This study investigates vocabulary development and lexical integration in children with intellectual and developmental disabilities (IDD) who use augmentative or alternative communication (AAC).

The article provides a comprehensive analysis of the escalating health impacts of climate change across Latin America, as well as the region's progress and challenges in adaptation, mitigation, and engagement.

Elsevier,

Climate Change and Disability: A Collaborative Approach to a Sustainable, Inclusive Future for All 2026, pp 77-84

This chapter underscores how climate change amplifies health risks and systemic barriers for children, especially those with special health care needs, aligning with SDG 3 (Good Health and Well-being) by addressing health vulnerabilities, SDG 10 (Reduced Inequalities) through calls for inclusive policies, and SDG 13 (Climate Action) by advocating disability-inclusive climate adaptation and resilience strategies.

Elsevier,

Climate Change and Disability: A Collaborative Approach to a Sustainable, Inclusive Future for All 2026, pp 45-48

This chapter highlights how climate change intensifies health challenges and resource access barriers for women with disabilities, aligning with SDG 3 (Good Health and Well-being) by emphasizing the need for inclusive decision-making to improve health outcomes and ensure equitable access to rights.

Report on a new smart delivery system designed to target and treat Alzheimer's disease more effectively, aiming to overcome the challenges of current treatments and offering a promising way to fight Alzheimer's more accurately and safely.
This study presents AlzFormer, a novel deep learning framework utilizing spatiotemporal self-attention to classify Alzheimer’s disease (AD), mild cognitive impairment (MCI), and cognitively normal (CN) individuals from structural MRI scans. By modeling MRI volumes as sequential slice-based inputs and fine-tuning a pre-trained TimeSformer model, AlzFormer achieved 94% accuracy and high class-wise F1-scores, while attention map analyses highlighted clinically relevant brain regions, demonstrating both robust performance and interpretability in multiclass AD diagnosis.
This article provides a comprehensive review of the use of graphene-based biosensing platforms for the early detection of Alzheimer's disease. It is found that graphene-based biosensors can detect Alzheimer's disease biomarkers at femtomolar concentrations, enabling early diagnosis before symptom onset. These sensors can also identify multiple biomarkers simultaneously in accessible biofluids like blood, saliva, and urine, enabling less invasive testing.
Elsevier,

The Lancet Regional Health - Southeast Asia, Volume 41, October 2025

This viewpoint offers insights on policy to improve diet quality, that resonate not only in Bangladesh but also across other countries navigating similar transitions.

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