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Intracranial arterial calcification on computed tomography and risk of cognitive impairment or dementia: a systematic review and meta-analysis
No full textIntroduction: Coronary arterial calcification on computed tomography (CT), or CT-CAC, is a widely studied risk factor for acute coronary events, but although intracranial arterial calcification on CT brain imaging (CT-IAC) is also a frequent finding in older individuals, there is no consensus on its prognostic significance, particularly whether its presence, severity, or site predict cognitive impairment or dementia. Given the clinical and mechanistic importance of any associations, we did a systematic review and meta-analysis.
Methods: Studies published before 30 January 2026 were identified from bibliographic databases, reference lists, and forward or backward screening. Inclusion criteria were: (1) Studies of adults linking CT-IAC/CAC with later cognitive impairment or dementia; (2) reporting adjusted effect measures with 95% confidence interval or p-values (or calculable); (3) calcification assessed by CT/CT angiography and cognition by recognised tests or expert evaluation. Studies were summarised qualitatively and pooled quantitatively depending on heterogeneity.
Results: Six cross-sectional studies and three longitudinal studies reported data on CT-IAC and cognitive status. Among five studies that reported associations for presence vs. absence of CT-IAC, presence of calcification was weakly associated with cognitive impairment or dementia (three cross-sectional studies – pooled adjusted odds ratio [aOR]=1.42, 0.88–2.28, p=0.15; two longitudinal studies – aOR=1.51, 1.03–2.22, p=0.033; all studies – aOR=1.48, 1.10–1.99, p=0.01). Among five studies that reported associations for more severe vs. milder CT-IAC, severe calcification was more strongly associated with the cognitive outcome (two cross-sectional studies – pooled aOR=2.29, 0.50–10.57, p=0.29; three longitudinal studies – aOR=1.84, 1.28–2.65, p=0.001; all studies – aOR=1.74, 1.28–2.36, p=0.0004), including in two longitudinal cohorts in patients with stroke/transient ischaemic attack (pooled aOR=1.73, 1.22–2.46, p=0.002). In two longitudinal studies, severity of vertebrobasilar CT-IAC also predicted dementia (pooled aOR=2.12, 1.06–4.21, p=0.033), and severity of medial/internal elastic lamina (IEL) CT-IAC was a stronger predictor of dementia (pooled aOR=2.35, 1.29–4.28, p=0.005) than severity of intimal CT-IAC (pooled aOR=1.29, 0.75–2.23, p=0.36). For coronary CT-CAC, three longitudinal cohorts revealed weak associations with dementia (per standard deviation increase in calcification measures – pooled adjusted hazards ratio=1.15, 1.02–1.30, p=0.025).
Conclusion: In longitudinal studies, presence and severity of CT-IAC are both independently associated with dementia, driven mainly by medial/IEL calcification, with weaker associations for intimal and coronary calcification. In cross-sectional studies, the associations for both CT-IAC measures were of a similar magnitude to the longitudinal analyses, but were not statistically significant. Future studies should determine age- and dementia-subtype specific associations
Multidimensional poverty in Yemen: an analysis of changes over time and gender
Get PDFThis brief aims to provide a detailed analysis of multidimensional poverty and deprivation in Yemen and its 21 governorates between 2013 and 2023. Using a proxy MPI based on the Demographic Health Survey (DHS-2013) and the MICS 2023, the brief analyses changes over time in poverty levels comparing pre-conflict levels to 2023. The brief also presents an intrahousehold analysis using the national MPI based on the YHDS 2021 to understand intrahousehold inequalities in the levels of deprivation of men and women. This analysis aims to contribute to the ongoing efforts of policymakers, development partners, and researchers to better understand and address the complex realities of poverty in Yemen and similar fragile contexts
Small Triangulations of 4-Manifolds and the 4-Manifold Census
Get PDFWe present a framework to classify PL-types of large censuses of triangulated 4-manifolds, which we use to classify the PL-types of all triangulated 4-manifolds with up to six pentachora. This is successful except for triangulations homeomorphic to the 4-sphere, CP2, and the rational homology sphere QS4(2), where we find at most four, three, and two PL-types respectively. We conjecture that they are all standard. In addition, we look at the cases resisting classification and discuss the combinatorial structure of these triangulations—which we deem interesting in their own rights
A novel deep semantic- and vision-based self-attention architecture for skin cancer classification
Get PDFObjectives: In the world, skin cancer is a significant health concern, and early diagnosis of this cancer plays a key role in improving patient outcomes. The early detection of this cancer reduces the death rate, but due to the complexity of the diagnosis, incorrect detection and prediction are provided by the experts. Therefore, it is essential to propose a computer-aided diagnostic system based on deep learning and explainable Artificial Intelligence (XAI) techniques that can be used as a second opinion in clinics and help physicians more accurately detect and predict this type of cancer. Methods: This work presents the proposed deep learning architecture consisting of two modules—skin lesion segmentation and lesion type classification. The proposed architecture is interpreted using XAI techniques to better evaluate the black-box model. In the skin lesion segmentation phase, we implemented DeepLab V3 architecture for semantic segmentation. The ResNet-18 model was used as the backbone, and later hyperparameters were optimized using Bayesian Optimization (BO). In the classification phase, we design a FusedNet architecture called Inverted self-attention with Vision Transformer (ISAwViT). The proposed fused network combines an inverted self-attention residual architecture with a vision transformer. The proposed fused network extracted feature information more deeply than performing an accurate prediction in a later stage. The design model is trained, and later in the testing phase, extracted features are classified using Softmax and several other classifiers. Results: The lesion segmentation and classification experiment was conducted on the HAM10000 dataset. The accuracy achieved by the HAM10000 dataset was 95.16% for lesion segmentation and 97.5% for lesion classification. Conclusion: Compared with recent techniques, the proposed model is more effective and efficient. In addition, the interpretation of the proposed model was performed using LIME and Grad-CAM, which show how the fused model makes correct classifications
Caregiver assessment of executive function deficits among HIV-infected and HIV-exposed uninfected preschool children in Kenya
Get PDFBackground: This study examined caregiver assessment of executive functioning (EF) in perinatally HIV-infected (PHIV) and perinatally HIV-exposed but uninfected (PHEU) Kenyan children, and explored the extent to which various biopsychosocial factors influence EF outcomes. Methods: Children aged 3–5 years that were PHIV (n = 43), PHEU (n = 52), or HIV-unexposed uninfected (HUU, n = 58) and their caregivers were enrolled in this study. EF was measured using the Childhood Executive Functioning Inventory. Caregivers’ common mental disorders (CMDs) and parenting behaviour were evaluated using the Shona Symptoms Questionnaire (SSQ) and a parenting behaviour scale, respectively. We used analyses of variance to assess group differences in EF scores and a hierarchal linear regression model to explore covariates associated with EF outcomes. Results: Overall, we observed significant negative effects of HIV exposure on EF scores, F (2, 149) = 8.591, p < 0.001. Compared to HUU children, PHIV children performed worse in working memory [mean difference (MD), 2.89 [95% CI: 0.65–5.14] p = 0.008], inhibitory control [MD, 2.47 (95% CI: 0.55–4.40), p = 0.008], and composite EF [MD, 5.37 (95% CI: 1.97–8.76), p = 0.001]. PHEU children showed poorer performance in working memory [MD, 3.24 (95% CI: 1.11–5.37), p = 0.001] and composite EF [MD, 4.97 (95% CI: 1.75–8.19), p = 0.001]. The observed EF impairment was strongly associated with caregivers’ CMDs and advanced HIV disease in children. Conclusion: Our study suggests that caregivers can observe overt executive dysfunction in children perinatally exposed to HIV. These findings underscore the importance of antiretroviral therapy adherence in PHIV children and the provision of psychosocial support to caregivers of HIV-exposed children to improve EF outcomes
Leaf-to-leaf paths and cycles in degree-critical graphs: Leaf-to-leaf paths and cycles in degree-critical graphs
Get PDFAn n-vertex graph is degree 3-critical if it has 2n-2 edges and no proper induced subgraph with minimum degree at least 3. In 1988, Erdős, Faudree, Gyárfás, and Schelp asked whether one can always find cycles of all short lengths in these graphs, which was disproven by Narins, Pokrovskiy, and Szabó through a construction based on leaf-to-leaf paths in trees whose vertices have degree either 1 or 3. They went on to suggest several weaker conjectures about cycle lengths in degree 3-critical graphs and leaf-to-leaf path lengths in these so-called 1-3 trees. We resolve three of their questions either fully or up to a constant factor. Our main results are the following:every n-vertex degree 3-critical graph has Ω(logn) distinct cycle lengths; every tree with maximum degree Δ≥3 and ℓ leaves has at least logΔ-1((Δ-2)ℓ) distinct leaf-to-leaf path lengths; for every integer N≥1, there exist arbitrarily large 1–3 trees which have O(N0.91) distinct leaf-to-leaf path lengths smaller than N, and, conversely, every 1–3 tree on at least 2N vertices has Ω(N2/3) distinct leaf-to-leaf path lengths smaller than N. Several of our proofs rely on purely combinatorial means, while others exploit a connection to an additive problem that might be of independent interest
Rapid invisible frequency tagging (RIFT) does not evoke intermodulation components in the neural response
Get PDFThe human visual system performs nonlinear integrative operations at multiple stages of visual information processing. For instance, integrating parts of visual stimuli into a coherent object involves coordinated neural processing along the visual hierarchy. However, it remains uncertain whether visual integration manifests in a nonlinear neural response, particularly through intermodulation components in the power spectrum. In this study, we used a visual motion paradigm combined with rapid invisible frequency tagging (RIFT) and magnetoencephalography (MEG) to explore nonlinear characteristics of neural responses associated with visual integration. In this paradigm, two grating patches were moving coherently or incoherently, and were modulated by RIFT at 56 and 63 Hz, respectively. The behavioural results revealed that the participants responded more accurately and faster to probes during coherent compared to incoherent motion. Moreover, the type of motion elicited differential effects on pupil dilation, with significantly larger pupil diameter observed during incoherent motion. To evaluate the neural response to coherent and incoherent motion stimuli, we assessed spectral coherence between MEG and RIFT. We observed a strong coherence at the tagging frequencies (f1 = 56 and f2 = 63 Hz) as well as at the higher harmonics at 112 Hz and 126 Hz, respectively. Importantly we did not observe a response at frequencies of the intermodulation (f2–f1, f2 + f1); nor did we observe a difference when comparing the coherence and incoherent motion. We conclude that in contrast to studies with low-frequency visible tagging, RIFT does not evoke intermodulation components and therefore, its applicability for investigating the neural mechanisms of visual integration might be limited
Measurement of ion acceleration and diffusion in a laser-driven magnetized plasma
Get PDFHere we present results from an experiment performed at the GSI Helmholtz Center for Heavy Ion Research. A mono-energetic beam of chromium ions with initial energies of ~ 450 MeV was fired through a magnetized interaction region formed by the collision of two counter-propagating laser-ablated plasma jets. While laser interferometry revealed the absence of strong fluid-scale turbulence, acceleration and diffusion of the beam ions was driven by wave-particle interactions. A possible mechanism is particle acceleration by electrostatic, short scale length kinetic turbulence, such as the lower-hybrid drift instability
The active construction of past episodes
Get PDFEpisodic memories – declarative memories of past events, characterized by rich spatiotemporal context – play a central role in guiding perception and behaviour. Here, we advance a model that integrates episodic memories within the active inference framework. We describe how episodic memories are incorporated into the generative models used in active inference to support the re-construction, replay and communication of past events. In doing so, we foreground two foundational themes. The first is the message passing in deep temporal models that allow one to actively construct memories of episodes. The second is the communicative aspect of declarative memories, and the way in which one might recount something from one’s autobiography. In effect, this means that the message passing that supports episodic memory propagates information about what we have done – or what we would do – given past circumstances to draw inferences about how to communicate those beliefs. Together, these themes emphasise that we are not passive recorders of the things that happen to us. We are active participants in the events we recall and in the telling of stories about them