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In complex systems, the system's self-regulation processes can transition between states of equilibrium and disequilibrium, leading to changes in the distribution of players within the playing space. Actions that are surprising, rare, or out of the ordinary tend to be valued for their potential to destabilize the opposing defensive structure, altering player dispersion, and creating fragile spaces for the attack. With advancements in understanding the influence of the environment on players' affordances, the tactical consequences from individuals' solutions to various scenarios and their impact on the game context becomes a rich area for investigation. This study compared defensive dispersion in the moments preceding and following original actions in small-sided games. The original actions were obtained using the Creative Behavior Assessment in Team Sports (CBATS) observational matrix. At the same time, defensive dispersion was derived from positional data collected via GPS and processed using dedicated routines in MATLAB to obtain variables such as Stretch Index, Surface Area, Team Width, Team Length, and Individual Player Area. The Kolmogorov-Smirnov test was employed for normality, and the General Linear Model with Repeated Measures was used to compare pre-and post-action moments across different action classifications (pass and shot) and game configurations (SSG 4v4 - Small , SSG 4v4 - Large , SSG 5v5 - Small , and SSG 5v5 - Large ). Differences were found in the Stretch Index, Surface Area, and Team Width variables in SSG 4v4 - Small and Surface Area in SSG 5v5 - Small (p < 0.05). It was concluded that the original action could attract opponents in small formats of SSG, increasing the contraction of the opposing team and reducing space around the action, with the potential to create new spaces in other areas of the field., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

This review article summarizes the experimental findings in rodents published between 2014 and 2024 concerning phthalates exposure and reproductive outcomes. Rodents were chosen for this review since most studies that have developmental aspects in different phases of exposure and that address more in-depth reproductive mechanisms have been carried out in mice and rats. The evidence of adverse effects of phthalates on fetal development and human and animal reproduction is extensive, with impacts ranging from gene expression to physiological alterations. Despite the large volume of scientific papers pointing out the harmful effects of exposure to phthalates, isolated or in mixtures, at different developmental periods, most of them are associated with the maternal exposure and long-term effects in the offspring. Regular vegetables, fruits, fish, dairy products, and whole grains intake rich in bioactive compounds can mitigate the adverse effects of EDCs in humans and animals at different developmental periods. Various food bioactive compounds (FBCs) such as genistein, resveratrol, lycopene, vitamin E, curcumin, selenium, and plant secondary metabolites (PSMs) present antioxidant, anti-inflammatory, anti-tumor, and other biological properties with the potential to reduce of deleterious effects of phthalates on the reproductive tract. In this review, we aimed to summarize the main studies produced in the last decade about phthalate exposure and reproductive disorders in males and females (at different developmental critical windows). Additionally, we proposed some FBCs and PSMs that could attenuate the main adverse effects caused by phthalate exposure on male reproduction since there is a lack of studies with females.

A previous study using miRNA sequencing revealed that exposure to a mixture of phthalates during pregnancy and lactation dysregulated rno-miR-184 and rno-miR-141-3p in the ventral prostate (VP) of offspring. Here, rno-miR-184 and rno-miR-141-3 expressions were obtained by RT-qPCR in the VP of F1 males as well as in F2 offspring, aiming to establish a relationship with possible oncogenic targets through in silico analyses with multigenerational approach. Additionally, some targets were measured by western blots to highlight a possible relationship between the deregulated miRNAs and some of their targets. VP samples from rats exposed to a mixture of phthalates maternally during pregnancy and lactation (GD10 to PND21-F1) and VP from offspring (F2) were examined. The phthalate mixture at both concentrations (20 μg and 200 mg/kg/day) increased the expression of both miRNAs in the F1 (PND22 and 120) and F2 (descendants of F1-treated males) prostate. Target prediction analysis revealed that both microRNAs are responsible for modulating the expression and synthesis of 40 common targets. A phthalate target association analysis and the HPA database showed an interesting relationship among these possible miRNAs modulated targets with prostate adenocarcinoma and other oncogenic processes. Western blots showed alteration in P63, P53, WNT5, and STAT3 expression, which are targeted by the miRNAs, in the VP of F1/F2 males. The data draw attention to the epigenetic modulation in the prostate of descendants exposed to phthalates and adds to one of the few currently found in the literature to point to microRNAs signature as biomarkers of exposure to plasticizers., (© 2024 Wiley Periodicals LLC.)

Western diet (WD), abundant in saturated fats and simple carbohydrates, has been associated with the development of prostate diseases. In addition, 2,4-dichlorophenoxyacetic acid (2,4-D), an herbicide used in agricultural and non-agricultural settings, may interfere with the endocrine system impacting reproductive health. The association of both factors is something common in everyday life, however, there are no relevant studies associating them as possible modulators of prostatic diseases. This study evaluated the action of the herbicide 2,4-D on the postnatal development of the prostate in mice fed with WD. Male C57Bl/6J mice received simultaneously a WD and 2,4-D at doses of 0.02, 2.0, or 20.0 mg/kg b.w./day for 6 months. The prolongated WD intake induced obesity and glucose intolerance, increasing body weight and fat. WD induced morphological changes and increased PCNA-positive epithelial cells in prostate. Additionally, the WD increased gene expression of AR, antioxidant targets, inflammation-related cytokines, cell repair and turnover, and targets related to methylation and miRNAs biosynthesis compared to the counterpart (basal diet). 2,4-D (0.02 and 2.0) changed prostate morphology and gene expression evoked by WD. In contrast, the WD group exposed to 20 mg/kg of 2,4-D reduced feed intake and body weight, and increased expression of androgen receptor and genes related to cell repair and DNA methylation compared to the negative control. Our results showed that 2,4-D was able to modulate the effects caused by WD, mainly at lower doses. However, further studies are needed to elucidate the mechanisms of 2,4-D on the obesogenic environment caused by the WD., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background and Purpose: Clinical outcome information on patients with neuromuscular diseases (NMDs) who have been infected with SARS-CoV-2 is limited. The aim of this study was to determine factors associated with the severity of COVID-19 outcomes in people with NMDs., Methods: Cases of NMD, of any age, and confirmed/presumptive COVID-19, submitted to the International Neuromuscular COVID-19 Registry up to 31 December 2021, were included. A mutually exclusive ordinal COVID-19 severity scale was defined as follows: (1) no hospitalization; (2) hospitalization without oxygenation; (3) hospitalization with ventilation/oxygenation; and (4) death. Multivariable ordinal logistic regression analyses were used to estimate odds ratios (ORs) for severe outcome, adjusting for age, sex, race/ethnicity, NMD, comorbidities, baseline functional status (modified Rankin scale [mRS]), use of immunosuppressive/immunomodulatory medication, and pandemic calendar period., Results: Of 315 patients from 13 countries (mean age 50.3 [±17.7] years, 154 [48.9%] female), 175 (55.5%) were not hospitalized, 27 (8.6%) were hospitalized without supplemental oxygen, 91 (28.9%) were hospitalized with ventilation/supplemental oxygen, and 22 (7%) died. Higher odds of severe COVID-19 outcomes were observed for: age ≥50 years (50-64 years: OR 2.4, 95% confidence interval [CI] 1.33-4.31; >64 years: OR 4.16, 95% CI 2.12-8.15; both vs. <50 years); non-White race/ethnicity (OR 1.81, 95% CI 1.07-3.06; vs. White); mRS moderately severe/severe disability (OR 3.02, 95% CI 1.6-5.69; vs. no/slight/moderate disability); history of respiratory dysfunction (OR 3.16, 95% CI 1.79-5.58); obesity (OR 2.24, 95% CI 1.18-4.25); ≥3 comorbidities (OR 3.2, 95% CI 1.76-5.83; vs. ≤2; if comorbidity count used instead of specific comorbidities); glucocorticoid treatment (OR 2.33, 95% CI 1.14-4.78); and Guillain-Barré syndrome (OR 3.1, 95% CI 1.35-7.13; vs. mitochondrial disease)., Conclusions: Among people with NMDs, there is a differential risk of COVID-19 outcomes according to demographic and clinical characteristics. These findings could be used to develop tailored management strategies and evidence-based recommendations for NMD patients., (© 2022 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Evolving fuzzy neural networks are models capable of solving complex problems in a wide variety of contexts. In general, the quality of the data evaluated by a model has a direct impact on the quality of the results. Some procedures can generate uncertainty during data collection, which can be identified by experts to choose more suitable forms of model training. This paper proposes the integration of expert input on labeling uncertainty into evolving fuzzy neural classifiers (EFNC) in an approach called EFNC-U . Uncertainty is considered in class label input provided by experts, who may not be entirely confident in their labeling or who may have limited experience with the application scenario for which the data is processed. Further, we aimed to create highly interpretable fuzzy classification rules to gain a better understanding of the process and thus to enable the user to elicit new knowledge from the model. To prove our technique, we performed binary pattern classification tests within two application scenarios, cyber invasion and fraud detection in auctions. By explicitly considering class label uncertainty in the update process of the EFNC-U, improved accuracy trend lines were achieved compared to fully (and blindly) updating the classifiers with uncertain data. Integration of (simulated) labeling uncertainty smaller than 20% led to similar accuracy trends as using the original streams (unaffected by uncertainty). This demonstrates the robustness of our approach up to this uncertainty level. Finally, interpretable rules were elicited for a particular application (auction fraud identification) with reduced (and thus readable) antecedent lengths and with certainty values in the consequent class labels. Additionally, an average expected uncertainty of the rules were elicited based on the uncertainty levels in those samples which formed the corresponding rules., Competing Interests: Conflict of interestThe authors have no competing interests to declare., (© The Author(s) 2022.)

Evolving fuzzy neural networks have the adaptive capacity to solve complex problems by interpreting them. This is due to the fact that this type of approach provides valuable insights that facilitate understanding the behavior of the problem being analyzed, because they can extract knowledge from a set of investigated data. Thus, this work proposes applying an evolving fuzzy neural network capable of solving data stream regression problems with considerable interpretability. The dataset is based on a necessary prediction of k barriers with wireless sensors to identify unauthorized persons entering a protected territory. Our method was empirically compared with state-of-the-art evolving methods, showing significantly lower RMSE values for separate test data sets and also lower accumulated mean absolute errors (MAEs) when evaluating the methods in a stream-based interleaved-predict-and-then-update procedure. In addition, the model could offer relevant information in terms of interpretable fuzzy rules, allowing an explainable evaluation of the regression problems contained in the data streams.

Veterinarians have a fundamental role to play in the detection of animal abuse and domestic violence cases. Therefore, it is essential that veterinary colleges provide appropriate training in animal welfare and veterinary forensics. The aim of this article is to characterize the perception and knowledge of veterinary students about training in veterinary forensics, animal welfare and the association between animal abuse and human violence. An online survey was made available to veterinary students at 227 veterinary colleges in Brazil and 22 in Colombia. The Chi-square test of independence was performed to compare responses of Brazilian and Colombian students for categorical survey items. Most of the surveyed students indicated that their college offered animal welfare training. However, only 21.8% (47/216) of the Colombian and 43.1% (216/523) of the Brazilian students mentioned that their veterinary colleges offered veterinary forensics training. Deficits in training in identification of non-accidental traumas, reporting of animal abuse and awareness of the association between interpersonal violence and animal abuse were identified in both countries. Despite this, more than 90% of students were aware of the relationship between these two crimes and in the importance of receiving compulsory training in animal abuse and veterinary forensics. Likewise, most of the respondents recognized that animal abuse includes both physical and mental abuse. The results highlight the need to improve education in animal welfare, animal abuse, human violence and veterinary forensics in veterinary colleges in Brazil and Colombia.

Heart problems are responsible for the majority of deaths worldwide. The use of intelligent techniques to assist in the identification of existing patterns in these diseases can facilitate treatments and decision making in the field of medicine. This work aims to extract knowledge from a dataset based on heart noise behaviors in order to determine whether heart murmur predilection exists or not in the analyzed patients. A heart murmur can be pathological due to defects in the heart, so the use of an evolving hybrid technique can assist in detecting this comorbidity team, and at the same time, extract knowledge through fuzzy linguistic rules, facilitating the understanding of the nature of the evaluated data. Heart disease detection tests were performed to compare the proposed hybrid model's performance with state of the art for the subject. The results obtained (90.75% accuracy) prove that in addition to great assertiveness in detecting heart murmurs, the evolving hybrid model could be concomitant with the extraction of knowledge from data submitted to an intelligent approach.

Spinocerebellar ataxia type 2 (SCA2) is an autosomal dominant degenerative disease. Pathological studies have demonstrated not only cerebellar and brainstem atrophy, but substantia nigra, motoneurons, basal ganglia, thalamus, and peripheral nerves involvement. These findings may explain non-motor and extra-cerebellar features in SCA2. We accessed the non-motor symptoms and extra-cerebellar signs in SCA2 patients in order to provide a better understanding on pathophysiological mechanisms and natural history of brain degeneration in the disease. Thirty-three SCA2 patients were evaluated and compared with 26 healthy subjects. We investigated the following variables: sleep disorders, cognitive deficit, olfactory impairment, urinary dysfunction, psychiatric symptoms, cramps, pain, movement disorders, and weight loss. SCA2 had a high frequency of REM sleep behavior disorder (48.48 %, N = 16) as well as excessive daytime sleepiness (42.42 %, N = 14). Chorea was present in 15.15 % (N = 5), dystonia in 27.27 % (N = 9), and parkinsonism in 27.27 % (N = 9). Slow saccadic pursuit was present in 87.87 % (N = 29) and ophtalmoparesis in 78.78 % (N = 26) of patients. Regarding sleep disorders, 18.18 % (N = 6) of patients had restless leg syndrome. Dysphagia was present in 39.39 % (N = 13), weight loss 24.24 % (N = 8), and urinary dysfunction 27.27 % (N = 9). Cramps was present in only 6 % of patients (N = 2). This study highlighted the high frequency of non-motor symptoms and extra-cerebellar signs in SCA2. Our findings demonstrate the widespread of nervous system involvement in SCA2 patients and contribute to better understand the natural history of brain degeneration in this genetic condition.

Motor neuron disease is one of the major groups of neurodegenerative diseases, mainly represented by amyotrophic lateral sclerosis. Despite wide genetic and biochemical data regarding its pathophysiological mechanisms, motor neuron disease develops under a complex network of mechanisms not restricted to the unique functions of the alpha motor neurons but which actually involve diverse functions of glial cell interaction. This review aims to expose some of the leading roles of glial cells in the physiological mechanisms of neuron-glial cell interactions and the mechanisms related to motor neuron survival linked to glial cell functions.

Neuromuscular junction disorders represent a wide group of neurological diseases characterized by weakness, fatigability and variable degrees of appendicular, ocular and bulbar musculature involvement. Its main group of disorders includes autoimmune conditions, such as autoimmune acquired myasthenia gravis and Lambert-Eaton syndrome. However, an important group of diseases include congenital myasthenic syndromes with a genetic and sometimes hereditary basis that resemble and mimick many of the classic myasthenia neurological manifestations, but also have different presentations, which makes them a complex clinical, therapeutic and diagnostic challenge for most clinicians. We conducted a wide review of congenital myasthenic syndromes in their clinical, genetic and therapeutic aspects.

Non-traumatic myelopathies represent a heterogeneous group of neurological conditions. Few studies report clinical and epidemiological profiles regarding the experience of referral services. Objective To describe clinical characteristics of a non-traumatic myelopathy cohort. Method Epidemiological, clinical, and radiological variables from 166 charts of patients assisted between 2001 and 2012 were compiled. Results The most prevalent diagnosis was subacute combined degeneration (11.4%), followed by cervical spondylotic myelopathy (9.6%), demyelinating disease (9%), tropical spastic paraparesis (8.4%) and hereditary spastic paraparesis (8.4%). Up to 20% of the patients presented non-traumatic myelopathy of undetermined etiology, despite the broad clinical, neuroimaging and laboratorial investigations. Conclusion Regardless an extensive evaluation, many patients with non-traumatic myelopathy of uncertain etiology. Compressive causes and nutritional deficiencies are important etiologies of non-traumatic myelopathies in our population.