Tokyo, Japan – A team led by researchers from Tokyo Metropolitan University have identified the best methods to study the resting state of the brain in marmosets using functional MRI. Studies often use sedatives and anesthetics to limit movement during measurements, but the drugs themselves can affect brain activity. The team studied seven drugs and identified choices which preserved normal function while minimizing motion. Their work extends the scope of research into an important model organism.Anxious, depressive, traumatic, and other stress-related disorders are associated with large scale brain network functional connectivity changes, yet the relationship between acute stress effects and the emergence of persistent large scale network reorganization is unclear. Using male Thy 1-jRGECO1a transgenic mice, we repeatedly sampled mesoscale cortical calcium activity across dorsal neocortex. First, mice were imaged in a homecage control condition, followed by an acute foot-shock stress, a chronic variable stress protocol, an acute on chronic foot-shock stress, and finally treatment with the prototype rapid acting antidepressant ketamine or vehicle. We derived functional connectivity metrics and network efficiency in two activity bands, namely slow cortical activity (0.3–4 Hz) and theta-alpha cortical activity (4–15 Hz). Compared to homecage control, an acute foot-shock stress induced widespread increases in cortical functional connectivity and network efficiency in the 4–15 Hz temporal band before normalizing after 24 h. Conversely, chronic stress produced a selective increase in between-module functional connectivity and network efficiency in the 0.3–4 Hz band, which was reversed after treatment with the rapid acting antidepressant ketamine. The functional connectivity changes induced by acute stress in the 4–15 Hz band were strongly related to those in the slow band after chronic stress, as well as the selective effects of subanesthetic ketamine. Together, this data indicates that stress induces functional connectivity changes with spatiotemporal features that link acute stress, persistent network reorganization after chronic stress, and treatment effects.The complexity of engineering optimization problems is increasing. Classical gradient-based optimization algorithms are a mathematical means of solving complex problems whose ability to do so is limited. Metaheuristics have become more popular than exact methods for solving optimization problems because of their simplicity and the robustness of the results that they yield. Recently, population-based bio-inspired algorithms have been demonstrated to perform favorably in solving a wide range of optimization problems. The jellyfish search optimizer (JSO) is one such bio-inspired metaheuristic algorithm, which is based on the food-finding behavior of jellyfish in the ocean. According to the literature, JSO outperforms many well-known meta-heuristics in a wide range of benchmark functions and real-world applications. JSO can also be used in conjunction with other artificial intelligence-related techniques. The success of JSO in solving diverse optimization problems motivates the present comprehensive discussion of the latest findings related to JSO. This paper reviews various issues associated with JSO, such as its inspiration, variants, and applications, and will provide the latest developments and research findings concerning JSO. The systematic review contributes to the development of modified versions and the hybridization of JSO to improve upon the original JSO and present variants, and will help researchers to develop superior metaheuristic optimization algorithms with recommendations of add-on intelligent agents.

Expression of mdg4 retrotransposons during Drosophila metamorphosis activates the antiviral NF-κB factor Relish. Silencing of mdg4 or Relish at the pupal stage leads to an inability to clear exogenous viruses in adulthood. Comparison of brain samples representing different developmental stages often necessitates registering the samples to common coordinates. Although the available software tools are successful in registering 3D images of adult brains, registration of perinatal brains remains challenging due to rapid growth-dependent morphological changes and variations in developmental pace between animals. To address these challenges, we introduce CORGI (Customizable Object Registration for Groups of Images), an algorithm for the registration of perinatal brains. First, we optimized image preprocessing to increase the algorithm’s sensitivity to mismatches in registered images. Second, we developed an attention-gated simulated annealing procedure capable of focusing on the differences between perinatal brains. Third, we applied classical multidimensional scaling (CMDS) to align (“synchronize”) brain samples in time, accounting for individual development paces. We tested CORGI on 28 samples of whole-mounted perinatal mouse brains (P0–P9) and compared its accuracy with other registration algorithms. Our algorithm offers a runtime of several minutes per brain on a laptop and automates such brain registration tasks as mapping brain data to atlases, comparing experimental groups, and monitoring brain development dynamics.Chronic lymphocytic leukemia (CLL) is an incurable malignancy of B-cells. In this study, bioinformatics analyses were conducted to identify possible pathogenic roles of CK2α, which is a protein encoded by CSNK2A1, in the progression and aggressiveness of CLL. Furthermore, various computational tools were used to search for a competent inhibitor of CK2α from fungal metabolites that could be proposed for CLL therapy. In CLL patients, high-expression of CSNK2A1 was associated with early need for therapy (n = 130, p < 0.0001) and short overall survival (OS; n = 107, p = 0.005). Consistently, bioinformatics analyses showed CSNK2A1 to associate with/play roles in CLL proliferation and survival-dependent pathways. Furthermore, PPI network analysis identified interaction partners of CK2α (PPI enrichment p value = 1 × 10–16) that associated with early need for therapy (n = 130, p < 0.003) and have been known to heavily impact on the progression of CLL. These findings constructed a rational for targeting CK2α for CLL therapy. Consequently, computational analyses reported 35 fungal metabolites out of 5820 (filtered from 19,967 metabolites) to have lower binding energy (ΔG: − 10.9 to − 11.7 kcal/mol) and better binding affinity (Kd: 9.77 × 107 M−1 to 3.77 × 108 M−1) compared with the native ligand (ΔG: − 10.8, Kd: 8.3 × 107 M−−1). Furthermore, molecular dynamics simulation study established that Butyl Xanalterate-CK2α complex continuously remained stable throughout the simulation time (100 ns). Moreover, Butyl Xanalterate interacted with most of the catalytic residues, where complex was stabilized by more than 65% hydrogen bond interactions, and a significant hydrophobic interaction with residue Phe113. Here, high-expression of CSNK2A1 was implicated in the progression and poor prognosis of CLL, making it a potential therapeutic target in the disease. Butyl Xanalterate showed stable and strong interactions with CK2α, thus we propose it as a competitive inhibitor of CK2α for CLL therapy.

Where Does Consciousness Reside in the Brain? New Discovery Helps Pinpoint Its Location

A recent study has identified brain network cores with strong bidirectional connections. Science may be getting closer to figuring out where consciousness resides in the brain. New research demonstrates the significance of certain kinds of neural connections in identifying consciousness. Jun Kit.