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The spiking activity of neuronal networks follows laws that are not time-reversal symmetric; the notion of pre-synaptic and post-synaptic neurons, stimulus correlations and noise correlations have a clear time order. Therefore, a biologically realistic statistical model for the spiking activity should be able to capture some degree of time irreversibility. We use the thermodynamic formalism to build a framework in the context maximum entropy models to quantify the degree of time irreversibility, providing an explicit formula for the information entropy production of the inferred maximum entropy Markov chain. We provide examples to illustrate our results and discuss the importance of time irreversibility for modeling the spike train statistics.

In the Faculty of Dentistry of the Catholic University of Cuenca, located in the city of Cuenca, province of Azuay. The lecture hall and the clinics of the faculty are built. These structures were built during 2018 and 2019. Due to the seismic events occurred in recent years, monitoring was carried out to obtain the characterization of the dynamic behaviour. The two structures are formed by a structural system based on structural steel frames (beam-column), the structure for laboratory use has metal columns filled with concrete, while the structure for classroom use has metal columns without concrete filling. The main objective was to obtain the vibration periods experimentally from the recording of environmental vibrations and also to obtain them analytically with mathematical models elaborated in structural analysis programs and environmental vibration tests were performed. The results show that building 1, composed by the dentistry clinic, obtained a vibration period of 0.41 s in X and 0.33 s in Y (Analytical Model); and, in the environmental vibration test it showed a period of 0.46 s in X and, 0.30 in Y. Building 2, composed of the dental faculty classroom, obtained periods of 0.53 s in X and 0.29 s in Y (Analytical Model). While in the environmental vibration studies they gave values of 0.52 s in X and 0.26 in Y.

The Thermodynamic Formalism provides a rigorous mathematical framework for studying quantitative and qualitative aspects of dynamical systems. At its core, there is a variational principle that corresponds, in its simplest form, to the Maximum Entropy principle. It is used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of science. In particular, it has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, in order to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.

Insects are often associated with diverse microorganisms that enhance their metabolism and nutrient assimilation. These microorganisms, residing in the insect’s gut, play a crucial role in breaking down complex molecules into simpler compounds essential for the host’s growth. This study investigates the diversity and functional potential of symbiotic bacteria in the gut of Arsenura armida (Lepidoptera: Saturniidae) larvae, an edible insect from southeastern Mexico, using culture-dependent and metagenomic approaches. Bacterial strains were isolated from different gut sections (foregut, midgut, and hindgut) and cultured on general-purpose media. Isolates were identified through 16S rRNA gene sequencing and genomic fingerprinting. Metagenomics revealed the bacterial community structure and diversity, along with their functional potential. A total of 96 bacterial strains were isolated, predominantly Gram-negative bacilli. Rapidly growing colonies exhibited enzymatic activity, cellulose degradation, and sugar production. Phylogenetic analysis identified eight genera, including Acinetobacter, Bacillus, Enterobacter, Pseudomonas, and others, with significant cellulose-degrading capabilities. Metagenomics confirmed Bacillota as the most abundant phylum. These complementary methods revealed abundant symbiotic bacteria with key metabolic roles in A. armida, offering promising biotechnological applications in enzymatic bioconversion and cellulose degradation.

We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. To find the maximum entropy Markov chain, we use the thermodynamic formalism, which provides insightful connections with statistical physics and thermodynamics from which large deviations properties arise naturally. We provide an accessible introduction to the maximum entropy Markov chain inference problem and large deviations theory to the community of computational neuroscience, avoiding some technicalities while preserving the core ideas and intuitions. We review large deviations techniques useful in spike train statistics to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability, and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.

Psoriasis has been related to metabolic dysfunction-associated fatty liver disease and, liver fibrosis. This study aimed to evaluate the prevalence of liver fibrosis in psoriasis and identify predictors for fibrosis. This is a cross-sectional study conducted from December 2012 to June 2016 assessing psoriasis and psoriatic arthritis patients attended at four centers in Mexico City. Data regarding history of the skin disease, previous and current medication, and previously diagnosed liver disease was collected. Liver fibrosis was assessed with four different non-invasive methods (FIB4, APRI, NAFLD score and elastography). We compared data based on the presence of fibrosis. Adjusted-logistic regression models were performed to estimate OR and 95% CI. A total of 160 patients were included. The prevalence of significant fibrosis using elastography was 25% (n = 40), and 7.5% (n = 12) for advanced fibrosis. Patients with fibrosis had higher prevalence of obesity (60% vs 30.8%, P = 0.04), type 2 diabetes (40% vs 27.5%, P = 0.003), gamma-glutamyl transpeptidase levels (70.8±84.4 vs. 40.1±39.2, P = 0.002), and lower platelets (210.7±58.9 vs. 242.8±49.7, P = 0.0009). Multivariate analysis showed that body mass index (OR1.11, 95%CI 1.02–1.21), type 2 diabetes (OR 3.44, 95%CI 1.2–9.88), and gamma-glutamyl transpeptidase (OR 1.01, 95%CI1-1.02) were associated with the presence of fibrosis. The use of methotrexate was not associated. Patients with psoriasis are at higher risk of fibrosis. Metabolic dysfunction, rather than solely the use of hepatotoxic drugs, likely plays a major role; it may be beneficial to consider elastography regardless of the treatment used. Metabolic factors should be assessed, and lifestyle modification should be encouraged.

Microbial symbioses play crucial roles in insect physiology, contributing to nutrition, detoxification, and metabolic adaptations. However, the microbial communities associated with the lac insect Llaveia axin axin, an economically significant species used in traditional lacquer production, remain poorly characterized. In this study, the bacterial diversity and community structure of L. axin axin were investigated using both culture-dependent and culture-independent (metagenomic) approaches, combined with fatty acid profile analysis. The insects were bred at the laboratory level, in controlled conditions, encompassing stages from eggs to adult females. Bacterial strains were isolated from bacteriomes and identified through 16S rRNA gene amplification and genomic fingerprinting through ARDRA analysis. Metagenomic DNA was sequenced using the Illumina MiSeq platform, and fatty acid profiles were determined by gas chromatography–mass spectrometry (GC-MS). A total of 20 bacterial strains were isolated, with Acinetobacter, Moraxella, Pseudomonas, and Staphylococcus detected in first-instar nymphs; Methylobacterium, Microbacterium, and Bacillus in pre-adult females; and Bacillus and Microbacterium in adults. Metagenomic analysis revealed key genera including Sodalis, Blattabacterium, and Candidatus Walczuchella, with Sodalis being predominant in early stages and Blattabacteriaceae in adults. Fatty acid analysis identified palmitic, oleic, linoleic, arachidic, and stearic acids, with stearic acid being the most abundant. These results suggest that dominant bacteria contribute to lipid biosynthesis and metabolic development in L. axin axin.

Psoriasis has been related to metabolic dysfunction-associated fatty liver disease and, liver fibrosis. This study aimed to evaluate the prevalence of liver fibrosis in psoriasis and identify predictors for fibrosis. This is a cross-sectional study conducted from December 2012 to June 2016 assessing psoriasis and psoriatic arthritis patients attended at four centers in Mexico City. Data regarding history of the skin disease, previous and current medication, and previously diagnosed liver disease was collected. Liver fibrosis was assessed with four different non-invasive methods (FIB4, APRI, NAFLD score and elastography). We compared data based on the presence of fibrosis. Adjusted-logistic regression models were performed to estimate OR and 95% CI. A total of 160 patients were included. The prevalence of significant fibrosis using elastography was 25% (n = 40), and 7.5% (n = 12) for advanced fibrosis. Patients with fibrosis had higher prevalence of obesity (60% vs 30.8%, P = 0.04), type 2 diabetes (40% vs 27.5%, P = 0.003), gamma-glutamyl transpeptidase levels (70.8±84.4 vs. 40.1±39.2, P = 0.002), and lower platelets (210.7±58.9 vs. 242.8±49.7, P = 0.0009). Multivariate analysis showed that body mass index (OR1.11, 95%CI 1.02-1.21), type 2 diabetes (OR 3.44, 95%CI 1.2-9.88), and gamma-glutamyl transpeptidase (OR 1.01, 95%CI1-1.02) were associated with the presence of fibrosis. The use of methotrexate was not associated. Patients with psoriasis are at higher risk of fibrosis. Metabolic dysfunction, rather than solely the use of hepatotoxic drugs, likely plays a major role; it may be beneficial to consider elastography regardless of the treatment used. Metabolic factors should be assessed, and lifestyle modification should be encouraged.

We consider a one-dimensional spin model with the long-range random Hamiltonian given by H [ σ ] = - 1 2 ∑ x ≠ y J x , y σ x σ y | x - y | α 0 + α x , y . The randomness is considered in both the pairwise interaction J x , y and in its decaying parameter with slowest value α 0 plus a non-negative random variable α x , y . We prove the loss of stability at α 0 = 1 / 2 . We also prove the existence of the free energy at the thermodynamic limit when α 0 > 1 / 2 . Furthermore, we show uniqueness of the equilibrium state for α 0 > 3 / 2 in the strong sense.

Beneficial soil microorganisms, particularly plant probiotic bacteria (PPB), play a pivotal role in promoting plant growth, development, and overall health through root colonization. PPB-based biofertilizers offer a sustainable and eco-friendly alternative to conventional agricultural inputs. This study evaluates the plant probiotic potential of three native bacterial strains Rhizobium sp. ACO-34A, Sinorhizobium mexicanum ITTG R7T, and Sinorhizobium chiapasense ITTG S70T to enhance the growth, quality, and sugar content of Agave tequilana. A comprehensive genomic and functional analysis was conducted for each strain to assess their plant probiotic traits. Additionally, a greenhouse inoculation assay was performed on six-month-old agave seedlings at the “piña” stage to evaluate the effects of these strains on plant growth and sugar content. Comparative genomic analysis revealed that these rhizobial strains harbor genes associated with key plant probiotic traits, reinforcing their role in enhancing plant development. The results demonstrated significant effects (p < 0.05) on growth and sugar content in inoculated plants. ACO-34A increased plant height by 35.4%, fresh weight by 41.5%, and inulin content by 57.3%, while ITTG-R7T showed improvements of 26.4%, 35.2%, and 38.2%, respectively, compared to the control, and ITTG S70T also exhibited enhancements, although to a lesser extent, with increases of 23.5% in plant height, 28.9% in fresh weight, and 31.2% in inulin content. These findings highlight the biofertilizer potential of these native rhizobial strains, particularly Rhizobium sp. ACO-34A, positioning them as promising candidates for the sustainable cultivation of A. tequilana.