Key Regions Research Articles

Repeated seizure-induced brainstem neuroinflammation contributes to post-ictal ventilatory control dysfunction.

Patients with epilepsy face heightened risk of post-ictal cardiorespiratory suppression and sudden unexpected death in epilepsy (SUDEP). Studies have shown that neuroinflammation, mediated by the activation of microglia and astrocytes, may be a cause or consequence of seizure disorders. Kcnj16 (Kir5.1) knockout rats (SS kcnj16-/- ) are susceptible to repeated audiogenic seizures and recapitulate features of human SUDEP, including post-ictal ventilatory suppression, which worsens with repeated seizures and seizure-induced mortality. In this study, we tested the hypothesis that repeated seizures cause neuroinflammation within key brainstem regions that contribute to the control of breathing. Audiogenic seizures were elicited once/day for up to 10days in groups of adult male SS kcnj16-/- rats, from which frozen brainstem biopsies of the pre-Bötzinger complex/nucleus ambiguus (preBötC/NA), Bötzinger complex (BötC), and raphe magnus (RMg) regions were subjected to a cytokine array. Several cytokines/chemokines, including IL-1α and IL-1ß, were increased selectively in preBötC/NA after 3 or 5days of seizures with fewer changes in other regions tested. In additional groups of male SS kcnj16-/- rats that underwent repeated seizures, we quantified microglial (IBA-1+) cell counts and morphology, specifically within the preBötC/NA region, and showed increased microglial cell counts, area, and volume consistent with microglial activation. To further test the role of inflammation in physiological responses to seizures and seizure-related mortality, additional groups of SS kcnj16-/- rats were treated with anakinra (IL-1R antagonist), ketoprofen (non-selective COX inhibitor), or saline for 3days before and up to 10days of seizures (1/day), and breathing was measured before, during, and after each seizure. Remarkably, IL-1R antagonism mitigated changes in post-ictal ventilatory suppression on days 7-10 but failed to prevent seizure-related mortality, whereas ketoprofen treatment exacerbated post-ictal ventilatory suppression compared to other treatment groups but prevented seizure-related mortality. These data demonstrate neuroinflammation and microglial activation within the key brainstem region of respiratory control following repeated seizures, which may functionally but differentially contribute to the pathophysiological consequences of repeated seizures.

Segmentation of underwater fish in complex aquaculture environments using enhanced Soft Attention Mechanism

Underwater fish segmentation technology serves as a crucial foundation for extracting aquatic biological information. However, due to intricate and fluctuating underwater environments, existing segmentation models fail to precisely focus on key image regions. Based on this, the paper developed an underwater fish segmentation model, Receptive Field Expansion Model(RFEM), by enhancing soft attention performance (More attention is directed to fish regions when processing fish pixels). This paper tests ten different attention mechanisms and selects the attention mechanism with better performance indicators to improve it and form an RFEM model. This paper uses two underwater fish data sets to verify the proposed model. The experimental results show the segmentation mean intersection-over-union ratio (MIoU) of RFEM based on dilation convolution reached 88.37%, and the mCPA reached 93.83%, Accuracy reached 96.08%, and F1-score reached 93.74%. It can provide solid technical support for intelligent monitoring such as body length measurement, weight estimation of underwater fish.

The effects of musicality on brain network topology in the context of Alzheimer’s disease and memory decline

Abstract Music’s role in modulating brain structure, particularly in neurodegenerative contexts such as Alzheimer’s Disease (AD), has been increasingly recognized. While previous studies have hinted at the potential neuroplastic benefits of musical engagement and training, the mechanisms through which music impacts structural connectivity in neurodegenerative pathways remain underexplored. We aimed to examine the impact of music perception skills, active musical engagement, and musical training on structural connectivity in areas relating to memory, emotion, and learning in individuals with worsening memory impairment, investigating the potential neuroplastic effects of music. Employing diffusion tensor imaging (DTI) based structural connectivity and graph theoretical analysis, we investigated brain topological features in 78 participants aged 42 to 85 with a range of memory impairments. Participants were assessed for musical training, engagement, and perception skills. The study analyzed regional and local network topological metrics to examine the influence of musical activities on graph metrics, while controlling for stages of objective memory impairment (SOMI) and diagnosis, separately. This study aimed to elucidate the effects of musical perception skills, active musical engagement, and musical training on structural connectivity within memory, emotion, and learning-related brain areas in individuals with varying degrees of memory impairment. We found enhanced structural connectivity of the right hippocampus and the right posterior cingulate cortex was associated with stronger local network metrics, such as clustering coefficient and betweenness centrality, with increased music perception skills like melody and beat perception. Musical training specifically impacted the clustering coefficient of the right hippocampus and the node degree of the right mid cingulate gyrus. Active musical engagement influenced the eigenvector centrality of the right hippocampus. Furthermore, musical training was associated with enhanced global metrics, such as global efficiency and characteristic path length. Our study integrates diffusion magnetic resonance imaging (MRI) and graph theoretical analysis to reveal significant effects of musical activities on structural connectivity in key brain regions. The results highlight the potential of musical activities to serve as a non-invasive modulatory tool for cognitive resilience, especially in memory impairment and neurodegeneration contexts. These insights contribute to the understanding of delaying AD onset and aiding early-stage patients through music-based interventions, emphasizing the importance of musical engagement in maintaining cognitive and brain health.

Can Energy-Consuming Rights Trading Policies Help to Curb Air Pollution? Evidence from China

Energy-consuming rights trading policies (ECRTPs) represent a significant institutional innovation for China aimed at achieving the dual control targets of total energy consumption and energy consumption intensity. However, the effectiveness of these policies in curbing air pollution remains uncertain. This study treats ECRTPs as a quasi-natural experiment to empirically analyze their impact on air pollution, utilizing panel data encompassing 277 prefecture-level cities in China covering the period from 2011 to 2021. Analytical methods applied include a Difference-in-Differences model, a mediation effects model, and a triple differences model to explore the effects of ECRTPs on air pollution. The findings reveal that ECRTP can significantly suppress air pollution, and this conclusion remains valid even after conducting robustness tests. Mechanism analysis indicates that ECRTPs suppress air pollution by boosting energy efficiency, advancing industrial structure upgrading, and facilitating technological innovation. Further heterogeneous studies show that ECRTPs have a more pronounced inhibitory effect on air pollution in cities that are economically and socially developed, exhibit greater energy-saving potential, are characterized as resource-based cities, and serve as key regions for the prevention and control of air pollution. The research conclusion provides empirical evidence and policy implications for evaluating the environmental effects of ECRTPs and further improving China’s energy-consuming rights trading system, as well as offering references and guidance for other developing countries to put forward ECRTPs.

Multifactor Mathematical Modeling and Analysis of the Impact of Extreme Climate on Geological Disasters

Objective: To investigate the impact of extreme climate on geological disasters in Shanxi and propose effective disaster prevention and mitigation strategies. Methods: Using daily temperature and precipitation data from 27 meteorological stations in Shanxi Province from 1975 to 2020, 32 extreme climate indices were calculated. Combined with geological disaster site data, the distribution characteristics of extreme climates and their relationship with geological disasters were analyzed, and a regression model for geological disaster risk zones was constructed. Results: Sixteen extreme climate indices in Shanxi Province showed significant changes, especially TMAXmean (100% significant). Indices related to negative precipitation effects showed a declining trend, with 77.78% being significant, while 96.3% of positive temperature effect indices showed an increasing trend, with 73.6% being significant. Geological disaster hotspots were concentrated in the mid-altitude (500–1500 m) hilly and low mountain areas along the central north–south axis and on Q and Pz strata. Extreme high-temperature indices were significantly positively correlated with geological disaster hotspots, while extreme low-temperature indices were negatively correlated. Indices related to extreme heavy precipitation (e.g., R99p.Slope, RX5day.Slope) were associated with an increase in geological disaster hotspots, whereas higher total precipitation and frequent heavy precipitation events were associated with a decrease in disaster hotspots. The grey relational degree between the Z-score and TXn.Slope, TXx.Slope, GSL.Slope, and TX90P.Slope was greater than 0.8. The random forest model performed best in evaluation metrics such as MAE, RMSE, and R2. Conclusions: Shanxi is likely to experience more extreme high-temperature and precipitation events in the future. The low-altitude hilly and terraced areas in Zones III and VII are key regions for geological disaster prevention and control. High temperatures and extreme rainfall events generally increase the disaster risk, while higher total precipitation reduces it. The random forest model is the optimal tool for predicting geological disaster risks in Shanxi Province.

Community priorities in a landscape of environmental lead contamination: Intersectionality of poverty, well-being, and environmental contamination

Kabwe, Zambia, is known in the global health world for its high concentrations of environmental lead and associated high blood lead levels in children, and thus it is a key region for exploring the intersections of human health and well-being (United Nations Sustainable Development Goal, SGD #3) and environmental health (SGD #12 and #15). Despite multiple efforts to remediate lead from the landscape, lead contamination remains pervasive in some Kabwe neighborhoods. Our study examined to what extent lead remediation was also a priority for community members. Using open-ended oral surveys with 49 household heads as well as ethnographic observational notes, we found that while lead is a concern, it is just one of many concerns. Indeed, economic concerns outweighed other concerns (SGD #1 and #6). Because community buy-in is vital to any global health intervention, these results suggest that externally defined intervention goals, such as lead remediation to address environmental toxicity, may be more successful if interventions also incorporate locally salient concerns. We conclude by arguing that social scientific studies of community members’ perspectives and concerns should be prerequisite to global health interventions. In the context of Kabwe, intervention efforts that incorporate solutions to address local concerns about poverty (SDG #1) and economic opportunity (SDG #6) may result in improved community cooperation with environmental remediation efforts, and thereby improved likelihood of sustainable environmental remediation.

Novel Deep CNNs Explore Regions, Boundaries, and Residual Learning for COVID-19 Infection Analysis in Lung CT.

COVID-19 poses a global health crisis, necessitating precise diagnostic methods for timely containment. However, accurately delineating COVID-19-affected regions in lung CT scans is challenging due to contrast variations and significant texture diversity. In this regard, this study introduces a novel two-stage classification and segmentation CNN approach for COVID-19 lung radiological pattern analysis. A novel Residual-BRNet is developed to integrate boundary and regional operations with residual learning, capturing key COVID-19 radiological homogeneous regions, texture variations, and structural contrast patterns in the classification stage. Subsequently, infectious CT images undergo lesion segmentation using the newly proposed RESeg segmentation CNN in the second stage. The RESeg leverages both average and max-pooling implementations to simultaneously learn region homogeneity and boundary-related patterns. Furthermore, novel pixel attention (PA) blocks are integrated into RESeg to effectively address mildly COVID-19-infected regions. The evaluation of the proposed Residual-BRNet CNN in the classification stage demonstrates promising performance metrics, achieving an accuracy of 97.97%, F1-score of 98.01%, sensitivity of 98.42%, and MCC of 96.81%. Meanwhile, PA-RESeg in the segmentation phase achieves an optimal segmentation performance with an IoU score of 98.43% and a dice similarity score of 95.96% of the lesion region. The framework's effectiveness in detecting and segmenting COVID-19 lesions highlights its potential for clinical applications.

Climate change is associated with higher phytoplankton biomass and longer blooms in the West Antarctic Peninsula

The Antarctic Peninsula (West Antarctica) marine ecosystem has undergone substantial changes due to climate-induced shifts in atmospheric and oceanic temperatures since the 1950s. Using 25 years of satellite data (1998-2022), this study presents evidence that phytoplankton biomass and bloom phenology in the West Antarctic Peninsula are significantly changing as a response to anthropogenic climate change. Enhanced phytoplankton biomass was observed along the West Antarctic Peninsula, particularly in the early austral autumn, resulting in longer blooms. Long-term sea ice decline was identified as the main driver enabling phytoplankton growth in early spring and autumn, in parallel with a recent intensification of the Southern Annular Mode (2010-ongoing), which was observed to influence regional variability. Our findings contribute to the understanding of the complex interplay between environmental changes and phytoplankton responses in this climatically key region of the Southern Ocean and raise important questions regarding the far-reaching consequences that these ecological changes may have on global carbon sequestration and Antarctic food webs in the future.

MULTIMEDIA CONTENT ANALYSIS FOR ALZHEIMER’S DISEASE DIAGNOSIS USING MRI SCANS AND DEEP LEARNING

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with early diagnosis being crucial for effective intervention. Magnetic Resonance Imaging (MRI) is a valuable tool for detecting structural brain changes associated with AD. However, accurate and automated analysis of MRI scans remains a challenge due to the complexity and variability in brain structures. Traditional methods for analyzing MRI scans for AD diagnosis often rely on manual interpretation or basic image processing techniques, which can be time-consuming and prone to variability. There is a need for advanced automated methods that can accurately segment brain structures and extract relevant features for reliable diagnosis. This study proposes a novel approach for AD diagnosis using MRI scans, combining Conditional Attention U-Net for segmentation and Ant Colony Optimization (ACO) for feature extraction. The Conditional Attention U-Net enhances segmentation accuracy by incorporating conditional attention mechanisms to focus on relevant features while minimizing background noise. ACO is employed to optimize feature extraction by simulating the foraging behavior of ants, which efficiently selects and refines key features related to AD. The proposed model was evaluated on a dataset of 500 MRI scans, comparing performance with traditional methods using metrics such as Dice Similarity Coefficient (DSC) and classification accuracy. The Conditional Attention U-Net achieved an average DSC of 0.89 for segmentation of key brain regions, outperforming conventional methods by 10%. The ACO-enhanced feature extraction resulted in a classification accuracy of 92% for AD diagnosis, representing a 7% improvement over baseline methods. The combination of these techniques demonstrated a significant enhancement in both segmentation precision and diagnostic accuracy, showcasing the effectiveness of the proposed approach for early AD detection.

Spatial enrichment and genomic analyses reveal the link of NOMO1 with amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a severe motor neuron disease with uncertain genetic predisposition in most sporadic cases. The spatial architecture of cell types and gene expression are the basis of cell-cell interactions, biological function and disease pathology, but are not well investigated in the human motor cortex, a key ALS-relevant brain region. Recent studies indicated single nucleus transcriptomic features of motor neuron vulnerability in ALS motor cortex. However, the brain regional vulnerability of ALS-associated genes and the genetic link between region-specific genes and ALS risk remain largely unclear. Here, we developed an entropy-weighted differential gene expression matrix-based tool (SpatialE) to identify the spatial enrichment of gene sets in spatial transcriptomics. We benchmarked SpatialE against another enrichment tool (multimodal intersection analysis) using spatial transcriptomics data from both human and mouse brain tissues. To investigate regional vulnerability, we analysed three human motor cortex and two dorsolateral prefrontal cortex tissues for spatial enrichment of ALS-associated genes. We also used Cell2location to estimate the abundance of cell types in ALS-related cortex layers. To dissect the link of regionally expressed genes and ALS risk, we performed burden analyses of rare loss-of-function variants detected by whole-genome sequencing in ALS patients and controls, then analysed differential gene expression in the TargetALS RNA-sequencing dataset. SpatialE showed more accurate and specific spatial enrichment of regional cell type markers than multimodal intersection analysis in both mouse brain and human dorsolateral prefrontal cortex. Spatial transcriptomic analyses of human motor cortex showed heterogeneous cell types and spatial gene expression profiles. We found that 260 manually curated ALS-associated genes are significantly enriched in layer 5 of the motor cortex, with abundant expression of upper motor neurons and layer 5 excitatory neurons. Burden analyses of rare loss-of-function variants in Layer 5-associated genes nominated NOMO1 as a novel ALS-associated gene in a combined sample set of 6814 ALS patients and 3324 controls (P = 0.029). Gene expression analyses in CNS tissues revealed downregulation of NOMO1 in ALS, which is consistent with a loss-of-function disease mechanism. In conclusion, our integrated spatial transcriptomics and genomic analyses identified regional brain vulnerability in ALS and the association of a layer 5 gene (NOMO1) with ALS risk.

Altered Effective Connectivity During Threat Anticipation in Individuals With Alcohol Use Disorder

BackgroundA developing theory and recent research suggest that heightened reactivity to uncertain stressors or threats may be an important individual difference factor that facilitates excessive drinking as a means of avoidance-based coping and characterizes individuals with current and past alcohol use disorder (AUD). Neuroimaging studies of unpredictable threat processing have repeatedly demonstrated activation of the anterior insula, anteromedial thalamus, and dorsal anterior cingulate cortex. In the current study, we aimed to understand how these 3 regions function as a network during anticipation of unpredictable threat (and predictable threat). MethodsParticipants were 43 adults (ages 21–30) with AUD and 26 healthy control participants. Functional magnetic resonance imaging and dynamic causal modeling were used to study interregional effective connectivities and predictable and unpredictable threat-related modulations thereof within this network. Parametric empirical Bayesian modeling was used to conduct between-group comparisons in effective connectivities. ResultsDuring unpredictable threat trials, the increased projection from the right anteromedial thalamus to the right anterior insula was significantly present only in the AUD group. This directional influence was stronger among individuals who consumed more drinks per week on average. As expected, we found no group differences in modulatory changes to effective connectivities during predictable threat trials. ConclusionsTo our knowledge, this is the first study to examine directional interactions between key frontolimbic regions during anticipation of unpredictable and predictable threat and demonstrate the importance of bottom-up thalamic-insular projections during unpredictable threat processing in AUD. Prospective studies are warranted to determine whether this association is causal.

Normative cortical activation patterns in children distinguishing one or two tactile sensory inputs points: An functional MRI study

AbstractThis study aims to determine if children follow the same cortical activation patterns as adults when responding to two‐point discrimination sensory stimuli during functional magnetic resonance imaging (fMRI). We recruited 15 children with typical development, aged between 8 and 16 years. These participants were asked to complete a two‐point discrimination test (task block) while undergoing an fMRI scan. In the two‐point stimulus test, strong activation compared to baseline was observed in the left and right frontal orbital cortex. The inferior parietal lobe also exhibited activity, particularly on the right side, with activation in both the supramarginal and angular gyri. Further activity was evident in the left supramarginal gyrus and the left paracingulate gyrus. This novel study on fMRI two‐point discrimination testing in children shows the activation patterns in key brain regions involved in somatosensory discrimination and decision making.Practical ApplicationsThis study provides crucial normative data on cortical activation patterns during two‐point discrimination testing in typically developing children. Such data serve as a valuable reference point for future research investigating sensory processing and cognitive function in pediatric populations. Researchers can use these findings to establish benchmarks and compare cortical activation patterns in children with neurodevelopmental conditions. This information is essential for exploring pathology, which may affect tactile sensation techniques and developing targeted interventions tailored to individual needs in pediatric treatment. Additionally, it lays the groundwork for further exploration into the neural mechanisms underpinning somatosensory discrimination, potentially leading to advancements in understanding and treating sensory‐related disorders in children.

Reduced Thalamic γ-Aminobutyric Acid (GABA) in Painless but Not Painful Diabetic Peripheral Neuropathy.

Alterations in the structure, function, and microcirculation of the thalamus, a key brain region involved in pain pathways, have previously been demonstrated in patients with Painless- and Painful-diabetic peripheral neuropathy (DPN). However, thalamic neurotransmitter levels including GABA (inhibitory neurotransmitter) and glutamate (excitatory neurotransmitter) in different DPN phenotypes are not known. We performed a Magnetic Resonance Spectroscopy study and quantified GABA and glutamate levels within the thalamus, in a carefully characterised cohort of participants with Painless- and Painful-DPN. Participants with DPN (Painful- and Painless combined) had a significantly lower GABA:H2O ratio compared to those without DPN (Healthy volunteers [HV] and diabetes without DPN [No-DPN]). Participants with Painless-DPN had the lowest GABA:H2O ratio, which reached significance compared with HV and No-DPN, but not Painful-DPN. There was no difference in GABA:H2O in Painful-DPN compared with all other groups. A significant correlation with GABA:H2O and neuropathy severity was also seen. This study demonstrates that lower levels of thalamic GABA in participants with Painless-DPN may reflect neuroplasticity due to reduced afferent pain impulses. Whereas partially preserved levels of GABA in Painful-DPN may indicate that central GABAergic pathways are involved in the mechanisms of neuropathic pain in diabetes.

Self-Supervised Medical Image Segmentation Using Deep Reinforced Adaptive Masking.

Self-supervised learning aims to learn transferable representations from unlabeled data for downstream tasks. Inspired by masked language modeling in natural language processing, masked image modeling (MIM) has achieved certain success in the field of computer vision, but its effectiveness in medical images remains unsatisfactory. This is mainly due to the high redundancy and small discriminative regions in medical images compared to natural images. Therefore, this paper proposes an adaptive hard masking (AHM) approach based on deep reinforcement learning to expand the application of MIM in medical images. Unlike predefined random masks, AHM uses an asynchronous advantage actor-critic (A3C) model to predict reconstruction loss for each patch, enabling the model to learn where masking is valuable. By optimizing the non-differentiable sampling process using reinforcement learning, AHM enhances the understanding of key regions, thereby improving downstream task performance. Experimental results on two medical image datasets demonstrate that AHM outperforms state-of-the-art methods. Additional experiments under various settings validate the effectiveness of AHM in constructing masked images.

Brain imaging of a gamified cognitive flexibility task in young and older adults.

The study aimed to develop and validate a gamified cognitive flexibility task through brain imaging, and to investigate behavioral and brain activation differences between young and older adults during task performance. Thirty-one young adults (aged 18-35) and 31 older adults (aged 60-80) were included in the present study. All participants underwent fMRI scans while completing the gamified cognitive flexibility task. Results showed that young adults outperformed older adults on the task. The left inferior frontal junction (IFJ), a key region of cognitive flexibility, was significantly activated during the task in both older and young adults. Comparatively, the percent signal change in the left IFJ was stronger in older adults than in young adults. Moreover, older adults demonstrated more precise representations during the task in the left IFJ. Additionally, the left inferior parietal lobule (IPL) and superior parietal lobule in older adults and the left middle frontal gyrus (MFG) and inferior frontal gyrus in young adults were also activated during the task. Psychophysiological interaction analyses showed significant functional connectivity between the left IFJ and the left IPL, as well as the right precuneus in older adults. In young adults, significant functional connectivity was found between the left IFJ and the left MFG, as well as the right angular. The current study provides preliminary evidence for the validity of the gamified cognitive flexibility task through brain imaging. The findings suggest that this task could serve as a reliable tool for assessing cognitive flexibility and for exploring age-related differences of cognitive flexibility in both brain and behavior.

TRIM35 Negatively Regulates the cGAS-STING-Mediated Signaling Pathway by Attenuating K63-Linked Ubiquitination of STING.

The cGAS-STING-mediated antiviral response plays an important role in the defense against DNA virus infection. Tripartite motif protein 35 (TRIM35), an E3 ubiquitin ligase, was identified as a positive regulator of RLR-mediated antiviral signaling in our previous study, but the effect of TRIM35 on the cGAS-STING signaling pathway has not been elucidated. Herein, we showed that TRIM35 negatively regulates the cGAS-STING signaling pathway by directly targeting STING. TRIM35 overexpression significantly inhibited the cGAMP-triggered phosphorylation of TBK1 and IRF3, attenuating IFN-β expression and the downstream antiviral response. Mechanistically, TRIM35 colocalized and directly interacted with STING in the cytoplasm. TRM35 removed K63-linked ubiquitin from STING through the C36 and C44 sites in the RING domain, which impaired the interaction of STING with TBK1 or IKKε. In addition, we demonstrated that the RING domain is a key region for the antiviral effects of TIRM35. These results collectively indicate that TRIM35 negatively regulates type I interferon (IFN-I) production by targeting and deubiquitinating STING. TRIM35 may be a potential therapeutic target for controlling viral infection.

Supraspinal glycinergic neurotransmission in pain: A scoping review of current literature.

The neurotransmitter glycine is an agonist at the strychnine-sensitive glycine receptors. In addition, it has recently been discovered to act at two new receptors, the excitatory glycine receptor and metabotropic glycine receptor. Glycine's neurotransmitter roles have been most extensively investigated in the spinal cord, where it is known to play essential roles in pain, itch, and motor function. In contrast, less is known about supraspinal glycinergic functions, and their contributions to pain circuits are largely unrecognized. As glycinergic neurons are absent from cortical regions, a clearer understanding of how supraspinal glycine modulates pain could reveal new pharmacological targets. This review aims to synthesize the published research on glycine's role in the adult brain, highlighting regions where glycine signaling may modulate pain responses. This was achieved through a scoping review methodology identifying several key regions of supraspinal pain circuitry where glycine signaling is involved. Therefore, this review unveils critical research gaps for supraspinal glycine's potential roles in pain and pain-associated responses, encouraging researchers to consider glycinergic neurotransmission more widely when investigating neural mechanisms of pain.

Impact of text-only versus large text-and-picture alcohol warning formats: A functional magnetic resonance imaging study in French young male drinkers.

Although the World Health Organization recommends visible and clear warning labels about the risks of alcohol consumption on containers and advertising, many of the currently used labels are too small to be visible. This study investigated the brain activity (using fMRI) and alcohol consumption intentions of French young men exposed to two warning formats displayed on alcoholic beverage advertisements: a small Text-only Alcohol Warning (TAW) currently used in many countries, and a larger text-and-picture alcohol warning (PAW). Seventy-four eligible 18-25-year-old male drinkers completed a face-to-face individual visit with a physician expert in addiction medicine. This was followed by the fMRI session during which they viewed 288 stimuli [96 alcohol advertisements with TAWs, the same 96 advertisements with PAWs, and 96 water advertisements (controls)] for 3 s each. If the advertisement made participants want ("yes")/do not want ("no") to consume the product, they pressed the corresponding button (self-report responses). The number of "yes" responses was compared between advertisement types with a paired sample t-test. Whole-brain and region-of-interest (ROI) analyses of the fMRI data were performed. Whole-brain BOLD fMRI highlighted contrasting effects of PAWs and TAWs. Compared with TAWs, PAWs elicited more activation in the precuneus, angular gyrus, occipital, frontal and temporal areas, and less activation in the nucleus accumbens, ventral tegmental areas, and putamen areas (regions of the reward circuit). The ROI analysis confirmed less activation in the reward circuit (left and right ventral tegmental areas, left and right nucleus accumbens) when viewing PAWs than TAWs. Analysis of the self-report responses indicated that the desire to consume the advertised alcohol product was lower when PAWs were viewed (compared with TAWs) (T = 8.18, p < 10-11). This is the first fMRI study to assess the effect of different alcohol warning formats. Our findings show that compared with TAWs, stronger PAWs in advertisements elicited less activity in key regions of the reward system. This suggests that the effects may influence the desire to consume alcohol products (self-report response analysis). These results could help policymakers who are interested in developing more effective labeling measures that target young people.

Cortical Tagged Synaptic Long-Term Depression in the Anterior Cingulate Cortex of Adult Mice.

The anterior cingulate cortex (ACC) is a key cortical region for pain perception and emotion. Different forms of synaptic plasticity, including long-term potentiation (LTP) and long-term depression (LTD), have been reported in the ACC. Synaptic tagging of LTP plays an important role in hippocampus-related associative memory. In this study, we demonstrate that synaptic tagging of LTD is detected in the ACC of adult male and female mice. This form of tagged LTD requires the activation of metabotropic glutamate receptor subtype 1 (mGluR1). The induction of tagged LTD is time-related with the strongest tagged LTD appearing when the interval between two independent stimuli is 30 min. Inhibitors of mGluR1 blocked the induction of tagged LTD; however, blocking N-methyl-d-aspartate receptors did not affect the induction of tagged LTD. Nimodipine, an inhibitor of L-type voltage-gated calcium channels, also blocked tagged LTD. In an animal model of amputation, we found that tagged LTD was either reduced or completely blocked. Together with our previous report of tagged LTP in the ACC, this study strongly suggests that excitatory synapses in the adult ACC are highly plastic. The biphasic tagging of synaptic transmission provides a new form of heterosynaptic plasticity in the ACC which has functional and pathophysiological significance in phantom pain.

MIS 3 innovative behavior and highland occupation during a stable wet episode in the Lake Tana paleoclimate record, Ethiopia

Securely dated archaeological sites from key regions and periods are critical for understanding early modern human adaptive responses to past environmental change. Here, we report new radiocarbon dates of > 42,000 cal years BP for an intensive human occupation of Gorgora rockshelter in the Ethiopian Highlands. We also document the development of innovative technologies and symbolic behaviors starting around this time. The evidenced occupation and behavioral patterns coincide with the onset and persistence of a stable wet phase in the geographically proximate high-resolution core record of Lake Tana. Range expansion into montane habitats and the subsequent development of innovative technologies and behaviors are consistent with population dispersal waves within Africa and beyond during wetter phases ~ 60–40 thousand years ago (ka).