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Reciprocal inhibition and coactivation are strategies of the central nervous system used to perform various daily tasks. In automatic postural responses (APR), coactivation is widely investigated in the ankle joint muscles, however reciprocal inhibition, although clear in manipulative motor actions, has not been investigated in the context of APRs. The aim was to identify whether reciprocal inhibition can be observed as a strategy in the recruitment of gastrocnemius Medialis (GM), Soleus (So) and Tibialis Anterior (TA) muscles in low- and high-velocity forward and backward perturbations. We applied two balance perturbations with a low and a high velocity of displacement of the movable platform in forward and backward conditions and we evaluated the magnitude and latency time of TA, GM and So activation latency, measured by electromyography (EMG). In forward perturbations, coactivation of the three muscles was observed, with greater activation amplitude of the GM and lesser amplitude of the So and TA muscles. For backward, the pattern of response observed was activation of the TA muscle, a decrease in the EMG signal, which characterizes reciprocal inhibition of the GM muscle and maintenance of the basal state of the So muscle. This result indicates that backward perturbations are more challenging.

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We study the impact of the Rashba spin-orbit coupling (RSOC) on the stability of charge-density wave (CDW) in systems with large electron-phonon coupling (EPC). Here, the EPC is considered in the framework of the Holstein model at the half-filled square lattice. We obtain the phase diagram of the Rashba-Holstein model using the Hartree-Fock mean-field theory, and identify the boundaries of the CDW and Rashba metal phases. We notice that the RSOC disfavors the CDW phase, driving the system to a correlated Rashba metal. Also, we employ a cluster perturbation theory (CPT) approach to investigate the phase diagram beyond the Hartree-Fock approximation. The quantum correlations captured by CPT indicate that the RSOC is even more detrimental to CDW than previously anticipated. That is, the Rashba metal region is observed to be expanded in comparison to the mean-field case. Additionally, we investigate pairing correlations, and the results further strengthen the identification of critical points.

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In this paper we study a generalized Klausmeier model replacing the integer derivative by a local fractional derivative. This derivative enables us to consider a wide range of systems with already well-known derivatives. We analyze the stability of this new model as well as the homotopic perturbation method. Finally, an inverse problem associated with a real data set is solved.

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Breast cancer is characterized as being a heterogeneous pathology with a broad phenotype variability. Breast cancer subtypes have been developed in order to capture some of this heterogeneity. Each of these breast cancer subtypes, in turns retains varied characteristic features impacting diagnostic, prognostic and therapeutics. Basal breast tumors, in particular have been challenging in these regards. Basal breast cancer is often more aggressive, of rapid evolution and no tailor-made targeted therapies are available yet to treat it. Arguably, epigenetic variability is behind some of these intricacies. It is possible to further classify basal breast tumor in groups based on their non-coding transcriptome and methylome profiles. It is expected that these groups will have differences in survival as well as in sensitivity to certain classes of drugs. With this in mind, we implemented a computational learning approach to infer different subpopulations of basal breast cancer (from TCGA multi-omic data) based on their epigenetic signatures. Such epigenomic signatures were associated with different survival profiles; we then identified their associated gene co-expression network structure, extracted a signature based on modules within these networks, and use these signatures to find and prioritize drugs (in the LINCS dataset) that may be used to target these types of cancer. In this way we are introducing the analytical workflow for an epigenomic signature-based drug repurposing structure.

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Kallikrein 6 (KLK6) is an attractive drug target for the treatment of neurological diseases and for various cancers. Herein, we explore the accuracy and efficiency of different computational methods and protocols to predict the free energy of binding (ΔGbind) for a series of 49 inhibitors of KLK6. We found that the performance of the methods varied strongly with the tested system. For only one of the three KLK6 datasets, the docking scores obtained with rDock were in good agreement (R2 ≥ 0.5) with experimental values of ΔGbind. A similar result was obtained with MM/GBSA (using the ff14SB force field) calculations based on single minimized structures. Improved binding affinity predictions were obtained with the free energy perturbation (FEP) method, with an overall MUE and RMSE of 0.53 and 0.68 kcal/mol, respectively. Furthermore, in a simulation of a real-world drug discovery project, FEP was able to rank the most potent compounds at the top of the list. These results indicate that FEP can be a promising tool for the structure-based optimization of KLK6 inhibitors.

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In this study, we aimed to investigate the influence of executive functions (EF) on motor adaptation. We compared the motor performance of adults with and without EF deficits. Those with EF deficits (n = 21) were individuals with attention deficit hyperactivity disorder (ADHD) under medical treatment, and those without EF deficits (n = 21) comprised a control group (CG) of participants who were also without neurological or psychiatric diagnoses. Both groups performed a complex coincident timing motor task and various computerized neuropsychological tests for assessing EF. To investigate motor adaptation, the motor task provided measures of absolute error (AE) and variable error (VE) to reflect, respectively, performance accuracy and consistency relative to the task goal. We used reaction time (RT) to measure planning time taken before starting the task. First, participants practiced until they reached a criterion of performance stabilization (prior to their exposure to motor perturbations). They were next exposed to fast and slow predictable and unpredictable perturbations. On all neuropsychological tasks, participants with ADHD scored more poorly than control participants (p < .05); participants with ADHD also performed worse than control participants on all motor measures, particularly under unpredictable perturbations (p < .05). Under slow perturbations, EF deficits, particularly attentional impulsivity, negatively affected motor adaptation while cognitive flexibility was related to performance improvement. Under fast perturbations, both impulsivity and fast reaction time were related to improvement in motor adaptation under both predictable and unpredictable perturbations. We discuss the research and practical implications of these findings.

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The neurocomputational model 'Directions into Velocities of Articulators' (DIVA) was developed to account for various aspects of normal and disordered speech production and acquisition. The neural substrates of DIVA were established through functional magnetic resonance imaging (fMRI), providing physiological validation of the model. This study introduces DIVA_EEG an extension of DIVA that utilizes electroencephalography (EEG) to leverage the high temporal resolution and broad availability of EEG over fMRI. For the development of DIVA_EEG, EEG-like signals were derived from original equations describing the activity of the different DIVA maps. Synthetic EEG associated with the utterance of syllables was generated when both unperturbed and perturbed auditory feedback (first formant perturbations) were simulated. The cortical activation maps derived from synthetic EEG closely resembled those of the original DIVA model. To validate DIVA_EEG, the EEG of individuals with typical voices (N = 30) was acquired during an altered auditory feedback paradigm. The resulting empirical brain activity maps significantly overlapped with those predicted by DIVA_EEG. In conjunction with other recent model extensions, DIVA_EEG lays the foundations for constructing a complete neurocomputational framework to tackle vocal and speech disorders, which can guide model-driven personalized interventions.

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Abstract Malaria, a disease of public health concern is a known cause of kidney failure, and dependence on herbal medicines for its treatment is increasing due to the high cost of drugs. So this study is designed to evaluate the ameliorating effect of ethanol extract from Salacia nitida root bark on electrolyte and renal perturbations in Plasmodium berghei-infected mice. Thirty malariainfected mice divided into five groups of six mice each and another group of six uninfected mice were used for the study. 280, 430, and 580 mg/kg of extract were given to infected mice in groups B, C, and D, 4 mg/kg of artesunate given to group E mice, and 4 ml/kg of physiological saline given to group A and uninfected group F mice for five days. Serum Na+, K+, HCO3, Cl-, TB, urea, creatinine, BUN concentrations, and BUN/creatinine ratio were determined using standard methods. Results showed significant increases (p < 0.05) in Na+, K+, and HCO3 and decreases in Cl-, TB, urea, creatinine, BUN, and BUN/creatinine ratio in the infected treated mice in groups B - E. This study showed that ethanol extract of S. nitida root bark is efficient in the treatment of renal disorders and blood electrolyte perturbations

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Vibrio cholerae causes cholera and can switch between planktonic and biofilm lifeforms, where biofilm formation enhances transmission, virulence, and antibiotic resistance. Due to antibiotic microbial resistance, new antimicrobials including silver nanoparticles (AgNPs) are being studied. Nevertheless, little is known about the metabolic changes exerted by AgNPs on both microbial lifeforms. Our objective was to evaluate the changes in the metabolomic profile of V. cholerae planktonic and biofilm cells in response to sublethal concentrations of AgNPs using MS2 untargeted metabolomics and chemoinformatics. A total of 690 metabolites were quantified among all groups. More metabolites were significantly modulated in planktonic cells (n = 71) compared to biofilm (n = 37) by the treatment. The chemical class profiles were distinct for both planktonic and biofilm, suggesting a phenotype-dependent metabolic response to the nanoparticles. Chemical enrichment analysis showed altered abundances of oxidized fatty acids (FA), saturated FA, phosphatidic acids, and saturated stearic acid in planktonic cells treated with AgNPs, which hints at a turnover of the membrane. In contrast, no chemical classes were enriched in the biofilm. In conclusion, this study suggests that the response of V. cholerae to silver nanoparticles is phenotype-dependent and that planktonic cells experience a lipid remodeling process, possibly related to an adaptive mechanism involving the cell membrane.

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As land use intensifies in tropical forests, it is expected that species assemblages will be modified and that key functions of these ecosystems will be affected. The latter scenario is important from a public health perspective, because the land use change has been linked the outbreaks of vector-borne diseases. In this study, we evaluated the response of Phlebotominae (Diptera: Psychodidae) assemblages and their pattern of co-occurrence in four sites with different land use in an emerging cutaneous leishmaniasis focus in Yucatan, Mexico. Our hypothesis is that the conservation status (as forest cover) will positively influence the structure and composition of sand flies' assemblages. Using three different traps over a period of five months, a sampling effort of 1, 440 night-traps was performed. A total of 7, 897 sand fly specimens belonging to six genera and 10 species were collected. Our hypothesis was partially achieved since sand fly diversity increased as forest cover increased and vice versa, however random patterns of co-occurrence in assemblages were detected among sites. Even though the high abundance of sand flies in the forest fragment suggests an amplification effect, our results show that different vector species directly dominate in each site. We discuss the potential implications of the nestedness of species dominance. We suggest that in this emerging focus and under the land use gradient, Lutzomyia cruciata and Psathyromyia cratifer could play a pivotal role in maintaining the transmission cycles of Leishmania. The apparent generalist or colonialist profile of Lu. cruciata in disturbed areas deserves attention, due to the potential risk of leishmaniasis "domiciliation". This information is essential to understand the eco-epidemiology of leishmaniasis and the factors associated with its emergence in Yucatan, Mexico.

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People with HIV (PWH) are at increased risk of developing active tuberculosis (TB), and anemia is a common complication in both conditions. Anemia in TB patients has been linked to immune activation, levels of inflammatory biomarkers in blood, and risk for HIV disease progression and death. In this study we show that anemia was associated with a more pronounced inflammatory profile in HIV-TB coinfected persons in a cohort of 159 individuals with advanced HIV disease (CD4 count < 100 cells/µL) recruited as part of a randomized clinical trial (NCT00988780). A panel of plasma biomarkers was assessed on plasma obtained prior to combination antiretroviral therapy (cART) initiation. We performed a series of multidimensional analyses including clinical variables and concentrations of inflammatory biomarkers to profile systemic inflammation of PWH with and without anemia. We observed that TB participants presented with moderately lower levels of hemoglobin than non-TB participants. These participants also presented a higher Degree of Inflammatory Perturbation (DIP) score, related to increased levels of IFN-γ and TNF. The DIP was associated with TB coinfection and anemia before cART initiation. Future mechanistic studies are warranted to assess the determinants of such associations and the implications on treatment outcomes.

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Pozas Rojas is a hydrological system comprising nine isolated shallow ponds and a deep lagoon, which were temporally merged in 2010 by increased rainfall due to a tropical cyclone. In this work, we assess which components, biotic interactions, or environment filtering effects, drive the assembly of microbial communities after a natural perturbation. Arsenic, pH, and temperature are among the most significant environmental variables between each pond, clustering the samples in two main groups, whereas microbial composition is diverse and unique to each site, with no core at the operational taxonomic unit level and only 150 core genera when studied at the genus level. Los Hundidos lagoon has the most differentiated community, which is highly similar to the epipelagic Mediterranean Sea communities. On the other hand, the shallow ponds at the Pozas Rojas system resemble more to epicontinental hydrological systems, such as some cold rivers of the world and the phreatic mantle from Iowa. Overall, despite being a sole of water body 2 years prior to the sampling, interspecific interactions, rather than environmental selection, seem to play a more important role in Pozas Rojas, bolstered by founder effects on each poza and subsequent isolation of each water body.

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In this paper, we propose a new privatization mechanism based on a naive theory of a perturbation on a probability using wavelets, such as a noise perturbs the signal of a digital image sensor. Wavelets are employed to extract information from a wide range of types of data, including audio signals and images often related to sensors, as unstructured data. Specifically, the cumulative wavelet integral function is defined to build the perturbation on a probability with the help of this function. We show that an arbitrary distribution function additively perturbed is still a distribution function, which can be seen as a privatized distribution, with the privatization mechanism being a wavelet function. Thus, we offer a mathematical method for choosing a suitable probability distribution for data by starting from some guessed initial distribution. Examples of the proposed method are discussed. Computational experiments were carried out using a database-sensor and two related algorithms. Several knowledge areas can benefit from the new approach proposed in this investigation. The areas of artificial intelligence, machine learning, and deep learning constantly need techniques for data fitting, whose areas are closely related to sensors. Therefore, we believe that the proposed privatization mechanism is an important contribution to increasing the spectrum of existing techniques.

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Tropical vines and lianas have evolved mechanisms to avoid mechanical damage during their climbing life histories. We explore the mechanical properties and stem development of a tropical climber that develops trellises in tropical rain forest canopies. We measured the young stems of Condylocarpon guianensis (Apocynaceae) that construct complex trellises via self-supporting shoots, attached stems, and unattached pendulous stems. The results suggest that, in this species, there is a size (stem diameter) and developmental threshold at which plant shoots will make the developmental transition from stiff young shoots to later flexible stem properties. Shoots that do not find a support remain stiff, becoming pendulous and retaining numerous leaves. The formation of a second TYPE II (lianoid) wood is triggered by attachment, guaranteeing increased flexibility of light-structured shoots that transition from self-supporting searchers to inter-connected net-like trellis components. The results suggest that this species shows a "hard-wired" development that limits self-supporting growth among the slender stems that make up a liana trellis. The strategy is linked to a stem-twining climbing mode and promotes a rapid transition to flexible trellis elements in cluttered densely branched tropical forest habitats. These are situations that are prone to mechanical perturbation via wind action, tree falls, and branch movements. The findings suggest that some twining lianas are mechanically fine-tuned to produce trellises in specific habitats. Trellis building is carried out by young shoots that can perform very different functions via subtle development changes to ensure a safe space occupation of the liana canopy.

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Low back pain (LBP) is a painful manifestation in the lower part of the spine which causes disabilities changing the sensitivity of sensory neurons resulting in weakness of postural muscles interfering with the balance. It is not already clear if LBP people's muscle changes affect the centre of pressure (CoP) recovery in challenging stance perturbations. The aim of this study was to identify differences in the muscle reactions of people with and without LBP to control CoP in challenging stance perturbations. We applied low (Vel1) and high (Vel2) magnitude stance perturbation by a movable platform and evaluated (a) the magnitude and latency time of trunk and lower limb muscle activation, (b) and the displacement and the latency time of the first CoP peak. The latency of trunk and hip muscle activation on Vel2 was lower for LBP group. The CoP latency and displacement did not change between groups and velocities indicating that the muscles took the same time to overcome the external forces. In conclusion, the maintenance of CoP latency at both velocities was not affected on Vel2, suggesting that such alterations have protective action and preservation of the pain on the LPB group in challenging stance perturbations.

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Resumen Introducción: Los manglares están en declive en el mundo, conocer su estructura y regeneración en diferentes niveles de alteración puede ayudar a comprender la dinámica poblacional ante situaciones de estrés. Objetivo: La meta principal del estudio fue analizar la estructura comunitaria y estimar la trayectoria de las poblaciones de Avicenia germinans en diferentes sitios de manglar que presentan tres niveles de alteración. Métodos: Ocho transectos de aproximadamente 500 m de largo y colocados de manera perpendicular a la laguna de Tampamachoco, Veracruz, interceptaron tres niveles de alteración en los sitios estudiados del bosque de manglar. En cada transecto, cuadrantes de 10 x 10 m, 5 x 5 m, y 1 x 1 m sirvieron para contar todos los árboles de mangle por especie y estadio de madurez en 2017 y 2018. Resultados: La especie más abundante fue: A. germinans seguida de Rhizophora mangle y Laguncularia racemosa. Con base en su abundancia, se encontraron diferencias significativas según los tres grados de alteración (AM R = 0.6, P < 0.001), ilustrado en un análisis de ordenación no métrico (nMDS). Una tabla de vida para A. germinans permitió un análisis poblacional que mostró una tasa intrínseca de incremento poblacional (r) negativa para los sitios que presentan alteración (-0.0027 u -0.0774) y positiva (0.0289) en el sitio sin alteración aparente. La supervivencia del estadio de plántula a juvenil varia de 50 % en el sitio no alterados a 5 y 4 % en los otros dos sitios. Conclusiones: Se necesitan medidas para incrementar la sobrevivencia de las plántulas y revertir la disminución de las trayectorias en los sitios con alteración, de otra forma el manglar tendrá una viabilidad reducida en el término medio.

Abstract Introduction: Globally, mangroves are declining; characterizing their structure and regeneration at different disturbance levels can help understand their responses to stressful situations. Objective: The study's primary goal was to analyze the mangrove community structure and to estimate the populations' trajectories of Avicenia germinans at different mangrove sites that present three levels of disturbance. Methods: Eight transects of approximately 500 m in length and laid perpendicular to the Tamapamchoco lagoon, Veracruz, intersected three levels of disturbance currently present on the mangrove forest. On each transect, 10 x 10 m, 5 x 5 m, and 1 x 1 m quadrants served to account for all mangrove trees by species and stage of maturity in 2017 and 2018. Results: The most abundant species was: A. germinans followed by Rhizophora mangle and Laguncularia racemosa. Based on their abundance, we found significant differences for the three levels of disturbance (ANOSIM R = 0.6, P < 0.001) presented in a non-metric ordination (nMDS). A life table for A. germinans allowed a population analysis that showed an intrinsic rate of population increase (r) that was negative at the disturbed sites (-0.0027 and -0.0774) and positive (0.0289) at the apparently undisturbed site. Seedling to juvenile stage survival ranged from 50 % at the undisturbed site to 5 and 4 % at the disturbed sites. Conclusions: Measures to increase the survival of seedlings are necessary to reverse the decreasing population trajectories at the disturbed sites; otherwise, the mangrove will have reduced viability in the medium term.

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Lattice simulations of the QCD correlation functions in the Landau gauge have established two remarkable facts. First, the coupling constant in the gauge sector-defined, e.g., in the Taylor scheme-remains finite and moderate at all scales, suggesting that some kind of perturbative description should be valid down to infrared momenta. Second, the gluon propagator reaches a finite nonzero value at vanishing momentum, corresponding to a gluon screening mass. We review recent studies which aim at describing the long-distance properties of Landau gauge QCD by means of the perturbative Curci-Ferrari model. The latter is the simplest deformation of the Faddeev-Popov Lagrangian in the Landau gauge that includes a gluon screening mass at tree-level. There are, by now, strong evidences that this approach successfully describes many aspects of the infrared QCD dynamics. In particular, several correlation functions were computed at one- and two-loop orders and compared withab-initiolattice simulations. The typical error is of the order of ten percent for a one-loop calculation and drops to few percents at two loops. We review such calculations in the quenched approximation as well as in the presence of dynamical quarks. In the latter case, the spontaneous breaking of the chiral symmetry requires to go beyond a coupling expansion but can still be described in a controlled approximation scheme in terms of small parameters. We also review applications of the approach to nonzero temperature and chemical potential.

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In the absence of new therapeutic strategies, chemotherapeutic drugs are the most widely used strategy against metastatic breast cancer, in spite of eliciting multiple adverse effects and having low responses with an average 5-year patient survival rate. Among the new therapeutic targets that are currently in clinical trials, here, we addressed the association between the regulation of the metabolic process of autophagy and the exposure of damage-associated molecular patterns associated (DAMPs) to immunogenic cell death (ICD), which has not been previously studied. After validating an mCHR-GFP tandem LC3 sensor capacity to report dynamic changes of the autophagic metabolic flux in response to external stimuli and demonstrating that both basal autophagy levels and response to diverse autophagy regulators fluctuate among different cell lines, we explored the interaction between autophagy modulators and chemotherapeutic agents in regards of cytotoxicity and ICD using three different breast cancer cell lines. Since these interactions are very complex and variable throughout different cell lines, we designed a perturbation-based model in which we propose specific modes of action of chemotherapeutic agents on the autophagic flux and the corresponding strategies of modulation to enhance the response to chemotherapy. Our results point towards a promising therapeutic potential of the metabolic regulation of autophagy to overcome chemotherapy resistance by eliciting ICD.

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We present computer simulation and theoretical results for a system of N Quantum Hard Spheres (QHS) particles of diameter σ and mass m at temperature T, confined between parallel hard walls separated by a distance Hσ, within the range 1≤H≤∞. Semiclassical Monte Carlo computer simulations were performed adapted to a confined space, considering effects in terms of the density of particles ρ*=N/V, where V is the accessible volume, the inverse length H-1 and the de Broglie's thermal wavelength λB=h/2πmkT, where k and h are the Boltzmann's and Planck's constants, respectively. For the case of extreme and maximum confinement, 0.5

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Recently, different authors have reported Perturbation Theory (PT) methods combined with machine learning (ML) to obtain PTML (PT + ML) models. They have applied PTML models to the study of different biological systems. Here we present one state-of-art review about the different applications of PTML models in Organic Synthesis, Medicinal Chemistry, Protein Research, and Technology. The aim of the models is to find relations between the molecular descriptors and the biological characteristics to predict key properties of new compounds. An area where the ML has been very useful is the drug discovery process. The entire process of drug discovery leads to the generation of lots of data, and it is also a costly and time-consuming process. ML comes with the opportunity of analyzing significant amounts of chemical data obtaining outcomes to find potential drug candidates.

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