Black Holes in Ho\v{r}ava Gravity with Higher Derivative Magnetic Terms

We consider Horava gravity coupled to Maxwell and higher derivative magnetic terms. We construct static spherically symmetric black hole solutions in the low-energy approximation. We calculate the horizon locations and temperatures in the near-extremal limit, for asymptotically flat and (anti-)de Sitter spaces. We also construct a detailed balanced version of the theory, for which we find projectable and non-projectable, non-perturbative solutions.Comment: 17 pages. v2: Up to date with published version; some minor remarks and more reference

Transcranial direct current stimulation (tDCS) reverts behavioral alterations and brainstem BDNF level increase induced by neuropathic pain model: Long-lasting effect

AbstractIntroductionNeuropathic pain (NP) is a chronic pain modality that usually results of damage in the somatosensory system. NP often shows insufficient response to classic analgesics and remains a challenge to medical treatment. The transcranial direct current stimulation (tDCS) is a non-invasive technique, which induces neuroplastic changes in central nervous system of animals and humans. The brain derived neurotrophic factor plays an important role in synaptic plasticity process. Behavior changes such as decreased locomotor and exploratory activities and anxiety disorders are common comorbidities associated with NP.ObjectiveEvaluate the effect of tDCS treatment on locomotor and exploratory activities, and anxiety-like behavior, and peripheral and central BDNF levels in rats submitted to neuropathic pain model.MethodsRats were randomly divided: Ss, SsS, SsT, NP, NpS, and NpT. The neuropathic pain model was induced by partial sciatic nerve compression at 14days after surgery; the tDCS treatment was initiated. The animals of treated groups were subjected to a 20minute session of tDCS, for eight days. The Open Field and Elevated Pluz Maze tests were applied 24h (phase I) and 7days (phase II) after the end of tDCS treatment. The serum, spinal cord, brainstem and cerebral cortex BDNF levels were determined 48h (phase I) and 8days (phase II) after tDCS treatment by ELISA.ResultsThe chronic constriction injury (CCI) induces decrease in locomotor and exploratory activities, increases in the behavior-like anxiety, and increases in the brainstem BDNF levels, the last, in phase II (one-way ANOVA/SNK, P<0.05 for all). The tDCS treatment already reverted all these effects induced by CCI (one-way ANOVA/SNK, P<0.05 for all). Furthermore, the tDCS treatment decreased serum and cerebral cortex BDNF levels and it increased these levels in the spinal cord in phase II (one-way ANOVA/SNK, P<0.05).ConclusiontDCS reverts behavioral alterations associated to neuropathic pain, indicating possible analgesic and anxiolytic tDCS effects. tDCS treatment induces changes in the BDNF levels in different regions of the central nervous system (CNS), and this effect can be attributed to different cellular signaling activations

Efeitos da pregabalina sobre alterações comportamentais induzidas pela cetamina em ratos

Objective: The aim of this study is to investigate the effects of pregabalin on the behavior of rats under the influence of ketamine, an NMDA receptor antagonist that mimics the symptoms of schizophrenia. Methods: Rats were injected with saline or 25 mg/kg ketamine intraperitoneally. After that, behavior modifications were investigated by the evaluation of stereotypy and hyperlocomotion, after treating rats with pregabalin (at doses of 30 mg/kg or 100 mg/kg) or placebo (saline solution). Results: The administration of pregabalin reduced ketamine-induced hyperlocomotion. However, neither doses of pregabalin had a significant effect on ketamine-induced stereotypy. Conclusion: This is the first study to investigate the effects of pregabalin using an animal model of psychosis. Furthermore, our results indicate that behavioral changes induced by ketamine in rats can be reversed with the use of pregabalin, suggesting its potential to treat psychotic symptoms.Objetivo: O presente estudo tem como objetivo investigar os efeitos da pregabalina sobre as alterações comportamentais em ratos induzidas pela cetamina, um antagonista do receptor glutamatérgico NMDA, utilizado em modelos animais de psicose. Métodos:\ud Ratos receberam injeção com solução salina ou cetamina, na dose de 25 mg/kg, com posterior avaliação das alterações comportamentais induzidas, através da avaliação da estereotipia e hiperlocomoção, depois destes ratos terem sido tratados com pregabalina (30 mg/kg ou 100 mg/kg) ou placebo. Resultados: A administração de pregabalina reduziu a hiperlocomoção nos ratos sob o efeito da cetamina. No entanto, nenhuma das doses de pregabalina teve efeito significativo sobre a estereotipia induzida pela cetamina. Conclusão:\ud Este é o primeiro estudo que investiga os efeitos da pregabalina em um modelo animal de psicose. Nossos resultados indicam que alterações comportamentais induzidas pela cetamina em ratos podem ser revertidas após uso da pregabalina, o que sugere um possível potencial desta no tratamento de sintomas psicóticos.CNPqINCTFMRP-USPUNES

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14