Cerebral small vessel disease (CSVD) refers to a spectrum of clinical and imaging findings resulting from pathological processes of various etiologies affecting cerebral arterioles, perforating arteries, capillaries, and venules. Unlike large vessels, it is a challenge to visualize small vessels in vivo, hence the difficulty to directly monitor the natural progression of the disease. CSVD might progress for many years during the early stage of the disease as it remains asymptomatic. Prevalent among elderly individuals, CSVD has been alarmingly reported as an important precursor of full-blown stroke and vascular dementia. Growing evidence has also shown a significant association between CSVD’s radiological manifestation with dementia and Alzheimer’s disease (AD) pathology. Although it remains contentious as to whether CSVD is a cause or sequelae of AD, it is not far-fetched to posit that effective therapeutic measures of CSVD would mitigate the overall burden of dementia. Nevertheless, the unifying theory on the pathomechanism of the disease remains elusive, hence the lack of effective therapeutic approaches. Thus, this chapter consolidates the contemporary insights from numerous experimental animal models of CSVD, to date: from the available experimental animal models of CSVD and its translational research value; the pathomechanical aspects of the disease; relevant aspects on systems biology; opportunities for early disease biomarkers; and finally, converging approaches for future therapeutic directions of CSVD.

The cerebral endothelium is an active interface between blood and the central nervous system. In addition to being a physical barrier between the blood and the brain, the endothelium also actively regulates metabolic homeostasis, vascular tone and permeability, coagulation, and movement of immune cells. Being part of the blood–brain barrier, endothelial cells of the brain have specialized morphology, physiology, and phenotypes due to their unique microenvironment. Known cardiovascular risk factors facilitate cerebral endothelial dysfunction, leading to impaired vasodilation, an aggravated inflammatory response, as well as increased oxidative stress and vascular proliferation. This culminates in the thrombo-inflammatory response, an underlying cause of ischemic stroke and cerebral small vessel disease (CSVD). These events are further exacerbated when blood flow is returned to the brain after a period of ischemia, a phenomenon termed ischemia-reperfusion injury. Purinergic signaling is an endogenous molecular pathway in which the enzymes CD39 and CD73 catabolize extracellular adenosine triphosphate (eATP) to adenosine. After ischemia and CSVD, eATP is released from dying neurons as a damage molecule, triggering thrombosis and inflammation. In contrast, adenosine is anti-thrombotic, protects against oxidative stress, and suppresses the immune response. Evidently, therapies that promote adenosine generation or boost CD39 activity at the site of endothelial injury have promising benefits in the context of atherothrombotic stroke and can be extended to current CSVD known pathomechanisms. Here, we have reviewed the rationale and benefits of CD39 and CD39 therapies to treat endothelial dysfunction in the brain.

This article provides a comprehensive review of deep learning-based blood vessel segmentation of the brain. Cerebrovascular disease develops when blood arteries in the brain are compromised, resulting in severe brain injuries such as ischemic stroke, brain hemorrhages, and many more. Early detection enables patients to obtain more effective treatment before becoming critically unwell. Due to the superior efficiency and accuracy compared to manual segmentation and other computer-assisted diagnosis procedures, deep learning algorithms have been extensively deployed in brain vascular segmentation. This study examined current articles on deep learning-based brain vascular segmentation, which examined the proposed methodologies, particularly the network architectures, and determined the model trend. We evaluated challenges and crucial factors associated with the application of deep learning to brain vascular segmentation, as well as future research prospects. This paper will assist researchers in developing more sophisticated and robust models in the future to develop deep learning solutions.

Despite decades of research, Alzheimer’s disease (AD) remains without a curative therapy. While amyloid- and tau-centered approaches have dominated the field, failures of monotherapeutic strategies underscore the need for a broader system-level understanding. Here, this review critically revisits the principal hypotheses of AD pathogenesis, including the amyloid cascade, tauopathy, neuroinflammation, cholinergic dysfunction, oxidative and mitochondrial stress, metal dyshomeostasis, autophagy–lysosomal failure, genetic susceptibility, and infectious triggers. This review synthesizes molecular and cellular evidence from human genetics, neuropathology, and experimental models, correcting common misconceptions and emphasizing interactions between pathways. Neuroinflammation is increasingly recognized as a central hub linking amyloid, tau, and vascular factors, while mitochondrial and lysosomal dysfunctions emerge as amplifiers of proteotoxic stress. Genetic studies highlight apolipoprotein-E ε4 (APOE ε4) as the strongest common risk allele, but also implicate genes involved in endosomal trafficking, lipid metabolism, and immune regulation. Taken together, AD is best understood as a multi-hit disorder in which converging processes, rather than a single driver, dictate disease initiation and progression. This narrative review proposes a systems neurobiology framework that integrates these mechanisms and identifies key points of convergence amenable to therapeutic targeting and biomarker development. Finally, this reappraisal aims to inform future research directions and guide the rational design of multi-target interventions.

Centella asiatica (C. asiatica) has attracted significant scientific interest due to its extensive medicinal properties and long-established use in traditional medicine. This review synthesizes recent advances in the technological exploitation of C. asiatica, covering the extraction of bioactive constituents to product development. Modern extraction techniques such as supercritical fluid extraction (SFE) and microwave-assisted extraction (MAE) have substantially improved the yield, selectivity, and preservation of key phytochemicals, particularly triterpenoids, saponins, and flavonoids. These compounds are now routinely characterized using advanced analytical platforms, ensuring product quality, consistency, and standardization. Moreover, the use of innovative formulation technologies and advanced delivery systems has facilitated the development of C. asiatica-based products tailored for various therapeutic areas, including pharmaceuticals, nutraceuticals, and cosmeceuticals targeting neuroprotection, wound healing, skin aging, and stress modulation. Alongside these developments, stringent quality control protocols, toxicological evaluations, and adherence to evolving regulatory standards enhance the safety and efficacy of C. asiatica-derived interventions. This review highlights the integration of traditional knowledge with modern science across the domains of extraction, analysis, formulation, and regulation. It serves as a comprehensive resource for researchers, formulators, and regulatory stakeholders aiming to develop high-quality, evidence-based C. asiatica products with improved bioavailability and therapeutic value.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, cognitive decline, and pathological hallmarks such as amyloid-beta (Aβ) plaques and tau neurofibrillary tangles. Recent evidence highlights autophagy as a pivotal mechanism in cellular homeostasis, mediating the clearance of misfolded proteins and damaged organelles. However, impaired autophagy contributes significantly to AD pathogenesis by disrupting proteostasis, exacerbating neuroinflammation, and promoting synaptic dysfunction. This review aims to scrutinize the intricate relationship between autophagy dysfunction and AD progression, explaining key pathways including macroautophagy, chaperone-mediated autophagy (CMA), and selective autophagy processes such as mitophagy and aggrephagy. This further extends the discussion beyond the central nervous system, evaluating the role of hepatic autophagy in Aβ clearance and systemic metabolic regulation. An understanding of autophagy’s involvement in AD pathology via various mechanisms could give rise to a novel therapeutic strategy targeting autophagic modulation to mitigate disease progression in the future.