Humans can read and comprehend text rapidly, implying that readers might process multiple words per fixation. However, the extent to which parafoveal words are previewed and integrated into the evolving sentence context remains disputed. We investigated parafoveal processing during natural reading by recording brain activity and eye movements using MEG and an eye tracker while participants silently read one-line sentences. The sentences contained an unpredictable target word that was either congruent or incongruent with the sentence context. To measure parafoveal processing, we flickered the target words at 60 Hz and measured the resulting brain responses (i.e. Rapid Invisible Frequency Tagging, RIFT) during fixations on the pre-target words. Our results revealed a significantly weaker tagging response for target words that were incongruent with the previous context compared to congruent ones, even within 100ms of fixating the word immediately preceding the target. This reduction in the RIFT response was also found to be predictive of individual reading speed. We conclude that semantic information is not only extracted from the parafovea but can also be integrated with the previous context before the word is fixated. This early and extensive parafoveal processing supports the rapid word processing required for natural reading. Our study suggests that theoretical frameworks of natural reading should incorporate the concept of deep parafoveal processing.

Object classification has been proposed as a principal objective of the primate ventral visual stream and has been used as an optimization target for deep neural network models (DNNs) of the visual system. However, visual brain areas represent many different types of information, and optimizing for classification of object identity alone does not constrain how other information may be encoded in visual representations. Information about different scene parameters may be discarded altogether (\'invariance\'), represented in non-interfering subspaces of population activity (\'factorization\') or encoded in an entangled fashion. In this work, we provide evidence that factorization is a normative principle of biological visual representations. In the monkey ventral visual hierarchy, we found that factorization of object pose and background information from object identity increased in higher-level regions and strongly contributed to improving object identity decoding performance. We then conducted a large-scale analysis of factorization of individual scene parameters - lighting, background, camera viewpoint, and object pose - in a diverse library of DNN models of the visual system. Models which best matched neural, fMRI, and behavioral data from both monkeys and humans across 12 datasets tended to be those which factorized scene parameters most strongly. Notably, invariance to these parameters was not as consistently associated with matches to neural and behavioral data, suggesting that maintaining non-class information in factorized activity subspaces is often preferred to dropping it altogether. Thus, we propose that factorization of visual scene information is a widely used strategy in brains and DNN models thereof.
When looking at a picture, we can quickly identify a recognizable object, such as an apple, applying a single word label to it. Although extensive neuroscience research has focused on how human and monkey brains achieve this recognition, our understanding of how the brain and brain-like computer models interpret other complex aspects of a visual scene – such as object position and environmental context – remains incomplete. In particular, it was not clear to what extent object recognition comes at the expense of other important scene details. For example, various aspects of the scene might be processed simultaneously. On the other hand, general object recognition may interfere with processing of such details. To investigate this, Lindsey and Issa analyzed 12 monkey and human brain datasets, as well as numerous computer models, to explore how different aspects of a scene are encoded in neurons and how these aspects are represented by computational models. The analysis revealed that preventing effective separation and retention of information about object pose and environmental context worsened object identification in monkey cortex neurons. In addition, the computer models that were the most brain-like could independently preserve the other scene details without interfering with object identification. The findings suggest that human and monkey high level ventral visual processing systems are capable of representing the environment in a more complex way than previously appreciated. In the future, studying more brain activity data could help to identify how rich the encoded information is and how it might support other functions like spatial navigation. This knowledge could help to build computational models that process the information in the same way, potentially improving their understanding of real-world scenes.

When assessing protein quality, a correction needs to be made to take into consideration the availability of the amino acids. This correction is based on the digestibility of the amino acids. It is recommended to use ileal (end of small intestine) digestibility as opposed to faecal digestibility. A correction needs to be made for endogenous (gut sourced as opposed to diet sourced) amino acids to give true digestibility as opposed to apparent digestibility. Also, this correction should be made by correcting the amino acid composition for individual amino acid digestibilities as opposed to correcting all amino acids for nitrogen digestibility. Determination of true ileal amino acid digestibility requires the collection of ileal digesta. In the human there are two methods that can be used; naso-ileal intubation and using the ileostomy model. Both are discussed in detail and it is concluded that both are appropriate methods to collect ileal digesta.

Cumulative evidence suggests that intermittent fasting (IF) has beneficial effects on human metabolic health. It has been indicated that its impact on the gut microbiota may mediate these beneficial effects. As a result, we hypothesized that IF may impact the human gut microbiota. A systematic review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol using the PubMed, Scopus, and CINAHL databases. We registered our systematic review protocol in PROSPERO under registration number CRD42021270050. Human intervention studies published until April 30, 2023, were included. The quality of the included studies was assessed using National Institutes of Health (NIH) quality assessment study tools for intervention studies. The search in the database returned 166 studies, of which 13 matched all criteria for the final qualitative analysis. The body of evidence suggests that IF modulates human gut microbiota alpha and beta diversity in lean (relatively healthy) and relatively healthy overweight/obese individuals but not in individuals with metabolic syndrome. Furthermore, IF also alters human gut microbiota composition in all phenotypes. Of interest, the gut microbiota taxa or microbial metabolites after an IF intervention are associated with metabolic markers. According to this review, IF influences the diversity and taxonomic levels of the human gut microbiota. Individual metabolic phenotypes may alter the effect of IF on the diversity and taxonomic levels of the gut microbiota.

Basolateral amygdala (BLA) is a key hub for affect in the brain,1,2,3 and dysfunction within this area contributes to a host of psychiatric disorders.4,5 BLA is extensively and reciprocally interconnected with frontal cortex,6,7,8,9 and some aspects of its function are evolutionarily conserved across rodents, anthropoid primates, and humans.10 Neuron density in BLA is substantially lower in primates compared to murine rodents,11 and frontal cortex (FC) is dramatically expanded in primates, particularly the more anterior granular and dysgranular areas.12,13,14 Yet, how these anatomical differences influence the projection patterns of single BLA neurons to frontal cortex across rodents and primates is unknown. Using a barcoded connectomic approach, we assessed the single BLA neuron connections to frontal cortex in mice and macaques. We found that BLA neurons are more likely to project to multiple distinct parts of FC in mice than in macaques. Further, while single BLA neuron projections to nucleus accumbens were similarly organized in mice and macaques, BLA-FC connections differed substantially. Notably, BLA connections to subcallosal anterior cingulate cortex (scACC) in macaques were least likely to branch to other medial frontal cortex areas compared to perigenual ACC (pgACC). This pattern of connections was reversed in the mouse homologues of these areas, infralimbic and prelimbic cortex (IL and PL), mirroring functional differences between rodents and non-human primates. Taken together, these results indicate that BLA connections to FC are not linearly scaled from mice to macaques and instead the organization of single-neuron BLA connections is distinct between these species.

Reports indicate that an interaction between TRPV4 and anoctamin 1 (ANO1) could be widely involved in water efflux of exocrine glands, suggesting that the interaction could play a role in perspiration. In secretory cells of sweat glands present in mouse foot pads, TRPV4 clearly colocalized with cytokeratin 8, ANO1, and aquaporin-5 (AQP5). Mouse sweat glands showed TRPV4-dependent cytosolic Ca2+ increases that were inhibited by menthol. Acetylcholine-stimulated sweating in foot pads was temperature-dependent in wild-type, but not in TRPV4-deficient mice and was inhibited by menthol both in wild-type and TRPM8KO mice. The basal sweating without acetylcholine stimulation was inhibited by an ANO1 inhibitor. Sweating could be important for maintaining friction forces in mouse foot pads, and this possibility is supported by the finding that wild-type mice climbed up a slippery slope more easily than TRPV4-deficient mice. Furthermore, TRPV4 expression was significantly higher in controls and normohidrotic skin from patients with acquired idiopathic generalized anhidrosis (AIGA) compared to anhidrotic skin from patients with AIGA. Collectively, TRPV4 is likely involved in temperature-dependent perspiration via interactions with ANO1, and TRPV4 itself or the TRPV4/ANO 1 complex would be targeted to develop agents that regulate perspiration.
Stress, spicy foods and elevated temperatures can all trigger specialized gland cells to move water to the skin – in other words, they can make us sweat. This process is one of the most important ways by which our bodies regulate their temperature and avoid life-threatening conditions such as heatstroke. Disorders in which this function is impaired, such as AIGA (acquired idiopathic generalized anhidrosis), pose significant health risks. Finding treatments for sweat-related diseases requires a detailed understanding of the molecular mechanisms behind sweating, which has yet to be achieved. Recent research has highlighted the role of two ion channels, TRPV4 and ANO1, in regulating fluid secretion in glands that produce tears and saliva. These gate-like proteins control how certain ions move in or out of cells, which also influences water movement. Once activated by external stimuli, TRPV4 allows calcium ions to enter the cell, causing ANO1 to open and chloride ions to leave. This results in water also exiting the cell through dedicated channels, before being collected in ducts connected to the outside of the body. TRPV4, which is activated by heat, is also present in human sweat gland cells. This prompted Kashio et al. to examine the role of these channels in sweat production, focusing on mice as well as AIGA patients. Probing TRPV4, ANO1 and AQP5 (a type of water channel) levels using fluorescent antibodies confirmed that these channels are all found in the same sweat gland cells in the foot pads of mice. Further experiments highlighted that TRPV4 mediates sweat production in these animals via ANO1 activation. As rodents do not regulate their body temperature by sweating, Kashio et al. explored the biological benefits of having sweaty paws. Mice lacking TRPV4 had reduced sweating and were less able to climb a slippery slope, suggesting that a layer of sweat helps improve traction. Finally, Kashio et al. compared samples obtained from healthy volunteers with those from AIGA patients and found that TRPV4 levels are lower in individuals affected by the disease. Overall, these findings reveal new insights into the underlying mechanisms of sweating, with TRPV4 a potential therapeutic target for conditions like AIGA. The results also suggest that sweating could be controlled by local changes in temperature detected by heat-sensing channels such as TRPV4. This would depart from our current understanding that sweating is solely controlled by the autonomic nervous system, which regulates involuntary bodily functions such as saliva and tear production.

The sensorimotor system can recalibrate itself without our conscious awareness, a type of procedural learning whose computational mechanism remains undefined. Recent findings on implicit motor adaptation, such as over-learning from small perturbations and fast saturation for increasing perturbation size, challenge existing theories based on sensory errors. We argue that perceptual error, arising from the optimal combination of movement-related cues, is the primary driver of implicit adaptation. Central to our theory is the increasing sensory uncertainty of visual cues with increasing perturbations, which was validated through perceptual psychophysics (Experiment 1). Our theory predicts the learning dynamics of implicit adaptation across a spectrum of perturbation sizes on a trial-by-trial basis (Experiment 2). It explains proprioception changes and their relation to visual perturbation (Experiment 3). By modulating visual uncertainty in perturbation, we induced unique adaptation responses in line with our model predictions (Experiment 4). Overall, our perceptual error framework outperforms existing models based on sensory errors, suggesting that perceptual error in locating one\'s effector, supported by Bayesian cue integration, underpins the sensorimotor system\'s implicit adaptation.

Protein homeostasis (proteostasis) deficiency is an important contributing factor to neurological and metabolic diseases. However, how the proteostasis network orchestrates the folding and assembly of multi-subunit membrane proteins is poorly understood. Previous proteomics studies identified Hsp47 (Gene: SERPINH1), a heat shock protein in the endoplasmic reticulum lumen, as the most enriched interacting chaperone for gamma-aminobutyric type A (GABAA) receptors. Here, we show that Hsp47 enhances the functional surface expression of GABAA receptors in rat neurons and human HEK293T cells. Furthermore, molecular mechanism study demonstrates that Hsp47 acts after BiP (Gene: HSPA5) and preferentially binds the folded conformation of GABAA receptors without inducing the unfolded protein response in HEK293T cells. Therefore, Hsp47 promotes the subunit-subunit interaction, the receptor assembly process, and the anterograde trafficking of GABAA receptors. Overexpressing Hsp47 is sufficient to correct the surface expression and function of epilepsy-associated GABAA receptor variants in HEK293T cells. Hsp47 also promotes the surface trafficking of other Cys-loop receptors, including nicotinic acetylcholine receptors and serotonin type 3 receptors in HEK293T cells. Therefore, in addition to its known function as a collagen chaperone, this work establishes that Hsp47 plays a critical and general role in the maturation of multi-subunit Cys-loop neuroreceptors.

CD8+ T cells must persist and function in diverse tumor microenvironments to exert their effects. Thus, understanding common underlying expression programs could better inform the next generation of immunotherapies. We apply a generalizable matrix factorization algorithm that recovers both shared and context-specific expression programs from diverse datasets to a single-cell RNA sequencing (scRNA-seq) compendium of 33,161 CD8+ T cells from 132 patients with seven human cancers. Our meta-single-cell analyses uncover a pan-cancer T cell dysfunction program that predicts clinical non-response to checkpoint blockade in melanoma and highlights CXCR6 as a pan-cancer marker of chronically activated T cells. Cxcr6 is trans-activated by AP-1 and repressed by TCF1. Using mouse models, we show that Cxcr6 deletion in CD8+ T cells increases apoptosis of PD1+TIM3+ cells, dampens CD28 signaling, and compromises tumor growth control. Our study uncovers a TCF1:CXCR6 axis that counterbalances PD1-mediated suppression of CD8+ cell responses and is essential for effective anti-tumor immunity.

OBJECTIVE: The electroretinogram (ERG) is the summed response from all levels of the retinal processing of light, and exhibits several profound nonlinearities in the underlying processing pathways. Accurate computational models of the ERG are important, both for understanding the multifold processes of light transduction to ecologically useful signals by the retina, and for their diagnostic capabilities for the identification and characterization of retinal disease mechanisms. There are, however, very few computational models of the ERG waveform, and none that account for the full extent of its features over time.
METHODS: This study takes the neuroanalytic approach to modeling the ERG waveform, defined as a computational model based on the main features of the transmitter kinetics of the retinal neurons.
RESULTS: The present neuroanalytic model of the human rod ERG is elaborated from the same general principles as that of Hood and Birch (Vis Neurosci 8(2):107-126, 1992), but incorporates the more recent understanding of the early nonlinear stages of ERG generation by Robson and Frishman (Prog Retinal Eye Res 39:1-22, 2014). As a result, it provides a substantially better match than previous models of rod responses in six different waveform features of the ERG flash intensity series on which the Hood and Birch model was based.
CONCLUSIONS: The neuroanalytic approach extends previous models of the component waves of the ERG, and can be structured to provide an accurate characterization of the full timecourse of the ERG waveform. The approach thus holds promise for advancing the theoretical understanding of the retinal kinetics of the light response.