Systematic review of photobiomodulation for multiple sclerosis.

Background: Multiple sclerosis (MS) is an inflammatory chronic autoimmune and neurodegenerative disorder of the brain and spinal cord, resulting in loss of motor, sensorial, and cognitive function. Among the non-pharmacological interventions for several brain conditions, photobiomodulation (PBM) has gained attention in medical society for its neuroprotective effects. We systematically reviewed the effects of PBM on MS. Methods: We conducted a systematic search on the bibliographic databases (PubMed and ScienceDirect) with the keywords based on MeSH terms: PBM, low-level laser therapy, multiple sclerosis, autoimmune encephalomyelitis, demyelination, and progressive multiple sclerosis. Data search was limited from 2012 to July 2024. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The initial systematic search identified 126 articles. Of these, 68 articles were removed by duplicity and 50 by screening. Thus, 8 studies satisfied the inclusion criteria. Results: The reviewed studies showed that PBM modulates brain markers linked to inflammation, oxidative stress, and apoptosis. Improvements in motor, sensorial, and cognitive functions in MS patients were also observed after PBM therapy. No study reported adverse effects of PBM. Conclusion: These findings suggest the potential of PBM as a promising non-pharmacological intervention for the management of MS, although further research is needed to standardize PBM protocols and assess its long-term effects.

Predicting the pulse of the Amazon: Machine learning insights into deforestation dynamics.

This study aims to analyze deforestation in the Brazilian Amazon from 1999 to 2020 using machine learning techniques to assess 16 critical factors. Our approach leverages the capabilities of machine learning, particularly Random Forest, which proved to be the most accurate model in terms of determination coefficient, mean squared error, and mean absolute error. The analysis revealed that the harvested area of permanent crops is the most influential variable in predicting deforestation, followed by the area of temporary crops. Furthermore, our findings indicate a significant inverse relationship between public spending and deforestation rates. These results contribute to understanding deforestation dynamics and offer potential strategies for improving conservation efforts.

Stress symptoms occur in patients undergoing chemotherapy treatment independently of the level of physical activity.

The cancer patient is undergoing a set of procedures that affect the physical and psychological balance, which can generate stressful situations in the organism. In turn, physical activity helps to treat stress, promoting well-being and reducing anxiety. Our study aimed to verify the influence of physical activity practice on stress symptoms in patients undergoing oncological chemotherapy treatment. For this, we used Lipp's Inventory of Stress Symptoms (ISSL) and the International Physical Activity Questionnaire (IPAQ) in 56 patients with cancer. Our data show that 45.4% of the participants exhibited stress scores, of which, 21.8% were at near to exhaustion, and 23.6% at exhaustion. We observed that 30% of them are considered sufficiently active, 25% insufficiently active, 45% sedentary. No association was observed between physical activity and stress. These findings indicate that stress symptoms occur in patients undergoing chemotherapy treatment regardless of the level of physical activity.

Detection and quantification of Babesia bovis and Babesia bigemina using different target genes.

Molecular assays have been widely used for the detection and quantification of bovine babesiosis due to their high sensitivity and specificity. However, variations in the sensitivity of pathogen detection may occur depending on the selected target gene. Thus, this study aimed to compare the detection sensitivity (DS) of Babesia bovis and B. bigemina infection levels in artificially and naturally infected cattle using quantitative PCR (qPCR) and six target genes. For B. bovis, the merozoite surface antigen genes 2b and 2c (msa-2b and msa-2c), and the mitochondrial cytochrome b gene (cybmt) were used. For B. bigemina, the genes encoding the proteins associated with rhoptry 1c (rap-1c), rap-1a, and cybmt were used. Six bovines, free of babesiosis, were artificially infected with 1 × 10-8 red blood cells infected (iRBC) with B. bovis (n = 3) or 1 × 10-6B. bigemina iRBC (n = 3). The animals were evaluated daily until parasitemia was confirmed (≥ 2.0%). The quantity of iRBC present in each animal was determined by examining blood smears. Blood samples were then subjected to DNA extraction, serial dilution, and qPCR analysis to determine the DS of each target gene. In addition, 30 calves naturally infected by Babesia spp. were also evaluated using the same six target genes. Regarding the artificial infection, B. bovis cybmt showed 25-fold higher sensitivity than the msa-2b and msa-2c genes, while the B. bigemina cybmt exhibited 5-fold and 25-fold higher sensitivity than the rap-1a and rap-1c genes, respectively. The rap-1a gene was found to be 5 times more sensitive than the rap-1c gene, while the B. bovis msa-2b and msa-2c genes exhibited similar DS. The positive frequencies of naturally infected calves for the target cybmt, msa-2b, and msa-2c genes (B. bovis) were: 100%, 33.3% and 50%, while cybmt, rap-1a, and rap-1c genes (B. bigemina) were 90%, 83.3%, and 63.3%, respectively. This study may contribute to the selection of suitable genes for molecular monitoring of bovine babesiosis. Mitochondrial genes could be considered as an alternative to improve the sensitivity of B. bovis and B. bigemina detection using qPCR.

Software for animal randomization: A tool for increasing the reproducibility of science.

Poorly designed preclinical studies may compromise human health due to erroneous conclusions regarding treatment effects in addition to contributing to experimental irreproducibility and wasted resources. Randomization is one of the crucial steps to enhance scientific rigor and is a commonly recognized bias-reducing instrument that increases the reliability and reproduction of studies involving animals (even with syngeneic animals). This procedure should be considered when planning a study and reported during data publication. In this context, this work aimed to highlight the importance of adopting quality measures in preclinical trials, with an emphasis on animal randomization. The 'Mouse Randomization' app was developed to help researchers estimate an adequate sample size to obtain significant statistical power, ensuring the ethical use of animals. This app is freely available on the internet to carry out animal randomization and calculate sample sizes for in vivo experiments. We believe that this brief discussion about animal randomization could raise awareness among researchers on how to improve the quality of preclinical research, increasing reproducibility and avoiding animal misuse.

Genomic history of coastal societies from eastern South America.

Sambaqui (shellmound) societies are among the most intriguing archaeological phenomena in pre-colonial South America, extending from approximately 8,000 to 1,000 years before present (yr BP) across 3,000 km on the Atlantic coast. However, little is known about their connection to early Holocene hunter-gatherers, how this may have contributed to different historical pathways and the processes through which late Holocene ceramists came to rule the coast shortly before European contact. To contribute to our understanding of the population history of indigenous societies on the eastern coast of South America, we produced genome-wide data from 34 ancient individuals as early as 10,000 yr BP from four different regions in Brazil. Early Holocene hunter-gatherers were found to lack shared genetic drift among themselves and with later populations from eastern South America, suggesting that they derived from a common radiation and did not contribute substantially to later coastal groups. Our analyses show genetic heterogeneity among contemporaneous Sambaqui groups from the southeastern and southern Brazilian coast, contrary to the similarity expressed in the archaeological record. The complex history of intercultural contact between inland horticulturists and coastal populations becomes genetically evident during the final horizon of Sambaqui societies, from around 2,200 yr BP, corroborating evidence of cultural change.

A Graph-Space Optimal Transport Approach Based on Kaniadakis κ-Gaussian Distribution for Inverse Problems Related to Wave Propagation.

Data-centric inverse problems are a process of inferring physical attributes from indirect measurements. Full-waveform inversion (FWI) is a non-linear inverse problem that attempts to obtain a quantitative physical model by comparing the wave equation solution with observed data, optimizing an objective function. However, the FWI is strenuously dependent on a robust objective function, especially for dealing with cycle-skipping issues and non-Gaussian noises in the dataset. In this work, we present an objective function based on the Kaniadakis κ-Gaussian distribution and the optimal transport (OT) theory to mitigate non-Gaussian noise effects and phase ambiguity concerns that cause cycle skipping. We construct the κ-objective function using the probabilistic maximum likelihood procedure and include it within a well-posed version of the original OT formulation, known as the Kantorovich-Rubinstein metric. We represent the data in the graph space to satisfy the probability axioms required by the Kantorovich-Rubinstein framework. We call our proposal the κ-Graph-Space Optimal Transport FWI (κ-GSOT-FWI). The results suggest that the κ-GSOT-FWI is an effective procedure to circumvent the effects of non-Gaussian noise and cycle-skipping problems. They also show that the Kaniadakis κ-statistics significantly improve the FWI objective function convergence, resulting in higher-resolution models than classical techniques, especially when κ=0.6.

Determinants of the composition of ectoparasitic flies of bats (Diptera: Streblidae, Nycteribiidae) in the Amazon and Cerrado landscape scales and ecotonal areas.

The high diversity of bats in the Neotropics is primarily associated with various ectoparasite species on their bodies. Interactions between these animals need to be comprehensively investigated at landscape scales, focusing on understanding the patterns of diversity of species. We sought to evaluate, througt bat captures and ectoparasite sampling, the determinants of the composition of ectoparasitic flies species present in bats in in the Amazon and Cerrado biomes and ecotone areas. We used a generalized dissimilarity model (GDM) to verify what factors explained the composition of ectoparasitic flies of bats using landscape metrics, geographic distance, biome, and host composition. Twenty-four bat species haboured a total of 33 species of ectoparasitic flies. Host composition was the best predictor of fly composition, followed by the environmental variables and by biome. Geographical distance presented negligible effects. Studies on large scales tend to reveal a wide diversity of ectoparasitic flies. Host composition, as the best predictor of fly composition, may be associated with interspecific characteristics among species. We recommend studies focusing on the landscape to understand better the parasitic associations of bats and their distribution across environments.

Association of the Practice of Physical Activity and Dietary Pattern with Psychological Distress before and during COVID-19 in Brazilian Adults.

To verify the association between the practice of physical activity and dietary patterns and psychological distress before and during the lockdown due to COVID-19, a cross-sectional study was performed with 2000 Brazilians (mean [M] = 35.78 years; standard deviation [SD] = 11.20; 59.6% women) recruited through convenience sampling via digital media. Participants completed an electronic questionnaire containing sociodemographic and clinical information, nutritional patterns, physical activity, and psychological distress. Data were analyzed using descriptive statistics and multinomial regression. Before the COVID-19 lockdown, the chance of women presenting very high stress, in relation to men, was six times higher (OR = 6.32; 95% CI 4.20-9.51), a behavior that remained similar during the lockdown (OR = 6.63; 95% CI 4.40-10.00). Before the lockdown, insufficient physical activity doubled the chance of having very high stress in relation to those who engaged in physical activities six to seven times a week (OR = 2.11; 95% CI 1.10-4.02). However, during the lockdown, this probability was higher, from twice to 10 times the chance (OR = 10.19; 95% CI 4.85-21.41). Not exercising alone (OR = 2.18; 95% CI 1.52-3.11) and a decreasing physical activity frequency (OR = 2.28; 95% CI 1.40-3.71) were also associated with very high stress during the lockdown. Additionally, the consumption of smaller amounts of food showed an inverse association with very high stress (OR = 0.28; 95% CI 0.18-0.43). The maintenance of physical activity and an adequate eating frequency are measures that should be considered to cope with higher levels of anxiety and depression.

Generalized statistics: Applications to data inverse problems with outlier-resistance.

The conventional approach to data-driven inversion framework is based on Gaussian statistics that presents serious difficulties, especially in the presence of outliers in the measurements. In this work, we present maximum likelihood estimators associated with generalized Gaussian distributions in the context of Rényi, Tsallis and Kaniadakis statistics. In this regard, we analytically analyze the outlier-resistance of each proposal through the so-called influence function. In this way, we formulate inverse problems by constructing objective functions linked to the maximum likelihood estimators. To demonstrate the robustness of the generalized methodologies, we consider an important geophysical inverse problem with high noisy data with spikes. The results reveal that the best data inversion performance occurs when the entropic index from each generalized statistic is associated with objective functions proportional to the inverse of the error amplitude. We argue that in such a limit the three approaches are resistant to outliers and are also equivalent, which suggests a lower computational cost for the inversion process due to the reduction of numerical simulations to be performed and the fast convergence of the optimization process.

The effect of loss aversion and entitlement on cheating: An online experiment.

We investigate how loss aversion and entitlement influence lying. We conduct an online experiment with a cheating task in which participants draw and report a number. Participants can cheat by reporting a different number to earn a higher payoff. We vary whether participants perform (or not) a real effort task to generate their endowment before the cheating task to evoke a sense of entitlement, and whether participants can cheat for an additional gain or to avoid a loss using a 2 (earned/not earned endowment) × 2 (loss/gain) design. We find no effect of loss aversion on cheating and only weak evidence of a prior stage of real effort on lying behavior. Furthermore, we find a correlation between real effort task performance and lying, but only in the gain domain. This is the first study to look at how entitlement affects cheating behavior in both the gain and loss domains.

Full-waveform inversion based on generalized Rényi entropy using patched Green's function techniques.

The estimation of physical parameters from data analyses is a crucial process for the description and modeling of many complex systems. Based on Rényi α-Gaussian distribution and patched Green's function (PGF) techniques, we propose a robust framework for data inversion using a wave-equation based methodology named full-waveform inversion (FWI). From the assumption that the residual seismic data (the difference between the modeled and observed data) obeys the Rényi α-Gaussian probability distribution, we introduce an outlier-resistant criterion to deal with erratic measures in the FWI context, in which the classical FWI based on l2-norm is a particular case. The new misfit function arises from the probabilistic maximum-likelihood method associated with the α-Gaussian distribution. The PGF technique works on the forward modeling process by dividing the computational domain into outside target area and target area, where the wave equation is solved only once on the outside target (before FWI). During the FWI processing, Green's functions related only to the target area are computed instead of the entire computational domain, saving computational efforts. We show the effectiveness of our proposed approach by considering two distinct realistic P-wave velocity models, in which the first one is inspired in the Kwanza Basin in Angola and the second in a region of great economic interest in the Brazilian pre-salt field. We call our proposal by the abbreviation α-PGF-FWI. The results reveal that the α-PGF-FWI is robust against additive Gaussian noise and non-Gaussian noise with outliers in the limit α → 2/3, being α the Rényi entropic index.

Photobiomodulation for the treatment of neuroinflammation: A systematic review of controlled laboratory animal studies.

Background: Neuroinflammation is a response that involves different cell lineages of the central nervous system, such as neurons and glial cells. Among the non-pharmacological interventions for neuroinflammation, photobiomodulation (PBM) is gaining prominence because of its beneficial effects found in experimental brain research. We systematically reviewed the effects of PBM on laboratory animal models, specially to investigate potential benefits of PBM as an efficient anti-inflammatory therapy. Methods: We conducted a systematic search on the bibliographic databases (PubMed and ScienceDirect) with the keywords based on MeSH terms: photobiomodulation, low-level laser therapy, brain, neuroinflammation, inflammation, cytokine, and microglia. Data search was limited from 2009 to June 2022. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. The initial systematic search identified 140 articles. Among them, 54 articles were removed for duplication and 59 articles by screening. Therefore, 27 studies met the inclusion criteria. Results: The studies showed that PBM has anti-inflammatory properties in several conditions, such as traumatic brain injury, edema formation and hyperalgesia, ischemia, neurodegenerative conditions, aging, epilepsy, depression, and spinal cord injury. Conclusion: Taken together, these results indicate that transcranial PBM therapy is a promising strategy to treat brain pathological conditions induced by neuroinflammation.

κ-statistics approach to optimal transport waveform inversion.

Extracting physical parameters that cannot be directly measured from an observed data set remains a great challenge in several fields of science and physics. In many of these problems, the construction of a physical model from waveforms is hampered by the phase ambiguity of the recorded wave fronts. In this work, we present an approach for mitigating the effect of phase ambiguity in waveform-driven issues. Our proposal combines the optimal transport theory with the κ-statistical thermodynamics approach. We construct an energy function from the most probable state of a system described by a finite-variance κ-Gaussian distribution to introduce an optimal transport metric. We demonstrate that our proposal outperforms the classical frameworks by considering a nonlinear geophysical data-driven problem based on a wave equation numerical solution. The κ-generalized optimal transport metric is easily adapted to various inverse problems, from estimating power-law exponents to machine learning approaches in quantum mechanics.

Effect of the ACTN-3 gene polymorphism on functional fitness and executive function of elderly.

During aging, physical integrity and cognitive abilities, especially executive function, become compromised, directly influencing the quality of life of the elderly. One good strategy to ensure healthy aging is the practice of physical exercise. Activities to improve aerobic capacity and muscle strength are extremely important in old age. However, some genetic factors can interfere both positively and negatively with these gains. In this context, the polymorphism rs1815739 (R577X) of the α-actinin 3 gene (ACTN-3) is commonly studied and related to muscle phenotype. Thus, the present study aimed to investigate the effect of the ACTN-3 gene polymorphism on the functional fitness (measured by the Senior Fit test) and cognitive capacity (evaluated by the Stroop test) of the elderly (n = 347), both men and women. We did not find the effect of genotype on functional fitness, but we did observed a positive effect of the ACTN-3 gene polymorphism on executive function. The presence of the X allele of the ACTN3 gene in the elderly was related to a better performance in the Stroop test (shorter answer time). Our results showed that ACTN-3 gene polymorphism affects the executive function of the elderly but not their functional fitness.

Microseismic event detection in noisy environments with instantaneous spectral Shannon entropy.

The detection of information-bearing signals in a time series is very important for describing and analyzing a wide variety of complex physical systems. However, identifying events in low signal-to-noise ratio circumstances remains a challenge once heavy data preprocessing is usually required. In this work, we propose a robust methodology based on the instantaneous-spectral Shannon entropy for capturing microseismic events in noisy environments without the requirement of data preprocessing. We call our proposal the instantaneous spectral entropy detection (ISED) method. We tested the ISED in a couple of real empirical seismic records to detect microseismic events. Our methodology detects microseismic patterns even without any preprocessing, in contrast to usual methods in the literature which need appreciable data preprocessing.

Transcranial photobiomodulation changes neuronal morphology in the cerebral cortex of rats.

Transcranial photobiomodulation improves cerebral cortex metabolism. We hypothesized that chronic laser treatment may stimulate neuronal growth. To test this hypothesis, we investigated the morphology of neurons in the cerebral cortex of rats submitted to brief (2.5 min) daily sham or transcranial laser treatment (810 nm wavelength at 100 mW) for 58 consecutive days. Laser treatment increased the number of dendritic nodes and ends, and reduced the total dendritic length in neurons of the cerebral cortex. Taken together, our data indicate that chronic transcranial photobiomodulation induces morphological neuroplasticity in the cerebral cortex of rats.

Morphometric affinities and direct radiocarbon dating of the Toca dos Coqueiros' skull (Serra da Capivara, Brazil).

The biological variation of the earliest skeletons of South America has been intensely debated for the last two centuries. One of the major research constraints has been the limited number of available samples dating to the early Holocene. We here present the first direct radiocarbon-date for the early Holocene human skeleton from Toca dos Coqueiros (Serra da Capivara, Brazil), also known as "Zuzu" (8640 ± 30 BP; 9526-9681 cal years BP). We performed craniometric analyses using exclusively samples from Brazil, to revisit the sex of the skeleton, and to discuss the evolutionary processes involved in the occupation of the continent. The sex of the individual was estimated as a female when compared to late and early Holocene individuals, but as a male when compared only to the early Holocene series. We also found that Zuzu presents the strongest differences with the late Holocene Guajajara individuals, located nearby, and the strongest similarities with the early Holocene series from Lagoa Santa, attesting for solid biological affinities among early Holocene individuals from Brazil, as well as a moderate level of morphological variation among them. This suggests that the early individuals were part of the same heterogeneous lineage, possibly a different one from which late Holocene populations diverged.