Autonomous University of Queretaro

This study evaluated the effects of thermocomposting followed by vermicomposting on the physicochemical properties of insect frass and its suitability as a germination and growth substrate for kale, tomato, and bell pepper. Vermicomposting improved frass stability by reducing pH, electrical conductivity, carbon content, and the C/N ratio, while increasing total nitrogen, cation exchange capacity, and calcium and magnesium availability, indicating enhanced maturity and nutrient retention. Peat–frass mixtures (20–100%), increased pH from acidic conditions in the control to near neutral in 100% frass and raised electrical conductivity from 0.67 dS m−1 to the highest values in the pure frass treatment. Tomato seedlings exhibited strong tolerance and enhanced growth at all frass proportions, with seedling heights exceeding 33 cm compared with the control. Kale showed optimal growth at 20–60% frass, while 80–100% reduced early development. In bell pepper, emergence declined at high frass proportions, although seedlings grown with ≥40% frass reached heights of approximately 8.3–8.6 cm. Vermicomposted frass also influenced plant metabolism, increasing flavonoid accumulation and modifying antioxidant activity. These findings demonstrate that stabilized frass can serve as a sustainable substrate component, contributing to organic waste valorization and improved seedling production when applied at crop-specific proportions.

Two-wheeled self-balancing robots (TWSBRs) are difficult to control because they are nonlinear, unstable, and underactuated, particularly when balance, velocity regulation, and line tracking must be achieved simultaneously. This paper proposes a hybrid parallel control architecture for a line-following TWSBR operating on straight segments, 90∘ curves, and a 15∘ slope. Balance stabilization is handled by a classical PD loop, while traslational velocity is regulated by an adaptive fuzzy PI controller, and line following is performed with an adaptive fuzzy PD controller. The fuzzy modules adjust the effective gains based on tracking errors, thereby improving robustness to disturbances, sensor noise, and changes in operating conditions. The complete strategy is implemented on a low-cost PIC18F4550 microcontroller. Experiments show that the fuzzy line-following controller reduces the orientation tracking error compared with a conventional controller. At 0.10ms, RMSE decreases from 0.042rad to 0.038rad, and at 0.175ms, it decreases from 0.083rad to 0.066rad. The fuzzy approach also improves IAE (1.317rads to 1.185rads) and ISE (0.242rad2s to 0.153rad2s) at 0.175ms, while maintaining similar maximum error (0.299rad to 0.261rad). Overall, the proposed hybrid scheme achieves better adaptability without retuning. These results support real-time deployment on resource-limited platforms.

This study investigates whether inter-channel similarity, quantified using Pearson’s correlation, can be used as an indicator of electrode relevance in electroencephalography (EEG)-based motor imagery (MI) classification and compares this approach with a genetic algorithm (GA)-based electrode selection strategy. Electrode subsets were obtained using Pearson correlation ranking, a GA optimizing classification accuracy, and the reference-study electrode subset reported in prior work. All subsets were evaluated on the BCI Competition IV Dataset 2a using a unified classifier architecture, and the sensitivity to classifier hyperparameter configuration was analyzed. Pearson-based selection achieved accuracies of 75.8% (8 channels), 78.1% (10 channels), and 81.5% (12 channels), while the GA achieved 75.9% (8 channels), 78.8% (10 channels), and 80.0% (13 channels). The reference-study electrode subset reached 75.0% (8 channels) and 76.7% (10 channels). Although correlation-based selection yielded competitive performance, no consistent relationship was observed between inter-channel similarity and discriminative relevance, and classification performance showed notable sensitivity to hyperparameter settings. These findings indicate that inter-channel similarity alone is not sufficient to determine electrode importance in MI classification and support the use of data-driven, model-aware selection strategies for the design of efficient low-channel-count brain–computer interface systems.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as NAFLD (non-alcoholic fatty liver disease), is a growing global concern, affecting nearly a third of the world’s population. This umbrella term covers a range of liver pathologies, from reversible disease stages like simple steatosis, to irreversible conditions such as cirrhosis and hepatocellular carcinoma (HCC). MASLD, which may result from metabolic risk factors like obesity and type 2 diabetes, is projected to increase due to a rise in sedentary lifestyles. This review addresses genetic influences that predispose to disease development, including the role of risk-conferring and protective/preventive alleles. The epistatic relationships between genetic variants can significantly influence the development and progression of MASLD. Key genetic variants, such as those located in the PNPLA3, TM6SF2, and MBOAT7 genes, often interact to exacerbate MASLD severity and play key roles in lipid metabolism and liver inflammation. For example, the co-expression of certain PNPLA3 and TM6SF2 variants increases the risk of advanced fibrosis and HCC. Some variants located in HSD17B13 and MTARC1 offer protective effects, reducing the risk of severe liver disease despite comorbidities such as obesity, and can mitigate the harmful effects of these risk alleles. Additionally, the potential of polygenic risk scores (PRS) to predict MASLD development and its complications is also discussed, although challenges remain, particularly in underrepresented populations due to the lack of comprehensive catalogues of genetic variation. Understanding these complex gene-gene interactions and the role of the environment underscores the importance of considering epistatic relationships when assessing MASLD risk and developing personalized therapeutic strategies, which could ease the future burden on healthcare systems. · Metabolic dysfunction-associated steatotic liver disease (MASLD) affects nearly one-third of the global population, with rising incidence due to sedentary lifestyles, obesity, and type 2 diabetes. · It is estimated that nearly 50% of MASLD patients have heritable predisposition genetic variants in genes such as PNPLA3 and TM6SF2, which play significant roles in MASLD development. · Several protective alleles have also been identified, which may mitigate MASLD progression despite genetic variants and environmental risk factors. · Epistatic relationship between predisposing and protective genes can influence Polygenic Risk Score and improve the precision detection and early diagnosis of liver metabolic diseases. · Risk-modifying variants have different allelic frequencies according to the population considered.

BackgroundThe retrosplenial cortex (RSC) is a cortical area that functions as a key component of the core network of brain regions involved in cognitive functions such as episodic memory, navigation, and planning. The RSC is capable of theta rhythm generation and, like the hippocampus, could be compromised in neurological diseases such as Alzheimer's disease (AD). Importantly, detecting early changes in RSC of transgenic animals could be translated into non-invasive biomarkers that can detect preclinical stages of AD and related dementias.ObjectiveOur aim in the present study was to evaluate molecular and functional alterations in the RSC of very young 3xTg-AD mice (1-month-old).MethodsImmunohistochemistry, anterograde viral tracer using an adeno-associated virus, western blotting, and electrophysiology were all carried out.ResultsOur results show significant accumulation of intracellular amyloid-β (Aβ) and hyperphosphorylated tau (pTau) in principal neurons from 1-month-old 3xTg-AD mice, which correlates with GSK3β activation and tau phosphorylation at serine 396. Coincidentally, oscillatory activity from the RSC is altered in the young 3xTg-AD mice. Specifically, we found that theta frequency is significantly higher in the transgenic animals.ConclusionsIn summary, our results suggest that the early accumulation of intracellular Aβ may affect the excitability of the RSC network, possibly due to changes in pTau resulting from GSK3β activation.

La informalidad y la competitividad son dos categorías que convergen en las ciudades latinoamericanas y que contribuyen a la construcción de identidad urbana. No obstante, la competitividad suele imponerse sobre los ordenamientos territoriales y se inserta en el entramado del ejercicio de poder, particularmente en los espacios centrales de la ciudad. El objetivo de esta investigación fue describir la relación entre las categorías de análisis —competitividad e informalidad— a partir de sus diametralidades con la formalidad en el Centro Histórico de la ciudad de Querétaro. Metodológicamente, se empleó la observación con un acercamiento etnográfico, apoyado en el diario de campo. Posteriormente, se realizó un análisis deductivo basado en las dos categorías analíticas mencionadas. Los hallazgos evidencian que la competitividad funciona como un elemento político asociado al poder, la planeación y el ordenamiento urbano de Santiago de Querétaro, particularmente en su Centro Histórico. Asimismo, se identifican formas de resistencia por parte de quienes trabajan en la informalidad o el autoempleo, quienes experimentan procesos de desplazamiento y restricciones en el uso y apropiación del espacio público. Desde una perspectiva social, el estudio muestra las tensiones de una ciudad que se proyecta como competitiva, pero que al mismo tiempo reproduce desigualdades. Se concluye que la competitividad no es ajena a la informalidad, sino que ambas coexisten en un mismo entramado social, político, cultural e institucional. Aunque se presentan como elementos dicotómicos y aparentemente opuestos, en la práctica se articulan y se condicionan mutuamente.