Singers show enhanced performance and neural representation of vocal imitation

Humans have a remarkable capacity to finely control the muscles of the larynx, via distinct patterns of cortical topography and innervation that may underpin our sophisticated vocal capabilities compared with non-human primates. Here, we investigated the behavioural and neural correlates of laryngeal control, and their relationship to vocal expertise, using an imitation task that required adjustments of larynx musculature during speech. Highly trained human singers and non-singer control participants modulated voice pitch and vocal tract length (VTL) to mimic auditory speech targets, while undergoing real-time anatomical scans of the vocal tract and functional scans of brain activity. Multivariate analyses of speech acoustics, larynx movements and brain activation data were used to quantify vocal modulation behaviour and to search for neural representations of the two modulated vocal parameters during the preparation and execution of speech. We found that singers showed more accurate task-relevant modulations of speech pitch and VTL (i.e. larynx height, as measured with vocal tract MRI) during speech imitation; this was accompanied by stronger representation of VTL within a region of the right somatosensory cortex. Our findings suggest a common neural basis for enhanced vocal control in speech and song. This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part I)’

Singers show enhanced performance and neural representation of vocal imitation

Humans have a remarkable capacity to finely control the muscles of the larynx, via distinct patterns of cortical topography and innervation that may underpin our sophisticated vocal capabilities compared with non-human primates. Here, we investigated the behavioural and neural correlates of laryngeal control, and their relationship to vocal expertise, using an imitation task that required adjustments of larynx musculature during speech. Highly trained human singers and non-singer control participants modulated voice pitch and vocal tract length (VTL) to mimic auditory speech targets, while undergoing real-time anatomical scans of the vocal tract and functional scans of brain activity. Multivariate analyses of speech acoustics, larynx movements and brain activation data were used to quantify vocal modulation behaviour and to search for neural representations of the two modulated vocal parameters during the preparation and execution of speech. We found that singers showed more accurate task-relevant modulations of speech pitch and VTL (i.e. larynx height, as measured with vocal tract MRI) during speech imitation; this was accompanied by stronger representation of VTL within a region of the right somatosensory cortex. Our findings suggest a common neural basis for enhanced vocal control in speech and song. This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part I)’

Utility of diffusion MRI characteristics of cervical lymph nodes as disease classifier between patients with head and neck squamous cell carcinoma and healthy volunteers

Diffusion MRI characteristics assessed by apparent diffusion coefficient (ADC) histogram analysis in head and neck squamous cell carcinoma (HNSCC) have been reported as helpful in classifying tumours based on diffusion characteristics. There is little reported on HNSCC lymph nodes classification by diffusion characteristics. The aim of this study was to determine whether pretreatment nodal microstructural diffusion MRI characteristics can classify diseased nodes of patients with HNSCC from normal nodes of healthy volunteers. Seventy-nine patients with histologically confirmed HNSCC prior to chemoradiotherapy, and eight healthy volunteers, underwent diffusion-weighted (DW) MRI at a 1.5-T MR scanner. Two radiologists contoured lymph nodes on DW (b = 300 s/m2) images. ADC, distributed diffusion coefficient (DDC) and alpha (α) values were calculated by monoexponential and stretched exponential models. Histogram analysis metrics of drawn volume were compared between patients and volunteers using a Mann–Whitney test. The classification performance of each metric between the normal and diseased nodes was determined by receiver operating characteristic (ROC) analysis. Intraclass correlation coefficients determined interobserver reproducibility of each metric based on differently drawn ROIs by two radiologists. Sixty cancerous and 40 normal nodes were analysed. ADC histogram analysis revealed significant differences between patients and volunteers (p ≤0.0001 to 0.0046), presenting ADC distributions that were more skewed (1.49 for patients, 1.03 for volunteers; p = 0.0114) and ‘peaked’ (6.82 for patients, 4.20 for volunteers; p = 0.0021) in patients. Maximum ADC values exhibited the highest area under the curve ([AUC] 0.892). Significant differences were revealed between patients and volunteers for DDC and α value histogram metrics (p ≤0.0001 to 0.0044); the highest AUC were exhibited by maximum DDC (0.772) and the 25th percentile α value (0.761). Interobserver repeatability was excellent for mean ADC (ICC = 0.88) and the 25th percentile α value (ICC = 0.78), but poor for all other metrics. These results suggest that pretreatment microstructural diffusion MRI characteristics in lymph nodes, assessed by ADC and α value histogram analysis, can identify nodal disease

Disrupted principal network organisation in multiple sclerosis relates to disability

Structural network-based approaches can assess white matter connections revealing topological alterations in multiple sclerosis (MS). However, principal network (PN) organisation and its clinical relevance in MS has not been explored yet. Here, structural networks were reconstructed from diffusion data in 58 relapsing-remitting MS (RRMS), 28 primary progressive MS (PPMS), 36 secondary progressive (SPMS) and 51 healthy controls (HCs). Network hubs’ strengths were compared with HCs. Then, PN analysis was performed in each clinical subtype. Regression analysis was applied to investigate the associations between nodal strength derived from the first and second PNs (PN1 and PN2) in MS, with clinical disability. Compared with HCs, MS patients had preserved hub number, but some hubs exhibited reduced strength. PN1 comprised 10 hubs in HCs, RRMS and PPMS but did not include the right thalamus in SPMS. PN2 comprised 10 hub regions with intra-hemispheric connections in HCs. In MS, this subnetwork did not include the right putamen whilst in SPMS the right thalamus was also not included. Decreased nodal strength of the right thalamus and putamen from the PNs correlated strongly with higher clinical disability. These PN analyses suggest distinct patterns of disruptions in MS subtypes which are clinically relevan

Comparison of Neurite Orientation Dispersion and Density Imaging and Two-Compartment Spherical Mean Technique Parameter Maps in Multiple Sclerosis

BACKGROUND: Neurite orientation dispersion and density imaging (NODDI) and the spherical mean technique (SMT) are diffusion MRI methods providing metrics with sensitivity to similar characteristics of white matter microstructure. There has been limited comparison of changes in NODDI and SMT parameters due to multiple sclerosis (MS) pathology in clinical settings. PURPOSE: To compare group-wise differences between healthy controls and MS patients in NODDI and SMT metrics, investigating associations with disability and correlations with diffusion tensor imaging (DTI) metrics. METHODS: Sixty three relapsing-remitting MS patients were compared to 28 healthy controls. NODDI and SMT metrics corresponding to intracellular volume fraction (v_{in}), orientation dispersion (ODI and ODE), diffusivity (D) (SMT only) and isotropic volume fraction (v_{iso}) (NODDI only) were calculated from diffusion MRI data, alongside DTI metrics (fractional anisotropy, FA; axial/mean/radial diffusivity, AD/MD/RD). Correlations between all pairs of MRI metrics were calculated in normal-appearing white matter (NAWM). Associations with expanded disability status scale (EDSS), controlling for age and gender, were evaluated. Patient-control differences were assessed voxel-by-voxel in MNI space controlling for age and gender at the 5% significance level, correcting for multiple comparisons. Spatial overlap of areas showing significant differences were compared using Dice coefficients. RESULTS: NODDI and SMT show significant associations with EDSS (standardised beta coefficient −0.34 in NAWM and −0.37 in lesions for NODDI vin; 0.38 and −0.31 for SMT ODE and vin in lesions; p < 0.05). Significant correlations in NAWM are observed between DTI and NODDI/SMT metrics. NODDI vin and SMT vin strongly correlated (r = 0.72, p < 0.05), likewise NODDI ODI and SMT ODE (r = −0.80, p < 0.05). All DTI, NODDI and SMT metrics detect widespread differences between patients and controls in NAWM (12.57% and 11.90% of MNI brain mask for SMT and NODDI v_{in}, Dice overlap of 0.42). DATA CONCLUSION: SMT and NODDI detect significant differences in white matter microstructure between MS patients and controls, concurring on the direction of these changes, providing consistent descriptors of tissue microstructure that correlate with disability and show alterations beyond focal damage. Our study suggests that NODDI and SMT may play a role in monitoring MS in clinical trials and practice

White matter integrity correlates with cognition and disease severity in Fabry disease

Cerebral white matter pathology is a common CNS manifestation of Fabry disease, visualized as white matter hyperintensities on MRI in 42-81% of patients. Diffusion tensor imaging (DTI) MRI is a sensitive technique to quantify microstructural damage within the white matter with potential value as a disease biomarker. We evaluated the pattern of DTI abnormalities in Fabry disease, and their correlations with cognitive impairment, mood, anxiety, disease severity and plasma lyso-Gb3 levels in 31 patients with genetically proven Fabry disease and 19 age-matched healthy control subjects. We obtained average values of fractional anisotropy and mean diffusivity within the white matter and performed voxelwise analysis with tract-based spatial statistics. Using a standardized neuropsychological test battery, we assessed processing speed, executive function, anxiety, depression and disease severity. The mean age (% male) was 44.1 (45%) for patients with Fabry disease and 37.4 (53%) for the healthy control group. In patients with Fabry disease, compared to healthy controls the mean average white matter fractional anisotropy was lower in [0.423 (standard deviation, SD 0.023) versus 0.446 (SD 0.016), P = 0.002] while mean average white matter mean diffusivity was higher (749 × 10-6 mm2/s (SD 32 × 10-6) versus 720 × 10-6 mm2/s (SD 21 × 10-6), P = 0.004]. Voxelwise statistics showed that the diffusion abnormalities for both fractional anisotropy and mean diffusivity were anatomically widespread. A lesion probability map showed that white matter hyperintensities also had a wide anatomical distribution with a predilection for the posterior centrum semiovale. However, diffusion abnormalities in Fabry disease were not restricted to lesional tissue; compared to healthy controls, the normal appearing white matter in patients with Fabry disease had reduced fractional anisotropy [0.422 (SD 0.022) versus 0.443 (SD 0.017) P = 0.003] and increased mean diffusivity [747 × 10-6 mm2/s (SD 26 × 10-6) versus 723 × 10-6 mm2/s (SD 22 × 10-6), P = 0.008]. Within patients, average white matter fractional anisotropy and white matter lesion volume showed statistically significant correlations with Digit Symbol Coding Test score (r = 0.558, P = 0.001; and r = -0.633, P ≤ 0.001, respectively). Average white matter fractional anisotropy correlated with the overall Mainz Severity Score Index (r = -0.661, P ≤ 0.001), while average white matter mean diffusivity showed a strong correlation with plasma lyso-Gb3 levels (r = 0.559, P = 0.001). Our findings using DTI confirm widespread areas of microstructural white matter disruption in Fabry disease, extending beyond white matter hyperintensities seen on conventional MRI. Moreover, diffusion measures show strong correlations with cognition (processing speed), clinical disease severity and a putative plasma biomarker of disease activity, making them promising quantitative biomarkers for monitoring Fabry disease severity and progression

(RB1)-negative retinal organoids display proliferation of cone photoreceptors and loss of retinal differentiation

Retinoblastoma is a tumor of the eye in children under the age of five caused by biallelic inactivation of the (RB1) tumor suppressor gene in maturing retinal cells. Cancer models are essential for understanding tumor development and in preclinical research. Because of the complex organization of the human retina, such models were challenging to develop for retinoblastoma. Here, we present an organoid model based on differentiation of human embryonic stem cells into neural retina after inactivation of (RB1) by CRISPR/Cas9 mutagenesis. Wildtype and (RB1) heterozygous mutant retinal organoids were indistinguishable with respect to morphology, temporal development of retinal cell types and global mRNA expression. However, loss of pRB resulted in spatially disorganized organoids and aberrant differentiation, indicated by disintegration of organoids beyond day 130 of differentiation and depletion of most retinal cell types. Only cone photoreceptors were abundant and continued to proliferate, supporting these as candidate cells-of-origin for retinoblastoma. Transcriptome analysis of (RB1) knockout organoids and primary retinoblastoma revealed gain of a retinoblastoma expression signature in the organoids, characterized by upregulation of (RBL1) (p107), (MDM2), (DEK), (SYK) and (HELLS). In addition, genes related to immune response and extracellular matrix were specifically upregulated in (RB1)-negative organoids. In vitro retinal organoids therefore display some features associated with retinoblastoma and, so far, represent the only valid human cancer model for the development of this disease

The Human Retinoblastoma Gene Is Imprinted

Genomic imprinting is an epigenetic process leading to parent-of-origin–specific DNA methylation and gene expression. To date, ∼60 imprinted human genes are known. Based on genome-wide methylation analysis of a patient with multiple imprinting defects, we have identified a differentially methylated CpG island in intron 2 of the retinoblastoma (RB1) gene on chromosome 13. The CpG island is part of a 5′-truncated, processed pseudogene derived from the KIAA0649 gene on chromosome 9 and corresponds to two small CpG islands in the open reading frame of the ancestral gene. It is methylated on the maternal chromosome 13 and acts as a weak promoter for an alternative RB1 transcript on the paternal chromosome 13. In four other KIAA0649 pseudogene copies, which are located on chromosome 22, the two CpG islands have deteriorated and the CpG dinucleotides are fully methylated. By analysing allelic RB1 transcript levels in blood cells, as well as in hypermethylated and 5-aza-2′-deoxycytidine–treated lymphoblastoid cells, we have found that differential methylation of the CpG island skews RB1 gene expression in favor of the maternal allele. Thus, RB1 is imprinted in the same direction as CDKN1C, which operates upstream of RB1. The imprinting of two components of the same pathway indicates that there has been strong evolutionary selection for maternal inhibition of cell proliferation

Recent advances in nanocarrier-loaded gels: Which drug delivery technologies against which diseases?

The combination of pharmaceutical technologies can be a wise choice for developing innovative therapeutic strategies. The association of nanocarriers and gels provides new therapeutic possibilities due to the combined properties of the two technologies. Gels support the nanocarriers, localize their administration to the target tissue, and sustain their release. In addition to the properties afforded by the gel, nanocarriers can provide additional drug sustained release or different pharmacokinetic and biodistribution profiles than those from nanocarriers administered by the conventional route to improve the drug therapeutic index. This review focuses on recent (over the last ten years) in vivo data showing the advances and advantages of using nanocarrier-loaded gels. Liposomes, micelles, liquid and solid lipid nanocapsules, polymeric nanoparticles, dendrimers, and fullerenes are all nanotechnologies which have been recently assessed for medical applications, such as cancer therapy, the treatment of cutaneous and infectious diseases, anesthesia, the administration of antidepressants, and the treatment of unexpected diseases, such as alopecia