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Importance: The mainstream use of chatbots requires a thorough investigation of their readability and quality of information. Objective: To identify readability and quality differences in information between a free and paywalled chatbot cancer-related responses, and to explore if more precise prompting can mitigate any observed differences. Design, Setting, and Participants: This cross-sectional study compared readability and information quality of a chatbot's free vs paywalled responses with Google Trends' top 5 search queries associated with breast, lung, prostate, colorectal, and skin cancers from January 1, 2021, to January 1, 2023. Data were extracted from the search tracker, and responses were produced by free and paywalled ChatGPT. Data were analyzed from December 20, 2023, to January 15, 2024. Exposures: Free vs paywalled chatbot outputs with and without prompt: "Explain the following at a sixth grade reading level: [nonprompted input]." Main Outcomes and Measures: The primary outcome measured the readability of a chatbot's responses using Flesch Reading Ease scores (0 [graduate reading level] to 100 [easy fifth grade reading level]). Secondary outcomes included assessing consumer health information quality with the validated DISCERN instrument (overall score from 1 [low quality] to 5 [high quality]) for each response. Scores were compared between the 2 chatbot models with and without prompting. Results: This study evaluated 100 chatbot responses. Nonprompted free chatbot responses had lower readability (median [IQR] Flesh Reading ease scores, 52.60 [44.54-61.46]) than nonprompted paywalled chatbot responses (62.48 [54.83-68.40]) (P < .05). However, prompting the free chatbot to reword responses at a sixth grade reading level was associated with increased reading ease scores than the paywalled chatbot nonprompted responses (median [IQR], 71.55 [68.20-78.99]) (P < .001). Prompting was associated with increases in reading ease in both free (median [IQR], 71.55 [68.20-78.99]; P < .001)and paywalled versions (median [IQR], 75.64 [70.53-81.12]; P < .001). There was no significant difference in overall DISCERN scores between the chatbot models, with and without prompting. Conclusions and Relevance: In this cross-sectional study, paying for the chatbot was found to provide easier-to-read responses, but prompting the free version of the chatbot was associated with increased response readability without changing information quality. Educating the public on how to prompt chatbots may help promote equitable access to health information.

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The relationship between type 2 diabetes mellitus (T2DM) and depression presents a significant area of medical concern, characterized by a higher incidence of depression among T2DM patients compared to the general population. This connection is not only evidenced in the prevalence of depressive symptoms in diabetic patients but also in the way these symptoms impact diabetes management. Furthermore, the influence of antidiabetic medications, especially sodium-glucose cotransporter-2 (SGLT2) inhibitors, on depression risk is a topic of ongoing research, with contrasting findings regarding the effects of drugs like metformin and pioglitazone. The aim of this study is to provide a comprehensive analysis of the relationship between T2DM and depression, focusing on the prevalence of depressive symptoms among diabetic patients, and the role of antidiabetic medications in modulating depression risk. Methods Utilizing data from the National Health and Nutrition Examination Survey (NHANES), we focused on individuals with T2DM. Depression status was assessed using the nine-item Patient Health Questionnaire (PHQ-9), a validated tool for evaluating depressive symptoms. Participants' depression status was categorized based on PHQ-9 composite scores. The analysis included demographic variables and the use of antidiabetic medications, with a focus on SGLT2 inhibitors. Logistic regression models adjusted for age, race/ethnicity, and BMI were employed. Results Our study involved 23,575 participants, of which 7,862 had T2DM. A significant difference in age and BMI was observed between diabetic and non-diabetic groups. Logistic regression analysis indicated that non-diabetic individuals had a significantly lower likelihood of depression compared to diabetic patients not on SGLT2 inhibitors. However, no statistically significant difference in depression levels was found between diabetic patients on SGLT2 inhibitors and those not on these medications. Conclusion These findings highlight the complex relationship between diabetes, antidiabetic medication, and depression. Notably, we found no significant impact of SGLT2 inhibitors on depression in diabetic patients, challenging previous assumptions about the role of specific antidiabetic drugs in mental health. We also revealed that older diabetic individuals reported fewer depressive symptoms, suggesting the influence of psychosocial factors and the need for age-specific depression management strategies. This research underscores the necessity of further studies to explore the nuanced effects of different antidiabetic medications on mental health outcomes, guiding toward more personalized treatment approaches for the mental health challenges in T2DM.

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Given humans' habitual use of screens, they rarely consider potential differences when viewing two-dimensional (2D) stimuli and real-world versions of dimensional stimuli. Dogs also have access to many forms of screens and touchpads, with owners even subscribing to dog-directed content. Humans understand that 2D stimuli are representations of real-world objects, but do dogs? In canine cognition studies, 2D stimuli are almost always used to study what is normally 3D, like faces, and may assume that both 2D and 3D stimuli are represented in the brain the same way. Here, we used awake fMRI in 15 dogs to examine the neural mechanisms underlying dogs' perception of two- and three-dimensional objects after the dogs were trained on either two- or three-dimensional versions of the objects. Activation within reward processing regions and parietal cortex of the dog brain to 2D and 3D versions of objects was determined by their training experience, as dogs trained on one dimensionality showed greater differential activation within the dimension on which they were trained. These results show that dogs do not automatically generalize between two- and three-dimensional versions of object stimuli and suggest that future research consider the implicit assumptions when using pictures or videos.

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The perception and representation of objects in the world are foundational to all animals. The relative importance of objects' physical properties versus how the objects are interacted with continues to be debated. Neural evidence in humans and nonhuman primates suggests animate-inanimate and face-body dimensions of objects are represented in the temporal cortex. However, because primates have opposable thumbs and interact with objects in similar ways, the question remains as to whether this similarity represents the evolution of a common cognitive process or whether it reflects a similarity of physical interaction. Here, we used functional magnetic resonance imaging (fMRI) in dogs to test whether the type of interaction affects object processing in an animal that interacts primarily with its mouth. In Study 1, we identified object-processing regions of cortex by having dogs passively view movies of faces and objects. In Study 2, dogs were trained to interact with two new objects with either the mouth or the paw. Then, we measured responsivity in the object regions to the presentation of these objects. Mouth-objects elicited significantly greater activity in object regions than paw-objects. Mouth-objects were also associated with activity in somatosensory cortex, suggesting dogs were anticipating mouthing interactions. These findings suggest that object perception in dogs is affected by how dogs expect to interact with familiar objects.

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In working and practical contexts, dogs rely upon their ability to discriminate a target odor from distracting odors and other sensory stimuli. Using awake functional magnetic resonance imaging (fMRI) in 18 dogs, we examined the neural mechanisms underlying odor discrimination between 2 odors and a mixture of the odors. Neural activation was measured during the presentation of a target odor (A) associated with a food reward, a distractor odor (B) associated with nothing, and a mixture of the two odors (A+B). Changes in neural activation during the presentations of the odor stimuli in individual dogs were measured over time within three regions known to be involved with odor processing: the caudate nucleus, the amygdala, and the olfactory bulbs. Average activation within the amygdala showed that dogs maximally differentiated between odor stimuli based on the stimulus-reward associations by the first run, while activation to the mixture (A+B) was most similar to the no-reward (B) stimulus. To clarify the neural representation of odor mixtures in the dog brain, we used a random forest classifier to compare multilabel (elemental) versus multiclass (configural) models. The multiclass model performed much better than the multilabel (weighted-F1 0.44 vs. 0.14), suggesting the odor mixture was processed configurally. Analysis of the subset of high-performing dogs' brain classification metrics revealed a network of olfactory information-carrying brain regions that included the amygdala, piriform cortex, and posterior cingulate. These results add further evidence for the configural processing of odor mixtures in dogs and suggest a novel way to identify high-performers based on brain classification metrics.

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The approximate number system (ANS), which supports the rapid estimation of quantity, emerges early in human development and is widespread across species. Neural evidence from both human and non-human primates suggests the parietal cortex as a primary locus of numerical estimation, but it is unclear whether the numerical competencies observed across non-primate species are subserved by similar neural mechanisms. Moreover, because studies with non-human animals typically involve extensive training, little is known about the spontaneous numerical capacities of non-human animals. To address these questions, we examined the neural underpinnings of number perception using awake canine functional magnetic resonance imaging. Dogs passively viewed dot arrays that varied in ratio and, critically, received no task-relevant training or exposure prior to testing. We found evidence of ratio-dependent activation, which is a key feature of the ANS, in canine parietotemporal cortex in the majority of dogs tested. This finding is suggestive of a neural mechanism for quantity perception that has been conserved across mammalian evolution.

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Dogs may follow their nose, but they learn associations to many types of sensory stimuli. Are some modalities learned better than others? We used awake fMRI in 19 dogs over a series of three experiments to measure reward-related learning of visual, olfactory, and verbal stimuli. Neurobiological learning curves were generated for individual dogs by measuring activation over time within three regions of interest: the caudate nucleus, amygdala, and parietotemporal cortex. The learning curves showed that dogs formed stimulus-reward associations in as little as 22 trials. Consistent with neuroimaging studies of associative learning, the caudate showed a main effect for reward-related stimuli, but not a significant interaction with modality. However, there were significant differences in the time courses, suggesting that although multiple modalities are represented in the caudate, the rates of acquisition and habituation are modality-dependent and are potentially gated by their salience in the amygdala. Visual and olfactory modalities resulted in the fastest learning, while verbal stimuli were least effective, suggesting that verbal commands may be the least efficient way to train dogs.

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How do dogs understand human words? At a basic level, understanding would require the discrimination of words from non-words. To determine the mechanisms of such a discrimination, we trained 12 dogs to retrieve two objects based on object names, then probed the neural basis for these auditory discriminations using awake-fMRI. We compared the neural response to these trained words relative to "oddball" pseudowords the dogs had not heard before. Consistent with novelty detection, we found greater activation for pseudowords relative to trained words bilaterally in the parietotemporal cortex. To probe the neural basis for representations of trained words, searchlight multivoxel pattern analysis (MVPA) revealed that a subset of dogs had clusters of informative voxels that discriminated between the two trained words. These clusters included the left temporal cortex and amygdala, left caudate nucleus, and thalamus. These results demonstrate that dogs' processing of human words utilizes basic processes like novelty detection, and for some dogs, may also include auditory and hedonic representations.

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Training dogs for awake-MRI began in 2012 for the study of canine cognition. Although originally envisioned as a research technique to understand the neural mechanisms of canine cognitive function, its potential as a new diagnostic clinical tool has become apparent. A high-quality structural scan of the brain can be acquired without sedation or anesthesia in as little as 30 s in a well-trained dog. This has opened the possibility of longitudinal imaging of CNS disease with MRI both as a means of monitoring treatment and potentially as a surveillance tool for inflammatory and neoplastic brain diseases in high-risk breeds. This same training can be used to image other body regions, such as the abdomen, enabling clinicians to screen for abdominal disease using cross sectional imaging without the need for anesthesia and without exposing the patient to ionizing radiation. We present four examples of dogs trained for awake-MRI who developed: (1) nasal carcinoma; (2) brain tumor; (3) abdominal lipoma; (4) idiopathic epilepsy.

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The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17-21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs' subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala.

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Dogs are hypersocial with humans, and their integration into human social ecology makes dogs a unique model for studying cross-species social bonding. However, the proximal neural mechanisms driving dog-human social interaction are unknown. We used functional magnetic resonance imaging in 15 awake dogs to probe the neural basis for their preferences for social interaction and food reward. In a first experiment, we used the ventral caudate as a measure of intrinsic reward value and compared activation to conditioned stimuli that predicted food, praise or nothing. Relative to the control stimulus, the caudate was significantly more active to the reward-predicting stimuli and showed roughly equal or greater activation to praise vs food in 13 of 15 dogs. To confirm that these differences were driven by the intrinsic value of social praise, we performed a second imaging experiment in which the praise was withheld on a subset of trials. The difference in caudate activation to the receipt of praise, relative to its withholding, was strongly correlated with the differential activation to the conditioned stimuli in the first experiment. In a third experiment, we performed an out-of-scanner choice task in which the dog repeatedly selected food or owner in a Y-maze. The relative caudate activation to food- and praise-predicting stimuli in Experiment 1 was a strong predictor of each dog's sequence of choices in the Y-maze. Analogous to similar neuroimaging studies of individual differences in human social reward, our findings demonstrate a neural mechanism for preference in domestic dogs that is stable within, but variable between, individuals. Moreover, the individual differences in the caudate responses indicate the potentially higher value of social than food reward for some dogs and may help to explain the apparent efficacy of social interaction in dog training.

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Based on behavioral evidence, the domestic dog has emerged as a promising comparative model of human self-control. However, while research on human inhibition has probed heterogeneity and neuropathology through an integration of neural and behavioral evidence, there are no parallel data exploring the brain mechanisms involved in canine inhibition. Here, using a combination of cognitive testing and awake neuroimaging in domestic dogs, we provide evidence precisely localizing frontal brain regions underpinning response inhibition in this species and demonstrate the dynamic relationship between these regions and behavioral measures of control. Thirteen dogs took part in an in-scanner go/no-go task and an out-of-scanner A-not-B test. A frontal brain region was identified showing elevated neural activity for all subjects during successful inhibition in the scanner, and dogs showing greater mean brain activation in this region produced fewer false alarms. Better performance in the go/no-go task was also correlated with fewer errors in the out-of-scanner A-not-B test, suggesting that dogs show consistent neurobehavioral individual differences in cognitive control, as is seen in humans. These findings help establish parity between human and canine mechanisms of self-control and pave the way for future comparative studies examining their function and dysfunction.

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Recent behavioral evidence suggests that dogs, like humans and monkeys, are capable of visual face recognition. But do dogs also exhibit specialized cortical face regions similar to humans and monkeys? Using functional magnetic resonance imaging (fMRI) in six dogs trained to remain motionless during scanning without restraint or sedation, we found a region in the canine temporal lobe that responded significantly more to movies of human faces than to movies of everyday objects. Next, using a new stimulus set to investigate face selectivity in this predefined candidate dog face area, we found that this region responded similarly to images of human faces and dog faces, yet significantly more to both human and dog faces than to images of objects. Such face selectivity was not found in dog primary visual cortex. Taken together, these findings: (1) provide the first evidence for a face-selective region in the temporal cortex of dogs, which cannot be explained by simple low-level visual feature extraction; (2) reveal that neural machinery dedicated to face processing is not unique to primates; and (3) may help explain dogs' exquisite sensitivity to human social cues.

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Understanding dogs' perceptual experience of both conspecifics and humans is important to understand how dogs evolved and the nature of their relationships with humans and other dogs. Olfaction is believed to be dogs' most powerful and perhaps important sense and an obvious place to begin for the study of social cognition of conspecifics and humans. We used fMRI in a cohort of dogs (N=12) that had been trained to remain motionless while unsedated and unrestrained in the MRI. By presenting scents from humans and conspecifics, we aimed to identify the dimensions of dogs' responses to salient biological odors - whether they are based on species (dog or human), familiarity, or a specific combination of factors. We focused our analysis on the dog's caudate nucleus because of its well-known association with positive expectations and because of its clearly defined anatomical location. We hypothesized that if dogs' primary association to reward, whether it is based on food or social bonds, is to humans, then the human scents would activate the caudate more than the conspecific scents. Conversely, if the smell of conspecifics activated the caudate more than the smell of humans, dogs' association to reward would be stronger to their fellow canines. Five scents were presented (self, familiar human, strange human, familiar dog, strange dog). While the olfactory bulb/peduncle was activated to a similar degree by all the scents, the caudate was activated maximally to the familiar human. Importantly, the scent of the familiar human was not the handler, meaning that the caudate response differentiated the scent in the absence of the person being present. The caudate activation suggested that not only did the dogs discriminate that scent from the others, they had a positive association with it. This speaks to the power of the dog's sense of smell, and it provides important clues about the importance of humans in dogs' lives. This article is part of a Special Issue entitled: Canine Behavior.

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Having previously used functional MRI to map the response to a reward signal in the ventral caudate in awake unrestrained dogs, here we examined the importance of signal source to canine caudate activation. Hand signals representing either incipient reward or no reward were presented by a familiar human (each dog's respective handler), an unfamiliar human, and via illustrated images of hands on a computer screen to 13 dogs undergoing voluntary fMRI. All dogs had received extensive training with the reward and no-reward signals from their handlers and with the computer images and had minimal exposure to the signals from strangers. All dogs showed differentially higher BOLD response in the ventral caudate to the reward versus no reward signals, and there was a robust effect at the group level. Further, differential response to the signal source had a highly significant interaction with a dog's general aggressivity as measured by the C-BARQ canine personality assessment. Dogs with greater aggressivity showed a higher differential response to the reward signal versus no-reward signal presented by the unfamiliar human and computer, while dogs with lower aggressivity showed a higher differential response to the reward signal versus no-reward signal from their handler. This suggests that specific facets of canine temperament bear more strongly on the perceived reward value of relevant communication signals than does reinforcement history, as each of the dogs were reinforced similarly for each signal, regardless of the source (familiar human, unfamiliar human, or computer). A group-level psychophysiological interaction (PPI) connectivity analysis showed increased functional coupling between the caudate and a region of cortex associated with visual discrimination and learning on reward versus no-reward trials. Our findings emphasize the sensitivity of the domestic dog to human social interaction, and may have other implications and applications pertinent to the training and assessment of working and pet dogs.

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Aging physiology greatly impacts care delivery in the geriatric patient population. Consideration should be given to addressing the patient-specific needs regarding the systemic changes seen in the aging patient. Each major body system presents its own unique challenges to the critical care practitioner, and a comprehensive understanding of these changes is necessary to effectively care for this patient population. This article summarizes these changes and provides key points for the practitioner to consider when caring for the aging patient in the critical care arena.

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Previously, we demonstrated the possibility of fMRI in two awake and unrestrained dogs. Here, we determined the replicability and heterogeneity of these results in an additional 11 dogs for a total of 13 subjects. Based on an anatomically placed region-of-interest, we compared the caudate response to a hand signal indicating the imminent availability of a food reward to a hand signal indicating no reward. 8 of 13 dogs had a positive differential caudate response to the signal indicating reward. The mean differential caudate response was 0.09%, which was similar to a comparable human study. These results show that canine fMRI is reliable and can be done with minimal stress to the dogs.

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Because of dogs' prolonged evolution with humans, many of the canine cognitive skills are thought to represent a selection of traits that make dogs particularly sensitive to human cues. But how does the dog mind actually work? To develop a methodology to answer this question, we trained two dogs to remain motionless for the duration required to collect quality fMRI images by using positive reinforcement without sedation or physical restraints. The task was designed to determine which brain circuits differentially respond to human hand signals denoting the presence or absence of a food reward. Head motion within trials was less than 1 mm. Consistent with prior reinforcement learning literature, we observed caudate activation in both dogs in response to the hand signal denoting reward versus no-reward.

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