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Summary Immunofocusing on conserved, subdominant epitopes is critical for vaccines against highly diverse viruses such as HIV-1, influenza, and SARS-CoV-2. The eight-residue N-terminus of the HIV-1 fusion peptide (FP) is one such example of a promising yet small target. We developed new FP immunogens using three alphavirus-like particles (VLPs) and introduced additional glycans to mask shared carrier-specific epitopes. In two independent guinea pig studies, sequential immunization with heterologous carriers enhanced FP-directed antibody titers, which were further improved with glycan engineering. Separately, using diverse FP variants sharing the same N-terminal six amino acids increased neutralizing antibody titers. When combined, these two strategies led to higher FP-directed titers and, after Env trimer boosting, induced FP-directed neutralizing antibodies against multi-clade wild-type HIV-1 in nearly all animals. These findings established the importance of minimizing recurrent off-target epitopes across immunizations and support the engineered VLPs as a promising platform for peptide immunization. HighlightsNovel HIV-1 fusion peptide immunogens using glycan-engineered alphavirus-like particlesImproved FP-directed response by minimizing recurrent carrier-specific epitopes across immunizationsImproved neutralizing response by sequential immunization with diverse FP variantsFP-directed antibodies neutralizing multi-clade wildtype viruses in nearly all animals 

The anterior dorsolateral striatum (DLS) is heavily innervated by convergent excitatory projections from the primary motor (M1) and sensory cortex (S1) and considered an important site of sensorimotor integration. M1 and S1 corticostriatal synapses have functional differences in their connection strength with striatal spiny projection neurons (SPNs) and fast-spiking interneurons (FSIs) in the DLS and, as a result, exert distinct influences on sensory-guided behaviors. In the present study, we tested whether M1 and S1 inputs exhibit differences in the subcellular anatomical distribution of striatal neurons. We injected adeno-associated viral vectors encoding spaghetti monster fluorescent proteins (sm.FPs) into M1 and S1 in male and female mice and used confocal microscopy to generate 3D reconstructions of corticostriatal inputs to single identified SPNs and FSIs obtained through ex vivo patch clamp electrophysiology. We found that M1 and S1 dually innervate SPNs and FSIs; however, there is a consistent bias towards the M1 input in SPNs that is not found in FSIs. In addition, M1 and S1 inputs were distributed similarly across the proximal, medial, and distal regions of SPN and FSI dendrites. Notably, closely localized M1 and S1 clusters of inputs were more prevalent in SPNs than FSIs, suggesting that cortical inputs are integrated through cell-type specific mechanisms. Our results suggest that the stronger functional connectivity from M1 to SPNs compared to S1, as previously observed, is due to a higher quantity of synaptic inputs. Our results have implications for how sensorimotor integration is performed in the striatum through cell-specific differences in corticostriatal connections. 

Random dropout has become a standard regularization technique in artificial neural networks (ANNs), but it is currently unknown whether an analogous mechanism exists in biological neural networks (BioNNs). If it does, its structure is likely to be optimized by hundreds of millions of years of evolution, which may suggest novel dropout strategies in large-scale ANNs. We propose that the brain serotonergic fibers (axons) meet some of the expected criteria because of their ubiquitous presence, stochastic structure, and ability to grow throughout the individual’s lifespan. Since the trajectories of serotonergic fibers can be modeled as paths of anomalous diffusion processes, in this proof-of-concept study we investigated a dropout algorithm based on the superdiffusive fractional Brownian motion (FBM). The results demonstrate that serotonergic fibers can potentially implement a dropout-like mechanism in brain tissue, supporting neuroplasticity. They also suggest that mathematical theories of the structure and dynamics of serotonergic fibers can contribute to the design of dropout algorithms in ANNs. 

Abstract Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counterintuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfvén waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold,α= 2 as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed >600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: preflare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine thatα= 1.63 ± 0.03. This is below the critical threshold, suggesting that Alfvén waves are an important driver of coronal heating.