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ELife Sep 2023How memories are used by the brain to guide future action is poorly understood. In olfactory associative learning in , multiple compartments of the mushroom body act in...
How memories are used by the brain to guide future action is poorly understood. In olfactory associative learning in , multiple compartments of the mushroom body act in parallel to assign a valence to a stimulus. Here, we show that appetitive memories stored in different compartments induce different levels of upwind locomotion. Using a photoactivation screen of a new collection of split-GAL4 drivers and EM connectomics, we identified a cluster of neurons postsynaptic to the mushroom body output neurons (MBONs) that can trigger robust upwind steering. These UpWind Neurons (UpWiNs) integrate inhibitory and excitatory synaptic inputs from MBONs of appetitive and aversive memory compartments, respectively. After formation of appetitive memory, UpWiNs acquire enhanced response to reward-predicting odors as the response of the inhibitory presynaptic MBON undergoes depression. Blocking UpWiNs impaired appetitive memory and reduced upwind locomotion during retrieval. Photoactivation of UpWiNs also increased the chance of returning to a location where activation was terminated, suggesting an additional role in olfactory navigation. Thus, our results provide insight into how learned abstract valences are gradually transformed into concrete memory-driven actions through divergent and convergent networks, a neuronal architecture that is commonly found in the vertebrate and invertebrate brains.
Topics: Animals; Wind; Learning; Drosophila; Smell; Neurons; Mushroom Bodies; Drosophila melanogaster
PubMed: 37721371
DOI: 10.7554/eLife.85756 -
Alzheimer's Research & Therapy Jul 2023We aimed to quantify the identification of mild cognitive impairment and/or Alzheimer's disease using olfactory-stimulated functional near-infrared spectroscopy using... (Clinical Trial)
Clinical Trial
Quantification of identifying cognitive impairment using olfactory-stimulated functional near-infrared spectroscopy with machine learning: a post hoc analysis of a diagnostic trial and validation of an external additional trial.
BACKGROUND
We aimed to quantify the identification of mild cognitive impairment and/or Alzheimer's disease using olfactory-stimulated functional near-infrared spectroscopy using machine learning through a post hoc analysis of a previous diagnostic trial and an external additional trial.
METHODS
We conducted two independent, patient-level, single-group, diagnostic interventional trials (original and additional trials) involving elderly volunteers (aged > 60 years) with suspected declining cognitive function. All volunteers were assessed by measuring the oxygenation difference in the orbitofrontal cortex using an open-label olfactory-stimulated functional near-infrared spectroscopy approach, medical interview, amyloid positron emission tomography, brain magnetic resonance imaging, Mini-Mental State Examination, and Seoul Neuropsychological Screening Battery.
RESULTS
In total, 97 (original trial) and 36 (additional trial) elderly volunteers with suspected decline in cognitive function met the eligibility criteria. The statistical model reported classification accuracies of 87.3% in patients with mild cognitive impairment and Alzheimer's disease in internal validation (original trial) but 63.9% in external validation (additional trial). The machine learning algorithm achieved 92.5% accuracy with the internal validation data and 82.5% accuracy with the external validation data. For the diagnosis of mild cognitive impairment, machine learning performed better than statistical methods with internal (86.0% versus 85.2%) and external validation data (85.4% versus 68.8%).
INTERPRETATION
In two independent trials, machine learning models using olfactory-stimulated oxygenation differences in the orbitofrontal cortex were superior in diagnosing mild cognitive impairment and Alzheimer's disease compared to classic statistical models. Our results suggest that the machine learning algorithm is stable across different patient groups and increases generalization and reproducibility.
TRIAL REGISTRATION
Clinical Research Information Service (CRiS) of Republic of Korea; CRIS numbers, KCT0006197 and KCT0007589.
Topics: Aged; Humans; Alzheimer Disease; Cognitive Dysfunction; Machine Learning; Reproducibility of Results; Spectroscopy, Near-Infrared; Middle Aged
PubMed: 37481573
DOI: 10.1186/s13195-023-01268-9 -
Alzheimer's & Dementia : the Journal of... Jun 2024Compromised autophagy, including impaired mitophagy and lysosomal function, plays pivotal roles in Alzheimer's disease (AD). Urolithin A (UA) is a gut microbial...
BACKGROUND
Compromised autophagy, including impaired mitophagy and lysosomal function, plays pivotal roles in Alzheimer's disease (AD). Urolithin A (UA) is a gut microbial metabolite of ellagic acid that stimulates mitophagy. The effects of UA's long-term treatment of AD and mechanisms of action are unknown.
METHODS
We addressed these questions in three mouse models of AD with behavioral, electrophysiological, biochemical, and bioinformatic approaches.
RESULTS
Long-term UA treatment significantly improved learning, memory, and olfactory function in different AD transgenic mice. UA also reduced amyloid beta (Aβ) and tau pathologies and enhanced long-term potentiation. UA induced mitophagy via increasing lysosomal functions. UA improved cellular lysosomal function and normalized lysosomal cathepsins, primarily cathepsin Z, to restore lysosomal function in AD, indicating the critical role of cathepsins in UA-induced therapeutic effects on AD.
CONCLUSIONS
Our study highlights the importance of lysosomal dysfunction in AD etiology and points to the high translational potential of UA.
HIGHLIGHTS
Long-term urolithin A (UA) treatment improved learning, memory, and olfactory function in Alzheimer's disease (AD) mice. UA restored lysosomal functions in part by regulating cathepsin Z (Ctsz) protein. UA modulates immune responses and AD-specific pathophysiological pathways.
Topics: Alzheimer Disease; Animals; Coumarins; Lysosomes; Mice; Mice, Transgenic; Disease Models, Animal; Mitophagy; Amyloid beta-Peptides; Cognition
PubMed: 38753870
DOI: 10.1002/alz.13847 -
Otolaryngology--head and Neck Surgery :... Jul 2023To provide a comprehensive overview on the applications of artificial intelligence (AI) in rhinology, highlight its limitations, and propose strategies for its... (Review)
Review
OBJECTIVE
To provide a comprehensive overview on the applications of artificial intelligence (AI) in rhinology, highlight its limitations, and propose strategies for its integration into surgical practice.
DATA SOURCES
Medline, Embase, CENTRAL, Ei Compendex, IEEE, and Web of Science.
REVIEW METHODS
English studies from inception until January 2022 and those focusing on any application of AI in rhinology were included. Study selection was independently performed by 2 authors; discrepancies were resolved by the senior author. Studies were categorized by rhinology theme, and data collection comprised type of AI utilized, sample size, and outcomes, including accuracy and precision among others.
CONCLUSIONS
An overall 5435 articles were identified. Following abstract and title screening, 130 articles underwent full-text review, and 59 articles were selected for analysis. Eleven studies were from the gray literature. Articles were stratified into image processing, segmentation, and diagnostics (n = 27); rhinosinusitis classification (n = 14); treatment and disease outcome prediction (n = 8); optimizing surgical navigation and phase assessment (n = 3); robotic surgery (n = 2); olfactory dysfunction (n = 2); and diagnosis of allergic rhinitis (n = 3). Most AI studies were published from 2016 onward (n = 45).
IMPLICATIONS FOR PRACTICE
This state of the art review aimed to highlight the increasing applications of AI in rhinology. Next steps will entail multidisciplinary collaboration to ensure data integrity, ongoing validation of AI algorithms, and integration into clinical practice. Future research should be tailored at the interplay of AI with robotics and surgical education.
Topics: Humans; Algorithms; Artificial Intelligence; Data Collection; Image Processing, Computer-Assisted; Robotics
PubMed: 35787221
DOI: 10.1177/01945998221110076 -
Frontiers in Pharmacology 2023Stroke, including ischemic and hemorrhagic stroke, causes massive cell death in the brain, which is followed by secondary inflammatory injury initiated by... (Review)
Review
Stroke, including ischemic and hemorrhagic stroke, causes massive cell death in the brain, which is followed by secondary inflammatory injury initiated by disease-associated molecular patterns released from dead cells. Phagocytosis, a cellular process of engulfment and digestion of dead cells, promotes the resolution of inflammation and repair following stroke. However, professional or non-professional phagocytes also phagocytose stressed but viable cells in the brain or excessively phagocytose myelin sheaths or prune synapses, consequently exacerbating brain injury and impairing repair following stroke. Phagocytosis includes the smell, eating and digestion phases. Notably, efficient phagocytosis critically depends on phagocyte capacity to take up dead cells continually due to the limited number of phagocytes vs. dead cells after injury. Moreover, phenotypic polarization of phagocytes occurring after phagocytosis is also essential to the proresolving and prorepair properties of phagocytosis. Much has been learned about the molecular signals and regulatory mechanisms governing the sense and recognition of dead cells by phagocytes during the smell and eating phase following stroke. However, some key areas remain extremely understudied, including the mechanisms involved in digestion regulation, continual phagocytosis and phagocytosis-induced phenotypic switching following stroke. Here, we summarize new discoveries related to the molecular mechanisms and multifaceted effects of phagocytosis on brain injury and repair following stroke and highlight the knowledge gaps in poststroke phagocytosis. We suggest that advancing the understanding of poststroke phagocytosis will help identify more biological targets for stroke treatment.
PubMed: 37601043
DOI: 10.3389/fphar.2023.1122527 -
Scientific Reports Aug 2023There is growing interest in canine behavioral research specifically for working dogs. Here we take advantage of a dataset of a Transportation Safety Administration...
There is growing interest in canine behavioral research specifically for working dogs. Here we take advantage of a dataset of a Transportation Safety Administration olfactory detection cohort of 628 Labrador Retrievers to perform Machine Learning (ML) prediction and classification studies of behavioral traits and environmental effects. Data were available for four time points over a 12 month foster period after which dogs were accepted into a training program or eliminated. Three supervised ML algorithms had robust performance in correctly predicting which dogs would be accepted into the training program, but poor performance in distinguishing those that were eliminated (~ 25% of the cohort). The 12 month testing time point yielded the best ability to distinguish accepted and eliminated dogs (AUC = 0.68). Classification studies using Principal Components Analysis and Recursive Feature Elimination using Cross-Validation revealed the importance of olfaction and possession-related traits for an airport terminal search and retrieve test, and possession, confidence, and initiative traits for an environmental test. Our findings suggest which tests, environments, behavioral traits, and time course are most important for olfactory detection dog selection. We discuss how this approach can guide further research that encompasses cognitive and emotional, and social and environmental effects.
Topics: Dogs; Animals; Smell; Machine Learning; Supervised Machine Learning; Algorithms; Mental Processes
PubMed: 37528118
DOI: 10.1038/s41598-023-39112-7 -
Toxics Dec 2023Honey bees are constantly threatened due to the wide use of pesticides. This study presents the effects of deltamethrin on the mortality, olfactory learning, and memory...
Honey bees are constantly threatened due to the wide use of pesticides. This study presents the effects of deltamethrin on the mortality, olfactory learning, and memory formation of the native Saudi bee . Topical and oral application of realistic field and serial dilutions of deltamethrin (250, 125, 62.5, and 25 ppm) caused significant mortality at 4, 12, 24, and 48 h posttreatment. Bee mortality increased with the increasing concentration of insecticide at all tested posttreatment times. Highest mortality was observed at 24 h and 48 h after both exposure routes. Food consumption gradually decreased with increasing concentration of deltamethrin during oral exposure. The LC of deltamethrin was determined at 12, 24, and 48 h for topical (86.28 ppm, 36.16 ppm, and 29.19 ppm, respectively) and oral (35.77 ppm, 32.53 ppm, and 30.78 ppm, respectively) exposure. Oral exposure led to significantly higher bee mortality than topical exposure of deltamethrin at 4 h and 12 h, but both exposure routes were equally toxic to bees at 24 h and 48 h. The sublethal concentrations (LC, LC, and LC) of deltamethrin significantly impaired the learning during conditioning trials, as well as the memory formation of bees at 2, 12, and 24 h after topical and oral exposure. Thus, deltamethrin inhibits learning, and bees were unable to memorize the learned task.
PubMed: 38250981
DOI: 10.3390/toxics12010025 -
EClinicalMedicine Aug 2023Lack of specific definitions of clinical characteristics, disease severity, and risk and preventive factors of post-COVID-19 syndrome (PCS) severely impacts research and...
BACKGROUND
Lack of specific definitions of clinical characteristics, disease severity, and risk and preventive factors of post-COVID-19 syndrome (PCS) severely impacts research and discovery of new preventive and therapeutics drugs.
METHODS
This prospective multicenter cohort study was conducted from February 2020 to June 2022 in 5 countries, enrolling SARS-CoV-2 out- and in-patients followed at 3-, 6-, and 12-month from diagnosis, with assessment of clinical and biochemical features, antibody (Ab) response, Variant of Concern (VoC), and physical and mental quality of life (QoL). Outcome of interest was identification of risk and protective factors of PCS by clinical phenotype, setting, severity of disease, treatment, and vaccination status. We used SF-36 questionnaire to assess evolution in QoL index during follow-up and unsupervised machine learning algorithms (principal component analysis, PCA) to explore symptom clusters. Severity of PCS was defined by clinical phenotype and QoL. We also used generalized linear models to analyse the impact of PCS on QoL and associated risk and preventive factors. CT registration number: NCT05097677.
FINDINGS
Among 1796 patients enrolled, 1030 (57%) suffered from at least one symptom at 12-month. PCA identified 4 clinical phenotypes: chronic fatigue-like syndrome (CFs: fatigue, headache and memory loss, 757 patients, 42%), respiratory syndrome (REs: cough and dyspnoea, 502, 23%); chronic pain syndrome (CPs: arthralgia and myalgia, 399, 22%); and neurosensorial syndrome (NSs: alteration in taste and smell, 197, 11%). Determinants of clinical phenotypes were different (all comparisons p < 0.05): being female increased risk of CPs, NSs, and CFs; chronic pulmonary diseases of REs; neurological symptoms at SARS-CoV-2 diagnosis of REs, NSs, and CFs; oxygen therapy of CFs and REs; and gastrointestinal symptoms at SARS-CoV-2 diagnosis of CFs. Early treatment of SARS-CoV-2 infection with monoclonal Ab (all clinical phenotypes), corticosteroids therapy for mild/severe cases (NSs), and SARS-CoV-2 vaccination (CPs) were less likely to be associated to PCS (all comparisons p < 0.05). Highest reduction in QoL was detected in REs and CPs (43.57 and 43.86 vs 57.32 in PCS-negative controls, p < 0.001). Female sex (p < 0.001), gastrointestinal symptoms (p = 0.034) and renal complications (p = 0.002) during the acute infection were likely to increase risk of severe PCS (QoL <50). Vaccination and early treatment with monoclonal Ab reduced the risk of severe PCS (p = 0.01 and p = 0.03, respectively).
INTERPRETATION
Our study provides new evidence suggesting that PCS can be classified by clinical phenotypes with different impact on QoL, underlying possible different pathogenic mechanisms. We identified factors associated to each clinical phenotype and to severe PCS. These results might help in designing pathogenesis studies and in selecting high-risk patients for inclusion in therapeutic and management clinical trials.
FUNDING
The study received funding from the Horizon 2020 ORCHESTRA project, grant 101016167; from the Netherlands Organisation for Health Research and Development (ZonMw), grant 10430012010023; from Inserm, REACTing (REsearch & ACtion emergING infectious diseases) consortium and the French Ministry of Health, grant PHRC 20-0424.
PubMed: 37654668
DOI: 10.1016/j.eclinm.2023.102107 -
The Journal of Neuroscience : the... Dec 2023Dopamine neurons (DANs) are extensively studied in the context of associative learning, in both vertebrates and invertebrates. In the acquisition of male and female...
Dopamine neurons (DANs) are extensively studied in the context of associative learning, in both vertebrates and invertebrates. In the acquisition of male and female olfactory memory, the PAM cluster of DANs provides the reward signal, and the PPL1 cluster of DANs sends the punishment signal to the Kenyon cells (KCs) of mushroom bodies, the center for memory formation. However, thermo-genetical activation of the PPL1 DANs after memory acquisition impaired aversive memory, and that of the PAM DANs impaired appetitive memory. We demonstrate that the knockdown of glutamate decarboxylase, which catalyzes glutamate conversion to GABA in PAM DANs, potentiated the appetitive memory. In addition, the knockdown of glutamate transporter in PPL1 DANs potentiated aversive memory, suggesting that GABA and glutamate co-transmitters act in an inhibitory manner in olfactory memory formation. We also found that, in γKCs, the Rdl receptor for GABA and the mGluR DmGluRA mediate the inhibition. Although multiple-spaced training is required to form long-term aversive memory, a single cycle of training was sufficient to develop long-term memory when the glutamate transporter was knocked down, in even a single subset of PPL1 DANs. Our results suggest that the mGluR signaling pathway may set a threshold for memory acquisition to allow the organisms' behaviors to adapt to changing physiological conditions and environments. In the acquisition of olfactory memory in , the PAM cluster of dopamine neurons (DANs) mediates the reward signal, while the PPL1 cluster of DANs conveys the punishment signal to the Kenyon cells of the mushroom bodies, which serve as the center for memory formation. We found that GABA co-transmitters in the PAM DANs and glutamate co-transmitters in the PPL1 DANs inhibit olfactory memory formation. Our findings demonstrate that long-term memory acquisition, which typically necessitates multiple-spaced training sessions to establish aversive memory, can be triggered with a single training cycle in cases where the glutamate co-transmission is inhibited, even within a single subset of PPL1 DANs, suggesting that the glutamate co-transmission may modulate the threshold for memory acquisition.
Topics: Animals; Female; Male; Drosophila; Smell; Dopamine; Dopaminergic Neurons; Penicillins; Glutamates; Amino Acid Transport System X-AG; gamma-Aminobutyric Acid; Mushroom Bodies; Drosophila melanogaster
PubMed: 37429719
DOI: 10.1523/JNEUROSCI.2152-22.2023 -
Frontiers in Neural Circuits 2024The olfactory tubercle (OT) is a unique part of the olfactory cortex of the mammal brain in that it is also a component of the ventral striatum. It is crucially involved... (Review)
Review
The olfactory tubercle (OT) is a unique part of the olfactory cortex of the mammal brain in that it is also a component of the ventral striatum. It is crucially involved in motivational behaviors, particularly in adaptive olfactory learning. This review introduces the basic properties of the OT, its synaptic connectivity with other brain areas, and the plasticity of the connectivity associated with learning behavior. The adaptive properties of olfactory behavior are discussed further based on the characteristics of OT neuronal circuits.
Topics: Animals; Neuronal Plasticity; Humans; Olfactory Tubercle; Learning
PubMed: 38841557
DOI: 10.3389/fncir.2024.1423505