Language impairment is a core clinical manifestation of Alzheimer's disease (AD) that profoundly affects autonomy, decision-making, and social participation. Building upon the 2015 review by Kuca et al., this narrative review synthesizes empirical evidence from 2016 through 2026. A structured Web of Science Core Collection search retrieved 154 records. Following screening, 66 records were excluded and 88 full-text reports were appraised, of which 13 were consolidated, yielding 75 cited core empirical studies alongside foundational diagnostic, neuropathological, and trial benchmarks. Four main areas are synthesized. First, progressive linguistic decline across clinical stages is characterized, delineating typical amnestic AD dementia, mild cognitive impairment due to AD, and the logopenic variant of primary progressive aphasia (lvPPA), highlighting the necessity of biological amyloid and tau biomarker confirmation. Second, automated speech and natural language processing biomarkers have emerged as scalable tools predicting progression to dementia and detecting biological amyloid-beta positivity; however, real-world translation remains constrained by demographic bias, cross-linguistic variations, acoustic sensitivity, and privacy issues. Third, non-pharmacological interventions, including structured language stimulation and naming therapy, demonstrate measurable task-specific improvements; nevertheless, gains are largely restricted to trained items with minimal transfer to everyday discourse. Caregiver communication training programs reliably improve dyadic interactions and mitigate caregiver distress. Fourth, approved symptomatic drugs do not directly reverse language decline, and add-on memantine in the randomized ROMEO-AD trial produced no statistically significant language benefit over donepezil alone. Disease-modifying anti-amyloid antibodies offer biological intervention for biomarker-positive lvPPA, but pivotal trials lacked primary speech endpoints, establishing eligibility rather than demonstrated language recovery. Non-invasive neuromodulation remains preliminary and requires sham-controlled trials. Communication should be recognized as a distinct clinical outcome in trial designs, prioritizing standardized speech endpoints to assess disease-modifying therapies.

Alzheimer's disease (AD) usually follows a slowly progressive course, but some patients experience unusually rapid cognitive and functional decline. This clinical phenotype, commonly termed rapidly progressive Alzheimer's disease (rpAD), has no consensus definition; its status as a distinct biological entity remains unresolved, and its reported frequency depends strongly on operational criteria and referral settings. To synthesize current evidence, we conducted targeted literature searches (up to August 31, 2026) of clinical, neuropathological, and biomarker studies. This narrative review extends earlier overviews by integrating newer genetic, tau-seeding, and blood-biomarker findings with conflicting clinical evidence, while distinguishing candidate mechanisms from established diagnostic tools. Selected autopsy and biomarker studies suggest differences in amyloid-β and tau conformations, synaptic and mitochondrial proteins, neuroinflammatory responses, and concomitant pathologies; however, most data are associative, derive from small or selected cohorts, and do not establish rpAD as a discrete disease subtype. In practice, evaluation should confirm AD pathology while promptly excluding treatable causes and rapidly progressive mimics, particularly Creutzfeldt-Jakob disease (CJD), using established tools such as cerebrospinal fluid biomarkers, MRI, and PrP RT-QuIC. Cerebrospinal fluid, molecular imaging, structural MRI, and emerging blood biomarkers can provide supportive evidence, but no biomarker profile has been prospectively validated as an rpAD-specific diagnostic rule. Harmonized definitions and prospective, biomarker-stratified multicenter validation are required before candidate mechanisms or biomarkers can guide rpAD-specific interventions.

With the acceleration of population aging and the progressive decline in physiological function, older adults with diabetes frequently present with multiple chronic conditions. This not only increases the complexity of clinical management but also adversely affects disease prognosis, quality of life, and the efficient allocation of healthcare resources. Traditional single-disease-centered management models are increasingly inadequate for addressing the complex and heterogeneous healthcare needs of these patients. Consequently, there is an urgent need to shift toward personalized and integrated management strategies guided by patients' overall health status and functional needs. A literature search was conducted in PubMed and Web of Science for studies published from 2014 to 2026, using combinations of keywords related to diabetes, older adults, multimorbidity, comorbidity, polypharmacy, comprehensive geriatric assessment, and multidisciplinary management. Inclusion criteria encompassed original studies, clinical trials, systematic reviews, meta-analyses, clinical guidelines, and consensus statements focusing on multimorbidity and its management in older adults with diabetes. Studies unrelated to the target population or research topic were excluded. The available evidence indicates that multimorbidity in older adults with diabetes is characterized by complex interactions across multiple organ systems and presents substantial challenges in therapeutic decision-making, polypharmacy, and treatment adherence. Comprehensive geriatric assessment, individualized treatment targets, shared decision-making, medication optimization and deintensification, and multidisciplinary collaboration represent important approaches to addressing these challenges. Emerging technologies, including real-time continuous glucose monitoring, electronic health records, digital health platforms, and integrated data analytics, may further facilitate dynamic risk monitoring, coordinated decision-making, and continuity of care. Overall, management should progressively shift from a disease-centered paradigm toward personalized, integrated, and function-oriented care, with greater emphasis on preserving functional independence, minimizing treatment burden, and improving quality of life in older adults with diabetes and multimorbidity.

Quadriceps weakness is a major determinant of disability in knee osteoarthritis (KOA), particularly in later life, yet weakness often exceeds the loss of muscle size. This discrepancy is clinically important because joint-derived activation failure occurs against a background of declining neuromuscular and regenerative reserve. We critically examine an evidence-bounded joint-afferent-motor unit framework in which abnormal afferent input from the diseased knee reduces effective neural drive through arthrogenic muscle inhibition (AMI). Persistent under-recruitment may be associated with altered motor-unit behavior and loading, impaired muscle quality, and greater reliance on compensatory reinnervation. We deliberately distinguish demonstrated human observations from provisional transitions and hypothesis-generating mechanistic extensions. Human evidence supports AMI and impaired muscle quality and provides preliminary cross-sectional evidence of altered motor-unit behavior; however, human studies have not established a temporal sequence from persistent AMI to motor-unit remodeling or denervation-reinnervation. Direct KOA-related neuromuscular junction (NMJ) evidence remains predominantly preclinical, and progressive NMJ degeneration has not been demonstrated in humans with KOA. Aging, sex, obesity, diabetes, systemic inflammation, pain sensitization, inactivity, and other comorbidities are treated as effect modifiers and competing explanations rather than proof of causation. We propose a testable, multimodal validation strategy combining joint imaging, standardized voluntary-activation testing, neurophysiology, high-density electromyography, motor-unit-number estimation, muscle imaging, and, when justified, tissue-level NMJ phenotyping. For older adults, the practical implication is mechanism-directed care: restore joint-related activation when inhibition dominates, use neural augmentation to enable adequate loading, address muscle-quality and metabolic constraints when present, and reserve NMJ-directed interventions for future human subgroups defined by convergent structural and physiological evidence.

Older adults living in long-term care settings, particularly those with cognitive impairment and apathy, frequently experience reduced social engagement. Socially assistive robots and virtual reality systems may help support engagement, but little is known about whether they can sustain engagement during real-world deployment while also facilitating interaction between older adults. This study examined whether socially structured socially assistive robot-virtual reality (SAR-VR) systems could sustain engagement and support human-human interaction during repeated use in long-term care settings.