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Jasper, A.

Publications and source records attributed to Jasper, A..

5 recordsLinked to original sources

Neurodevelopmental Inequality arising from Early Childhood Stunting: Evidences from Brain Connectivity

Early childhood stunting (ECS) affects millions of children globally and conjectured to result in suboptimal brain and cognitive development later in life. Charting out the trajectory of brain network development and most importantly how the compensation of function can be achieved gives windows of intervention to clinicians, educators and policy makers. In this study, advanced network neuroscience tools, graph theoretical methods applied on diffusion weighted MR-imaging (DWI) revealed the effects of ECS on white matter (WM) organization in a community-based birth cohort of 170 children (mean age = 9.18 years, SD = 0.28) from Vellore, India. Based on stunting status at ages two, five, and nine years, children were categorised into four groups: always stunted (AS; n=21), stunted until five with catch-up at nine (S5C9; n=31), stunted until two with catch-up at five (S2C5; n=28), and never stunted or typically developing (TD; n=90). The catch-up groups showed strikingly similar anthropometric measures compared to TD. However, all stunted groups (AS, S5C9, S2C5) showed significantly lower performance and verbal IQ scores compared to TD children. DWI data revealed AS children exhibited shorter tract lengths across select cortico-cortical connections, an increased number and strength of short- and medium-range connections, and a corresponding reduction in long-range connections and strength. Network analyses further revealed that AS and S5C9 groups displayed higher local clustering and local efficiency relative to TD, reflecting greater local segregation of brain networks. Hub-like modules was broadly conserved across groups, although both catch-up groups (S2C5 and S5C9) showed additional hubs, suggesting compensatory network reorganization via a more modular architecture. Together, these findings provide novel evidence that ECS is linked to altered structural reorganization of brain networks and reduced cognitive performance in later childhood. While persistent stunting (AS) is associated with the most pronounced alterations, partial catch-up (S2C5 and S5C9) is accompanied by compensatory adaptations, such as increased short-range connectivity and recruitment of additional hubs. These results underscore the critical importance of early nutritional interventions to support optimal brain network development.

neuroscience↗

Integration of immunomonitoring assays with PET/CT in TB patients identifies on-treatment biomarkers

Tuberculosis (TB) continues to pose a significant global public health challenge with substantial patient morbidity and mortality. Current TB patient biomarkers lack sufficient resolution to inform treatment response and patient stratification. This necessitates the development of sensitive and reliable host biomarkers. We previously demonstrated the efficacy of TruCulture whole blood stimulation for differentiating asymptomatic TB from active pulmonary TB disease patients in endemic regions. Our systems immunology study expands upon this previous work by evaluating the potential of TruCulture to monitor longitudinal responses to TB treatment in patients from the Predict-TB trial before, during, and after 6 months of antibiotic therapy. We stimulated whole blood from TB patients (n=40) using TruCulture under four conditions (Null, Mycobacterium tuberculosis-antigen, LPS, and IL-1{beta}) at baseline (week 0), during treatment (weeks 16 and 24), and one-year follow-up post- treatment (week 72). 20/25 measured cytokines exhibited significant changes throughout treatment, with several continuing to evolve during post-therapy follow-up. Machine learning based analysis identified Mtb-Ag-induced IL-1RA (AUC = 0.90, 0.92, 0.95 at weeks 16, 24, 72) and LPS-induced NLRP3 (AUC = 0.94 at week 16) as the best protein and transcriptional biomarkers for distinguishing treated from untreated patients, strongly implicating the inflammasome response. Combining these results with the extent of lung disease assessed by FDG PET/CT scans, we showed direct disease relevance for these blood-based biomarkers. The identified biomarker profiles hold promise for improving TB patient care through early prediction of treatment responses, real-time therapy monitoring, and informed development of host-directed therapeutic strategies for clinical decision-making. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=146 HEIGHT=200 SRC="FIGDIR/small/723467v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@15ae804org.highwire.dtl.DTLVardef@136939forg.highwire.dtl.DTLVardef@15ac58org.highwire.dtl.DTLVardef@e5d8f0_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO Predict-TB clinical study overview and summary of TB-specific biomarkers identified from TruCulture whole blood stimulation system. C_FIG

immunology↗

Multimodal lesion mapping in affective blindsight reveals dual amygdala and superior temporal sulcus contributions to nonconscious emotion processing

Affective blindsight, the capacity to discriminate emotional stimuli despite bilateral damage to the primary visual cortex (V1) and without conscious awareness, offers a unique model of non-conscious visual processing. Subcortical pathways involving the pulvinar and amygdala have been proposed, but putative cortical contributions remain unclear. We examined 182 patients, including 31 with bilateral V1 lesions. Among these, 15 had cortical visual loss and 7 showed affective blindsight. Using behavioral testing, lesion symptom mapping, and tractography, we found that preserved pulvinar connectivity with both the posterior superior temporal sulcus (STS) and the amygdala is necessary for affective blindsight. These findings provide causal evidence for a multi-route architecture, identifying the pulvinar-STS pathway, alongside the pulvinar-amygdala pathway, as a critical substrate for non-conscious affective processing.

neuroscience↗

Childhood brain morphometry in children with persistent stunting and catch-up growth

BackgroundEarly childhood stunting affects around 150 million young children worldwide and leads to suboptimal human potential in later life. However, there is limited data on the effects of early childhood stunting and catch-up growth on brain morphometry. MethodsWe evaluated childhood brain volumes at nine years of age in a community-based birth-cohort follow-up study in Vellore, south India among four groups based on anthropometric assessments at two, five, and nine years namely Never Stunted (NS), Stunted at two years and caught up by five years (S2N5), Stunted at two and five years and caught up by nine years (S2N9), and Always Stunted (AS). T1-weighted magnetic resonance imaging (MRI) images were acquired using a 3T MRI scanner, and brain volumes were quantified using FreeSurfer software. FindingsAmongst 251 children from the overall cohort, 178 children with a mean age of 9.54 were considered for further analysis. The total brain volume, subcortical volume, bilateral cerebellar white matter, and posterior corpus callosum showed a declining trend from NS to AS. Regional cortical brain analysis showed significant lower bilateral lateral occipital volumes, right pallidum, bilateral caudate, and right thalamus volumes between NS and AS. InterpretationTo the best of our knowledge, this first neuroimaging analysis to investigate the effects of persistent childhood stunting and catch-up growth on brain volumetry indicates impairment at different brain levels involving total brain and subcortical volumes, networking/connecting centres (thalamus, basal ganglia, callosum, cerebellum) and visual processing area of lateral occipital cortex.

neuroscience↗

Circuit-motivated generalized affine models characterize stimulus-dependent visual cortical shared variability

Correlated variability in the visual cortex is modulated by stimulus properties. The stimulus dependence of correlated variability impacts stimulus coding and is indicative of circuit structure. An affine model combining a factor proportional to mean stimulus response and an additive offset has been proposed to explain how correlated variability in primary visual cortex (V1) depends on stimulus orientations. However, whether the affine model could be extended to explain modulations by other stimulus variables or variability shared between two brain areas is unknown. Motivated by a simple neural circuit mechanism, we modified the affine model to better explain the contrast-dependence of neural variability shared within either primary or secondary visual cortex (V1 or V2) as well as the orientation-dependence of neural variability shared between V1 and V2. Our results bridge neural circuit mechanisms and statistical models, and provide a parsimonious explanation for the stimulus-dependence of correlated variability within and between visual areas.

neuroscience↗