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Alzheimer’s disease (AD) is the most common neurodegenerative disease in the world. It is classified as familial and sporadic. The dominant familial or autosomal presentation represents 1–5% of the total number of cases. It is categorized as early onset (EOAD; <65 years of age) and presents genetic mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or the Amyloid precursor protein (APP). Sporadic AD represents 95% of the cases and is categorized as late-onset (LOAD), occurring in patients older than 65 years of age. Several risk factors have been identified in sporadic AD; aging is the main one. Nonetheless, multiple genes have been associated with the different neuropathological events involved in LOAD, such as the pathological processing of Amyloid beta (Aβ) peptide and Tau protein, as well as synaptic and mitochondrial dysfunctions, neurovascular alterations, oxidative stress, and neuroinflammation, among others. Interestingly, using genome-wide association study (GWAS) technology, many polymorphisms associated with LOAD have been identified. This review aims to analyze the new genetic findings that are closely related to the pathophysiology of AD. Likewise, it analyzes the multiple mutations identified to date through GWAS that are associated with a high or low risk of developing this neurodegeneration. Understanding genetic variability will allow for the identification of early biomarkers and opportune therapeutic targets for AD.

Autophagy is a highly conserved lysosomal degradation pathway active at basal levels in all cells. However, under stress conditions, such as a lack of nutrients or trophic factors, it works as a survival mechanism that allows the generation of metabolic precursors for the proper functioning of the cells until the nutrients are available. Neurons, as post-mitotic cells, depend largely on autophagy to maintain cell homeostasis to get rid of damaged and/or old organelles and misfolded or aggregated proteins. Therefore, the dysfunction of this process contributes to the pathologies of many human diseases. Furthermore, autophagy is highly active during differentiation and development. In this review, we describe the current knowledge of the different pathways, molecular mechanisms, factors that induce it, and the regulation of mammalian autophagy. We also discuss its relevant role in development and disease. Finally, here we summarize several investigations demonstrating that autophagic abnormalities have been considered the underlying reasons for many human diseases, including liver disease, cardiovascular, cerebrovascular diseases, neurodegenerative diseases, neoplastic diseases, cancers, and, more recently, infectious diseases, such as SARS-CoV-2 caused COVID-19 disease.

Alzheimer’s disease (AD) is the most common neurodegenerative disease worldwide. Histopathologically, AD presents with two hallmarks: neurofibrillary tangles (NFTs), and aggregates of amyloid β peptide (Aβ) both in the brain parenchyma as neuritic plaques, and around blood vessels as cerebral amyloid angiopathy (CAA). According to the vascular hypothesis of AD, vascular risk factors can result in dysregulation of the neurovascular unit (NVU) and hypoxia. Hypoxia may reduce Aβ clearance from the brain and increase its production, leading to both parenchymal and vascular accumulation of Aβ. An increase in Aβ amplifies neuronal dysfunction, NFT formation, and accelerates neurodegeneration, resulting in dementia. In recent decades, therapeutic approaches have attempted to decrease the levels of abnormal Aβ or tau levels in the AD brain. However, several of these approaches have either been associated with an inappropriate immune response triggering inflammation, or have failed to improve cognition. Here, we review the pathogenesis and potential therapeutic targets associated with dysfunction of the NVU in AD.

Neurodegenerative diseases are characterized by protein aggregation and overlapping pathologies, challenging traditional classifications and highlighting shared underlying mechanisms. Parkinson’s disease and related synucleinopathies, including Lewy body dementia and multiple system atrophy, highlight the interplay between α-synuclein and tau, two key proteins implicated in these disorders. Recent studies reveal that tau and α-synuclein co-aggregate, interact synergistically, and propagate via prion-like mechanisms, exacerbating neuronal dysfunction. This review examines the physiological roles and pathological transitions of tau and α-synuclein, emphasizing their roles in microtubule dynamics, synaptic regulation, and the structural heterogeneity of aggregates. Evidence from post-mortem brains, transgenic models, and proteomic analyses underscores the significance of soluble oligomers as primary neurotoxic species and explores the diverse molecular composition of Lewy bodies and glial cytoplasmic inclusions. The co-localization of tau and α-synuclein, influenced by genetic factors and post-translational modifications, offers insights into shared mechanisms across synucleinopathies and tauopathies. These findings advocate for integrated therapeutic strategies targeting protein cross-seeding and proteostatic disruption while preserving physiological roles. By framing neurodegeneration as a collapse of proteostatic networks rather than isolated proteinopathies, this work proposes a paradigm shift toward understanding and treating complex neurodegenerative disorders.

This paper presents results concerning mechanistic modeling to describe the dynamics and interactions between biomass growth, glucose consumption and ethanol production in batch culture fermentation by Kluyveromyces marxianus (K. marxianus). The mathematical model was formulated based on the biological assumptions underlying each variable and is given by a set of three coupled nonlinear first-order Ordinary Differential Equations. The model has ten parameters, and their values were fitted from the experimental data of 17 K. marxianus strains by means of a computational algorithm design in Matlab. The latter allowed us to determine that seven of these parameters share the same value among all the strains, while three parameters concerning biomass maximum growth rate, and ethanol production due to biomass and glucose had specific values for each strain. These values are presented with their corresponding standard error and 95% confidence interval. The goodness of fit of our system was evaluated both qualitatively by in silico experimentation and quantitative by means of the coefficient of determination and the Akaike Information Criterion. Results regarding the fitting capabilities were compared with the classic model given by the logistic, Pirt, and Luedeking–Piret Equations. Further, nonlinear theories were applied to investigate local and global dynamics of the system, the Localization of Compact Invariant Sets Method was applied to determine the so-called localizing domain, i.e., lower and upper bounds for each variable; whilst Lyapunov’s stability theories allowed to establish sufficient conditions to ensure asymptotic stability in the nonnegative octant, i.e., R+,03. Finally, the predictive ability of our mechanistic model was explored through several numerical simulations with expected results according to microbiology literature on batch fermentation.

The production of secondary metabolites can be improved with the supply of precursors both in submerged and solid-state fermentation (SSF). Microorganisms assimilate the precursors and biotransform them to excrete compounds of commercial interest. The raw materials used in SSF, frequently agro-industrial residues, may contain molecules that serve as precursors for secondary metabolites. However, supplying a precursor can dramatically improve crop production. Commonly, precursors are added as part of the liquid with which the solid material to be fermented is moistened. However, recently it has been proposed to take advantage of the oxygen supply for the gradual supply of volatile precursors. It can help to avoid toxicity problems with the precursors. The present work reviews the strategies to supply precursors to improve the production of secondary metabolites in solid-state fermentation.

During alcoholic fermentations, some non-Saccharomyces yeasts are often displaced by Saccharomyces cerevisiae. It remains unclear whether this displacement is mediated by metabolites produced by S. cerevisiae or depends on cell–cell contact. This study evaluated the effects of extracellular metabolites produced by S. cerevisiae on the growth and fermentative performance of Kluyveromyces marxianus isolated from mezcal fermentations. The development of both yeasts was evaluated in monocultures and in co-cultures with physical contact. Indirect interaction was also tested by exchanging cell-free fermented media. The growth and fermentative response of K. marxianus in cell-free S. cerevisiae-fermented medium showed modulation that depended on the growth phase during which the exchange was performed. The exchange performed at 6 h (exponential phase) limited the maximum growth of K. marxianus and resulted in lower fermentative performance. When the exchange was done during the stationary phase (17.5 h), K. marxianus exhibited a longer stationary phase and better fermentative performance. Finally, when the exchange was performed at 24 h (the beginning of the death phase), the effects on survival and fermentative performance were less pronounced. Furthermore, co-culture with cell–cell contact showed that direct competition and/or mechanisms dependent on physical contact intensify the displacement of K. marxianus. The results show that direct cell–cell contact promotes greater inhibition of K. marxianus by S. cerevisiae, which is relevant for the design of mixed fermentations aimed at achieving a greater contribution of non-Saccharomyces yeasts to the organoleptic characteristics of alcoholic beverages.

GABA A receptors (GABA A Rs) are no longer viewed as uniform inhibitory switches but as structurally diverse, dynamically regulated ensembles that decode inhibitory signals with remarkable spatial and temporal precision. Their heterogeneity arises not only from the nineteen subunit genes but also from the combinatorial logic of assembly, alternative splicing, stoichiometry, post-translational modifications, and adaptive trafficking. These ensembles function as computational modules, tuned to the demands of individual circuits where they regulate excitability, gain control, and plasticity. Here, we highlight how recent advances in cryo–electron microscopy have transformed the field, revealing unexpected conformational states, novel ligand-binding pockets, and regulatory interfaces with accessory proteins, such as NACHO. In vivo studies demonstrate that individual neurons often co-express multiple receptor subtypes, forming heterogeneous ensembles that integrate inputs from GABA, neurosteroids, histamine, endocannabinoids, and exogenous ligands. This ensemble logic reframes inhibition as a circuit-specific computation rather than a uniform force. In this review, we discuss how disorders once attributed to “too little inhibition”—including epilepsy, chronic pain, schizophrenia, and Parkinson’s disease—can now be traced to disruptions in receptor assembly, trafficking, or ensemble composition. We also examine how classical pharmacology, with benzodiazepines and barbiturates as blunt instruments, falls short of capturing this complexity. By contrast, emerging approaches—subtype-selective allosteric modulators, gene editing, chaperone manipulation, and AI-guided ligand design—point toward precision therapeutics that recalibrate inhibition at the level of specific cell types, ensembles, and circuit motifs. Taken together, inhibition emerges not as a static force but as a flexible, ensemble-driven computation embedded in receptor structure and circuit architecture, and modulated by internal states and environmental context. Decoding this logic and learning to manipulate it with precision marks the next frontier in inhibitory neuroscience and the development of next-generation therapies for brain disorders.

Alzheimer's disease (AD) is the most common neurodegenerative disease worldwide, characterized by progressive cognitive decline and, in advanced stages, marked motor impairments. These motor deficits are associated with muscle atrophy, mitochondrial dysfunction, and amyloid- (Aβ) pathology affecting both motor brain areas and peripheral tissues, ultimately contributing to disability, fall risk, and reduced quality of life. Although physical exercise has been shown to confer cognitive and functional benefits in AD, to date, no studies have directly examined the relationship between motor performance and the underlying pathological mechanisms. This study introduces a novel approach by simultaneously addressing muscle pathology and mitochondrial alterations associated with motor decline. Twelve-month-old male triple-transgenic (3xTg-AD) and non-transgenic (Non-Tg) mice were assigned to sedentary or exercise groups (  = 16 each group). The exercise protocol combined voluntary wheel running and forced treadmill training, 5 days/week for 4 months. Motor performance was evaluated using open-field, gait analysis, grip strength, and beam walking tests. Post-intervention, histological analyses evaluated Aβ deposition and mitochondrial morphology, biochemical assays assessed mitochondrial function, and ELISA estimated Aβ levels in the brain and muscle. Physical exercise improved locomotion, balance, and strength in advanced stages of the disease, with modest benefits for memory. Histology showed reduced muscle atrophy and cortical amyloid, but not hippocampal. ELISA detected lower relative levels of Aβ only in the brain. Exercise restored reduced muscle Complex I activity, increased brain Complex IV and ATPase in both tissues, and pronounced changes in mitochondrial morphology in muscle. This study provides the first evidence that physical exercise improves motor function and attenuates muscle and brain pathology in advanced stages of 3xTg-AD, supporting its potential as a complementary therapeutic strategy with translational relevance to humans.