two attentional states. We found that, compared to diffused attention, focal attention sharpened the spatial gradient in the strength of the background connectivity. Dynamic causal modeling analysis further revealed the effect of attention in both the feedback and feedforward connectivity between V1 and extrastriate cortex. In a context which induced a strong effect of crowding, the effect of attention in the background connectivity profile diminished. Our findings reveal a context-dependent attention prioritization in information transmission via modulating the recurrent processing across the early stages in human visual cortex.

BACKGROUND: Variants of the SCN5A gene, which encodes the NaV1.5 cardiac sodium channel, have been linked to arrhythmic disorders associated with dilated cardiomyopathy (DCM). However, the precise pathological mechanisms remain elusive. The present study aimed to elucidate the pathophysiological consequences of the DCM-linked Nav1.5/R219H variant, which is known to generate a gating pore current, using patient-specific human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) cultured in monolayers.
METHODS: Ventricular- and atrial-like hiPSC-CM monolayers were generated from DCM patients carrying the R219H SCN5A variant as well as from healthy control individuals. CRISPR-corrected hiPSC-CMs served as isogenic controls. Simultaneous optical mapping of action potentials (APs) and calcium transients (CaTs) was employed to measure conduction velocities (CVs) and AP durations (APDs) and served as markers of electrical excitability. Calcium handling was evaluated by assessing CaT uptake (half-time to peak), recapture (tau of decay), and durations (TD50 and TD80). A multi-electrode array (MEA) analysis was conducted on hiPSC-CM monolayers to measure field potential (FP) parameters, including corrected Fridericia FP durations (FPDc).
RESULTS: Our results revealed that CVs were significantly reduced by more than 50 % in both ventricular- and atrial-like hiPSC-CM monolayers carrying the R219H variant compared to the control group. APDs were also prolonged in the R219H group compared to the control and CRISPR-corrected groups. CaT uptake, reuptake, and duration were also markedly delayed in the R219H group compared to the control and CRISPR-corrected groups in both the ventricular- and the atrial-like hiPSC-CM monolayers. Lastly, the MEA data revealed a notably prolonged FPDc in the ventricular- and atrial-like hiPSC-CMs carrying the R219H variant compared to the control and isogenic control groups.
CONCLUSIONS: These findings highlight the impact of the gating pore current on AP propagation and calcium homeostasis within a functional syncytium environment and offer valuable insights into the potential mechanisms underlying DCM pathophysiology.

Diabetes mellitus (DM) is known as the first non-communicable global epidemic. It is estimated that 537 million people have DM, but the condition has been properly diagnosed in less than half of these patients. Despite numerous preventive measures, the number of DM cases is steadily increasing. The state of chronic hyperglycaemia in the body leads to numerous complications, including diabetic cardiomyopathy (DCM). A number of pathophysiological mechanisms are behind the development and progression of cardiomyopathy, including increased oxidative stress, chronic inflammation, increased synthesis of advanced glycation products and overexpression of the biosynthetic pathway of certain compounds, such as hexosamine. There is extensive research on the treatment of DCM, and there are a number of therapies that can stop the development of this complication. Among the compounds used to treat DCM are antiglycaemic drugs, hypoglycaemic drugs and drugs used to treat myocardial failure. An important element in combating DCM that should be kept in mind is a healthy lifestyle-a well-balanced diet and physical activity. There is also a group of compounds-including coenzyme Q10, antioxidants and modulators of signalling pathways and inflammatory processes, among others-that are being researched continuously, and their introduction into routine therapies is likely to result in greater control and more effective treatment of DM in the future. This paper summarises the latest recommendations for lifestyle and pharmacological treatment of cardiomyopathy in patients with DM.

BACKGROUND: Diabetic cardiomyopathy (DCM) is a crucial complication of long-term chronic diabetes that can lead to myocardial hypertrophy, myocardial fibrosis, and heart failure. There is increasing evidence that DCM is associated with pyroptosis, a form of inflammation-related programmed cell death. Growth differentiation factor 11 (GDF11) is a member of the transforming growth factor β superfamily, which regulates oxidative stress, inflammation, and cell survival to mitigate myocardial hypertrophy, myocardial infarction, and vascular injury. However, the role of GDF11 in regulating pyroptosis in DCM remains to be elucidated. This research aims to investigate the role of GDF11 in regulating pyroptosis in DCM and the related mechanism.
RESULTS: Mice were injected with streptozotocin (STZ) to induce a diabetes model. H9c2 cardiomyocytes were cultured in high glucose (50 mM) to establish an in vitro model of diabetes. C57BL/6J mice were preinjected with adeno-associated virus 9 (AAV9) intravenously via the tail vein to specifically overexpress myocardial GDF11. GDF11 attenuated pyroptosis in H9c2 cardiomyocytes after high-glucose treatment. In diabetic mice, GDF11 alleviated cardiomyocyte pyroptosis, reduced myocardial fibrosis, and improved cardiac function. Mechanistically, GDF11 inhibited pyroptosis by preventing inflammasome activation. GDF11 achieved this by specifically binding to apoptosis-associated speck-like protein containing a CARD (ASC) and preventing the assembly and activation of the inflammasome. Additionally, the expression of GDF11 during pyroptosis was regulated by peroxisome proliferator-activated receptor α (PPARα).
CONCLUSIONS: These findings demonstrate that GDF11 can treat diabetic cardiomyopathy by alleviating pyroptosis and reveal the role of the PPARα-GDF11-ASC pathway in DCM, providing ideas for new strategies for cardioprotection.

OBJECTIVE: Simultaneous assessment of neurodegeneration in both the cervical cord and brain across multiple centres can enhance the effectiveness of clinical trials. Thus, this study aims to simultaneously assess microstructural changes in the cervical cord and brain above the stenosis in degenerative cervical myelopathy (DCM) using quantitative magnetic resonance imaging (MRI) in a multicentre study.
METHODS: We applied voxelwise analysis with a probabilistic brain/spinal cord template embedded in statistical parametric mappin (SPM-BSC) to process multi parametric mapping (MPM) including effective transverse relaxation rate (R2*), longitudinal relaxation rate (R1), and magnetization transfer (MT), which are indirectly sensitive to iron and myelin content. Regression analysis was conducted to establish associations between neurodegeneration and clinical impairment. Thirty-eight DCM patients (mean age ± SD = 58.45 ± 11.47 years) and 38 healthy controls (mean age ± SD = 41.18 ± 12.75 years) were recruited at University Hospital Balgrist, Switzerland and Toronto Western Hospital, Canada.
RESULTS: Remote atrophy was observed in the cervical cord (p = 0.002) and in the left thalamus (0.026) of the DCM group. R1 was decreased in the periaqueductal grey matter (p = 0.014), thalamus (p = 0.001), corpus callosum (p = 0.0001), and cranial corticospinal tract (p = 0.03). R2* was increased in the primary somatosensory cortices (p = 0.008). Sensory impairments were associated with increased iron-sensitive R2* in the thalamus and periaqueductal grey matter in DCM.
CONCLUSIONS: Simultaneous assessment of the spinal cord and brain revealed DCM-induced demyelination, iron deposition, and atrophy. The extent of remote neurodegeneration was associated with sensory impairment, highlighting the intricate and expansive nature of microstructural neurodegeneration in DCM, reaching beyond the stenosis level.

BACKGROUND: Degenerative cervical myelopathy (DCM) is the most common form of atraumatic spinal cord injury globally. Degeneration of spinal discs, bony osteophyte growth and ligament pathology results in physical compression of the spinal cord contributing to damage of white matter tracts and grey matter cellular populations. This results in an insidious neurological and functional decline in patients which can lead to paralysis. Magnetic resonance imaging (MRI) confirms the diagnosis of DCM and is a prerequisite to surgical intervention, the only known treatment for this disorder. Unfortunately, there is a weak correlation between features of current commonly acquired MRI scans (\"community MRI, cMRI\") and the degree of disability experienced by a patient.
OBJECTIVE: This study examines the predictive ability of current MRI sequences relative to \"advanced MRI\" (aMRI) metrics designed to detect evidence of spinal cord injury secondary to degenerative myelopathy. We hypothesize that the utilization of higher fidelity aMRI scans will increase the effectiveness of machine learning models predicting DCM severity and may ultimately lead to a more efficient protocol for identifying patients in need of surgical intervention.
METHODS: Single institution analysis of imaging registry of patients with DCM.
METHODS: A total of 296 patients in the cMRI group and 228 patients in the aMRI group.
METHODS: Physiologic measures: accuracy of machine learning algorithms to detect severity of DCM assessed clinically based on the modified Japanese Orthopedic Association (mJOA) scale.
METHODS: Patients enrolled in the Canadian Spine Outcomes Research Network registry with DCM were screened and 296 cervical spine MRIs acquired in cMRI were compared with 228 aMRI acquisitions. aMRI acquisitions consisted of diffusion tensor imaging, magnetization transfer, T2-weighted, and T2*-weighted images. The cMRI group consisted of only T2-weighted MRI scans. Various machine learning models were applied to both MRI groups to assess accuracy of prediction of baseline disease severity assessed clinically using the mJOA scale for cervical myelopathy.
RESULTS: Through the utilization of Random Forest Classifiers, disease severity was predicted with 41.8% accuracy in cMRI scans and 73.3% in the aMRI scans. Across different predictive model variations tested, the aMRI scans consistently produced higher prediction accuracies compared to the cMRI counterparts.
CONCLUSIONS: aMRI metrics perform better in machine learning models at predicting disease severity of patients with DCM. Continued work is needed to refine these models and address DCM severity class imbalance concerns, ultimately improving model confidence for clinical implementation.

UNASSIGNED: The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in animal models. However, the pivotal nodes and directed causal regulation within this inhibitory circuit in humans remains controversial.
UNASSIGNED: The main aim of the present study was to determine the causal information flow and critical nodes in the basal ganglia-thalamocortical inhibitory circuits and also to examine whether these are modulated by biological factors (i.e. sex) and behavioral performance.
UNASSIGNED: Here, we capitalize on the recent progress in robust and biologically plausible directed causal modeling (DCM-PEB) and a large response inhibition dataset (n = 250) acquired with concomitant functional magnetic resonance imaging to determine key nodes, their causal regulation and modulation via biological variables (sex) and inhibitory performance in the inhibitory circuit encompassing the right inferior frontal gyrus (rIFG), caudate nucleus (rCau), globus pallidum (rGP), and thalamus (rThal).
UNASSIGNED: The entire neural circuit exhibited high intrinsic connectivity and response inhibition critically increased causal projections from the rIFG to both rCau and rThal. Direct comparison further demonstrated that response inhibition induced an increasing rIFG inflow and increased the causal regulation of this region over the rCau and rThal. In addition, sex and performance influenced the functional architecture of the regulatory circuits such that women displayed increased rThal self-inhibition and decreased rThal to GP modulation, while better inhibitory performance was associated with stronger rThal to rIFG communication. Furthermore, control analyses did not reveal a similar key communication in a left lateralized model.
UNASSIGNED: Together, these findings indicate a pivotal role of the rIFG as input and causal regulator of subcortical response inhibition nodes.