Whereas recent studies have elucidated principles for representation of information within the entorhinal cortex, less is known about the molecular basis for information processing by entorhinal neurons. The HCN1 gene encodes ion channels that mediate hyperpolarization-activated currents (I(h)) that control synaptic integration and influence several forms of learning and memory. We asked whether hyperpolarization-activated, cation nonselective 1 (HCN1) channels control processing of information by stellate cells found within layer II of the entorhinal cortex. Axonal projections from these neurons form a major component of the synaptic input to the dentate gyrus of the hippocampus. To determine whether HCN1 channels control either the resting or the active properties of stellate neurons, we performed whole-cell recordings in horizontal brain slices prepared from adult wild-type and HCN1 knock-out mice. We found that HCN1 channels are required for rapid and full activation of hyperpolarization-activated currents in stellate neurons. HCN1 channels dominate the membrane conductance at rest, are not required for theta frequency (4-12 Hz) membrane potential fluctuations, but suppress low-frequency (<4 Hz) components of spontaneous and evoked membrane potential activity. During sustained activation of stellate cells sufficient for firing of repeated action potentials, HCN1 channels control the pattern of spike output by promoting recovery of the spike afterhyperpolarization. These data suggest that HCN1 channels expressed by stellate neurons in layer II of the entorhinal cortex are key molecular components in the processing of inputs to the hippocampal dentate gyrus, with distinct integrative roles during resting and active states.

The internal ribosome entry site (IRES) of the hepatitis C virus (HCV) drives noncanonical initiation of protein synthesis necessary for viral replication. Functional studies of the HCV IRES have focused on 80S ribosome formation but have not explored its role after the 80S ribosome is poised at the start codon. Here, we report that mutations of an IRES domain that docks in the 40S subunit’s decoding groove cause only a local perturbation in IRES structure and result in conformational changes in the IRES-rabbit 40S subunit complex. Functionally, the mutations decrease IRES activity by inhibiting the first ribosomal translocation event, and modeling results suggest that this effect occurs through an interaction with a single ribosomal protein. The ability of the HCV IRES to manipulate the ribosome provides insight into how the ribosome’s structure and function can be altered by bound RNAs, including those derived from cellular invaders.

Fluorescence microscopy is essential for biological research, offering high-contrast imaging of microscopic structures. However, the quality of these images is often compromised by optical aberrations and noise, particularly in low signal-to-noise ratio (SNR) conditions. While adaptive optics (AO) can correct aberrations, it requires costly hardware and slows down imaging; whereas current denoising approaches boost the SNR but leave out the aberration compensation. To address these limitations, we introduce HD2Net, a deep learning framework that enhances image quality by simultaneously denoising and suppressing the effect of aberrations without the need for additional hardware. Building on our previous work, HD2Net incorporates noise estimation and aberration removal modules, effectively restoring images degraded by noise and aberrations. Through comprehensive evaluation of synthetic phantoms and biological data, we demonstrate that HD2Net outperforms existing methods, significantly improving image resolution and contrast. This framework offers a promising solution for enhancing biological imaging, particularly in challenging aberrating and low-light conditions.

Fluorescence microscopy is essential for biological research, offering high-contrast imaging of microscopic structures. However, the quality of these images is often compromised by optical aberrations and noise, particularly in low signal-to-noise ratio (SNR) conditions. While adaptive optics (AO) can correct aberrations, it requires costly hardware and slows down imaging; whereas current denoising approaches boost the SNR but leave out the aberration compensation. To address these limitations, we introduce HD2Net, a deep learning framework that enhances image quality by simultaneously denoising and suppressing the effect of aberrations without the need for additional hardware. Building on our previous work, HD2Net incorporates noise estimation and aberration removal modules, effectively restoring images degraded by noise and aberrations. Through comprehensive evaluation of synthetic phantoms and biological data, we demonstrate that HD2Net outperforms existing methods, significantly improving image resolution and contrast. This framework offers a promising solution for enhancing biological imaging, particularly in challenging aberrating and low-light conditions.

Intracellular recordings are routinely used to study the synaptic and intrinsic properties of neurons in vitro. A key requirement for these recordings is a mechanically very stable preparation; thus their use in vivo had been limited previously to head-restrained animals. We have recently demonstrated that anchoring the electrode rigidly in place with respect to the skull provides sufficient stabilization for long-lasting, high-quality whole-cell recordings in awake, freely moving rats. This protocol describes our procedure in detail, adds specific instructions for targeting hippocampal CA1 pyramidal neurons and updates it with changes that facilitate patching and improve the success rate. The changes involve combining a standard, nonhead-mounted micromanipulator with a gripper to firmly hold the recording pipette during the anchoring process then gently release it afterwards. The procedure from the beginning of surgery to the end of a recording takes approximately 5 h. This technique allows new studies of the mechanisms underlying neuronal integration and cellular/synaptic plasticity in identified cells during natural behaviors.

Hedonic eating is defined as food consumption driven by palatability without physiological need. However, neural control of palatable food intake is poorly understood. We discovered that hedonic eating is controlled by a neural pathway from the peri-locus ceruleus to the ventral tegmental area (VTA). Using photometry-calibrated optogenetics, we found that VTA dopamine (VTA) neurons encode palatability to bidirectionally regulate hedonic food consumption. VTA neuron responsiveness was suppressed during food consumption by semaglutide, a glucagon-like peptide receptor 1 (GLP-1R) agonist used as an antiobesity drug. Mice recovered palatable food appetite and VTA neuron activity during repeated semaglutide treatment, which was reversed by consumption-triggered VTA neuron inhibition. Thus, hedonic food intake activates VTA neurons, which sustain further consumption, a mechanism that opposes appetite reduction by semaglutide.

PURPOSE: The aim of the study was to examine acculturation and established risk factors in explaining variation in periodontitis prevalence among Hispanic/Latino subgroups.

METHODS: Participants were 12,730 dentate adults aged 18-74 years recruited into the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) from four U.S. field centers between 2008 and 2011. A standardized periodontal assessment measured probing pocket depth and gingival recession at six sites per tooth for up to 28 teeth. Periodontitis was defined according to the Centers for Disease Control and Prevention and American Academy of Periodontology case classifications developed for population surveillance. Covariates included acculturation indicators and established periodontitis risk factors. Survey estimation procedures took account of the complex sampling design. Adjusted multivariate binomial regression estimated prevalence ratios and 95% confidence limits (CLs).

RESULTS: Unadjusted prevalence of moderate and severe periodontitis was 38.5% and ranged from 24.7% among Dominicans to 52.1% among Cubans. Adjusted prevalence ratios for subgroups relative to Dominicans were as follows: (1) 1.34 (95% CL, 1.13-1.58) among South Americans; (2) 1.37 (95% CL, 1.17-1.61) among Puerto Ricans; (3) 1.43 (95% CL, 1.25-1.64) among Mexicans; (4) 1.53 (95% CL, 1.32-1.76) among Cubans; and (5) 1.55 (95% CL, 1.35-1.78) among Central Americans.

CONCLUSIONS: Heterogeneity in prevalence of moderate/severe periodontitis among Hispanic/Latino subpopulations was not explained by acculturation or periodontitis risk factors.

The mechanistic operation of brain regions is often interpreted by partitioning constituent neurons into 'cell types'. Historically, such cell types were broadly defined by their correspondence to gross features of the nervous system (such as cytoarchitecture). Modern-day neuroscientific techniques, enabling a more nuanced examination of neuronal properties, have illustrated a wealth of heterogeneity within these classical cell types. Here, we review the extent of this within-cell-type heterogeneity in one of the simplest cortical regions of the mammalian brain, the rodent hippocampus. We focus on the mounting evidence that the classical CA3, CA1 and subiculum pyramidal cell types all exhibit prominent and spatially patterned within-cell-type heterogeneity, and suggest these cell types provide a model system for exploring the organization and function of such heterogeneity. Given that the hippocampus is structurally simple and evolutionarily ancient, within-cell-type heterogeneity is likely to be a general and crucial feature of the mammalian brain.

Although associative learning has been localized to specific brain areas in many animals, identifying the underlying synaptic processes in vivo has been difficult. Here, we provide the first demonstration of long-term synaptic plasticity at the output site of the Drosophila mushroom body. Pairing an odor with activation of specific dopamine neurons induces both learning and odor-specific synaptic depression. The plasticity induction strictly depends on the temporal order of the two stimuli, replicating the logical requirement for associative learning. Furthermore, we reveal that dopamine action is confined to and distinct across different anatomical compartments of the mushroom body lobes. Finally, we find that overlap between sparse representations of different odors defines both stimulus specificity of the plasticity and generalizability of associative memories across odors. Thus, the plasticity we find here not only manifests important features of associative learning but also provides general insights into how a sparse sensory code is read out.

Gap junctions play an important role in the regulation of neuronal metabolism and homeostasis by serving as connections that enable small molecules to pass between cells and synchronize activity between cells. Although recent studies have linked gap junctions to memory formation, it remains unclear how they contribute to this process. Gap junctions are hexameric hemichannels formed from the connexin and pannexin gene families in chordates and the innexin (inx) gene family in invertebrates. Here we show that two modulatory neurons, the anterior paired lateral (APL) neuron and the dorsal paired medial (DPM) neuron, form heterotypic gap junctions within the mushroom body (MB), a learning and memory center in the Drosophila brain. Using RNA interference-mediated knockdowns of inx7 and inx6 in the APL and DPM neurons, respectively, we found that flies showed normal olfactory associative learning and intact anesthesia-resistant memory (ARM) but failed to form anesthesia-sensitive memory (ASM). Our results reveal that the heterotypic gap junctions between the APL and DPM neurons are an essential part of the MB circuitry for memory formation, potentially constituting a recurrent neural network to stabilize ASM.