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BACKGROUND Dementia, including Alzheimer's disease (AD), is a growing concern in Egypt, yet biomarker research in this population is scarce. Identifying serum biomarkers is essential for early diagnosis and understanding disease mechanisms in underrepresented groups. METHODS We performed serum proteomic profiling on 20 Egyptian dementia patients and 10 cognitively unimpaired controls from the Egyptian Dementia Registry using mass spectrometry. Differential protein expression and pathway enrichment analyses were conducted. RESULTS Of 260 quantified proteins, 21 were significantly different between dementia patients and controls (P < 0.05). Several serine protease inhibitor and immunoglobulin family proteins were downregulated, while apolipoprotein A‐II was upregulated in dementia. Enrichment analysis revealed associations with inflammation, complement activation, and lipid metabolism pathways. CONCLUSION This is the first serum proteomic study of dementia in an Egyptian cohort, highlighting coordinated changes in protein families involved in inflammation and lipid metabolism, and emphasizing the importance of biomarker research in diverse populations. Highlights The study presents initial proteomic data from the Egyptian Dementia Registry. The Egyptian population has been underrepresented in the area of dementia research. Serine protease inhibitor G1, apolipoprotein A‐II, and lipopolysaccharide binding protein emerged as significant proteins. The work lays the foundation for more understanding of molecular determinants in dementia in the Middle East.

INTRODUCTION Dementia is a growing public health challenge in low‐ and middle‐income countries (LMICs) like Egypt, where data are scarce. The Egyptian Dementia Network (EDN) registry addresses this gap by capturing epidemiological, clinical, and environmental data across Egypt. METHODS In this multicenter study, 662 participants from six governorates were enrolled using standardized tools. RESULTS The cohort had advanced age (mean 68.3 years), low education (65.9% illiterate), and high comorbidities including hypertension (55%) and diabetes (23%). Alzheimer's disease (62%) and vascular dementia (23%) predominated. Only 24.4% received pharmacological treatment and 2.1% psychosocial support, highlighting care gaps. Household insecticide exposure (20.4%) was notable. DISCUSSION EDN demonstrates the feasibility of implementing a national dementia registry in LMICs, generating baseline insights into demographic, clinical, and environmental risks. In addition, registry‐linked biosamples have enabled pilot multi‑omics and exposome analyses, underscoring its potential as a scalable scientific platform for future dementia research. Highlights Established Egypt's first national, multicenter dementia registry. Aimed to characterize dementia profiles and care gaps across diverse regions. Identified late‐stage diagnosis and limited access to dementia interventions. Uncovered unique environmental risk factors relevant to the Egyptian context. Provides a foundation for policy, research, and improved dementia care in Egypt. Overview of the Egyptian Dementia Network (EDN) registry highlighting multiple centers’ inclusion, cohort demographics, dementia diagnosis, and interventions.

Dementia poses a significant global health challenge, with increasing impact on individuals and healthcare systems. This study aims to investigate the metabolic profiles of clinical Alzheimer’s disease (AD) and vascular dementia (VaD) patients in Egypt, seeking to identify connections between metabolic disruptions and environmental factors. Utilizing serum samples from 61 AD patients and 76 VaD patients compared to 100 healthy controls, the research employed untargeted LC-MS and generalized regression analysis. The findings revealed significant alterations in 59 metabolites in AD patients and 69 in VaD patients, including environmental contaminants. Additionally, pathway enrichment analysis indicated distinct metabolic pathways affected in each group, such as amino acid metabolism in AD and purine metabolism in VaD. This research provides insights into the biological pathways and environmental agents linked to dementia, highlighting the need for diverse populations in metabolomic studies to improve prevention and intervention strategies globally.

Recent advances in additive manufacturing (AM) have attracted significant industrial interest. Initially, AM was mainly associated with the fabrication of prototypes, but the AM advances together with the broadening range of available materials, especially for producing metallic parts, have broaden the application areas and now the technology can be used for manufacturing functional parts, too. Especially, the AM technologies enable the creation of complex and topologically optimised geometries with internal cavities that were impossible to produce with traditional manufacturing processes. However, the tight geometrical tolerances along with the strict surface integrity requirements in aerospace, biomedical and automotive industries are not achievable in most cases with standalone AM technologies. Therefore, AM parts need extensive post-processing to ensure that their surface and dimensional requirements together with their respective mechanical properties are met. In this context, it is not surprising that the integration of AM with post-processing technologies into single and multi set-up processing solutions, commonly referred to as hybrid AM, has emerged as a very attractive proposition for industry while attracting a significant R&D interest. This paper reviews the current research and technology advances associated with the hybrid AM solutions. The special focus is on hybrid AM solutions that combine the capabilities of laser-based AM for processing powders with the necessary post-process technologies for producing metal parts with required accuracy, surface integrity and material properties. Commercially available hybrid AM systems that integrate laser-based AM with post-processing technologies are also reviewed together with their key application areas. Finally, the main challenges and open issues in broadening the industrial use of hybrid AM solutions are discussed.

A key advantage of additive manufacturing (AM) is that it allows the fabrication of lattice structures for customized biomedical implants with high performance. This paper presents the use of statistical approaches in design optimization of additively manufactured titanium lattice structures for biomedical implants. Design of experiments using response surface and analysis of variance was carried out to study the effect design parameters on the properties of the AM lattice structures such as ultimate compression strength, specific compressive strength, elastic modulus, and porosity. In addition, the lattice dimensions were optimized to fabricate a diamond cellular structure with properties that match human bones. The study found that the length of a diamond-shaped unit cell strut is the most significant design parameter. In particular, the porosity of the unit cell increases as the strut length increases, while it had a significant reverse effect on the specific compressive strength, elastic modulus, and ultimate compression strength. On the other hand, increasing the orientation angle was found to reduce both the specific compressive strength and modulus of elasticity of the lattice structure. An optimized lattice structure with strut diameter of 0.84 mm, length of 3.29 mm, and orientation angle of 47° was shown to have specific compressive strength, elastic modulus, ultimate compression strength, and porosity of 37.8 kN m/kg, 1 GPa, 49.5 MPa, and 85.7%, respectively. A cellular structure with the obtained properties could be effectively applied for trabecular bone replacement surgeries.

The penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WTs) and photovoltaics (PVs) is highly uncertain. Their correlation with load demand is not always guaranteed, which compromises system reliability. Distributed energy resources (DERs), especially demand response (DR) programs and energy storage systems (ESSs), are possible options to overcome these operational challenges under the virtual power plant (VPP) setting. This study investigates the impact of using a DR program and battery energy storage system (BESS) on the VPP’s internal electricity market, and also cost-minimization analysis from a utility viewpoint. Three different constrained optimal power flow (OPF) problems are solved such as base case, DR case, and BESS case to determine total incurred costs, locational marginal prices (LMPs), and generator commitments. A scenario tree approach is used to model the uncertainties associated with WTs, PVs, and load demand. The proposed model is investigated on a 14-bus distribution system. The simulation results obtained demonstrate a favorable impact of DR and a BESS on renewable operational challenges.

Ceramic materials are increasingly used in micro-electro-mechanical systems (MEMS) as they offer many advantages such as high-temperature resistance, high wear resistance, low density, and favourable mechanical and chemical properties at elevated temperature. However, with the emerging of additive manufacturing, the use of ceramics for functional and structural MEMS raises new opportunities and challenges. This paper provides an extensive review of the manufacturing processes used for ceramic-based MEMS, including additive and conventional manufacturing technologies. The review covers the micro-fabrication techniques of ceramics with the focus on their operating principles, main features, and processed materials. Challenges that need to be addressed in applying additive technologies in MEMS include ceramic printing on wafers, post-processing at the micro-level, resolution, and quality control. The paper also sheds light on the new possibilities of ceramic additive micro-fabrication and their potential applications, which indicates a promising future.

Hollow auxetic structures enable lightweight mechanical design by reducing mass while preserving architected deformation. However, hollow auxetic studies focus on LPBF metals. This study presents a manufacturing-constrained design and validation framework for a hollow hybrid re-entrant chiral lattice produced by stereolithography. The unit cell was parameterised by chiral angle, re-entrant strut length, and hollow internal diameter, with drainage features integrated into the CAD model to preserve hollow channels during printing and post-processing. A minimum internal diameter study defined the printable design window. Within these limits, a central composite design coupled with finite element analysis mapped the response surface and identified an optimised geometry of θ = 15°, L = 3.5 mm, and d = 1.68 mm, with a predicted unit-cell negative Poisson’s ratio of about −1.17. Compression testing confirmed that the printed unit cell and 3 × 3 × 3 lattice retained the intended rotation-dominated auxetic deformation mode. At the selected comparison strain, the unit cell showed a negative Poisson’s ratio of −0.68 and the 3 × 3 × 3 lattice showed −0.29. Relative to the solid lattice, the hollow lattice reduced density by 42.4% with only a 3.0% reduction in stiffness, increasing specific stiffness by 68.9% and specific peak strength by 5.2%, but reducing specific energy absorption by 25.6% due to earlier localisation and junction driven fracture. These results provide practical design guidance for manufacturable hollow SLA auxetic lattices, especially for lightweight and stiffness-limited applications where low mass and high specific stiffness are more important than energy absorption.

Origami structures have attracted attention in biomedical applications due to their ability to develop surgical tools that can be expanded from a minimal volume to a larger and functional device. On the other hand, four-dimensional (4D) printing is an emerging technology, which involves 3D printing of smart materials that can respond to external stimuli such as heat. This short communication introduces the proof of concept of merging origami and 4D printing technologies to develop minimally invasive delivery of functional biomedical scaffolds with high shape recovery. The shape-memory effect (SME) of the PLA filament and the origami designs were also assessed in terms of deformability and recovery rate. The results showed that herringbone tessellation origami structure combined with internal natural cancellous bone core satisfies the design requirement of foldable scaffolds. The substantial and consistent SME of the 4D printed herringbone tessellation origami, which exhibited 96% recovery compared to 61% for PLA filament, was the most significant discovery of this paper. The experiments demonstrated how the use of 4D printing in situ with origami structures could achieve reliable and repeatable results, therefore conclusively proving how 4D printing of origami structures can be applied to biomedical scaffolds.