Objective: This study aimed to evaluate the utility of the Korean version of the Quantitative Checklist for Autism in Toddlers (Q-CHAT) in hospital settings and to identify items sensitive for detecting autism spectrum disorder (ASD) trait. Methods: The Q-CHAT was administered to a clinical sample of children presenting with developmental delays with a high probability of ASD in a hospital setting (n=37), as well as to typically developing community children (n=67), aged 12 to 54 months. Results: The mean Q-CHAT total score in the hospital sample (42.0±13.6) was significantly higher than in the community sample (29.9±7.8), with maximized sensitivity and adequate specificity at 32.5 (sensitivity=0.811, specificity=0.687). The internal consistency of Q-CHAT was 0.764 for the overall sample and 0.825 for the hospital sample. Q-CHAT total scores and item scores in the hospital sample remained stable across age groups, indicating age-invariant properties. The hospital sample showed higher endorsement of less favorable development in social interaction and reciprocity items compared to community sample. No difference in the Q-CHAT item scores was present among age groups in the hospital samples. In the community samples, item scores, such as comprehending a child’s speech, using the hand of others as a tool, adapting to a change in routine, repeating the same action, and making unusual finger movements, decreased with the advance of age. Conclusion The Korean version of the Q-CHAT demonstrates good validity and reliability and is effective in discriminating autistic traits even in children older than 24 months. The items endorsed for hospital samples varied from community samples, implying item-specific sensitivity for hospital samples.

Objective: This study aimed to evaluate the utility of the Korean version of the Quantitative Checklist for Autism in Toddlers (Q-CHAT) in hospital settings and to identify items sensitive for detecting autism spectrum disorder (ASD) trait. Methods: The Q-CHAT was administered to a clinical sample of children presenting with developmental delays with a high probability of ASD in a hospital setting (n=37), as well as to typically developing community children (n=67), aged 12 to 54 months. Results: The mean Q-CHAT total score in the hospital sample (42.0±13.6) was significantly higher than in the community sample (29.9±7.8), with maximized sensitivity and adequate specificity at 32.5 (sensitivity=0.811, specificity=0.687). The internal consistency of Q-CHAT was 0.764 for the overall sample and 0.825 for the hospital sample. Q-CHAT total scores and item scores in the hospital sample remained stable across age groups, indicating age-invariant properties. The hospital sample showed higher endorsement of less favorable development in social interaction and reciprocity items compared to community sample. No difference in the Q-CHAT item scores was present among age groups in the hospital samples. In the community samples, item scores, such as comprehending a child’s speech, using the hand of others as a tool, adapting to a change in routine, repeating the same action, and making unusual finger movements, decreased with the advance of age. Conclusion The Korean version of the Q-CHAT demonstrates good validity and reliability and is effective in discriminating autistic traits even in children older than 24 months. The items endorsed for hospital samples varied from community samples, implying item-specific sensitivity for hospital samples.

Objective: This study aimed to evaluate the utility of the Korean version of the Quantitative Checklist for Autism in Toddlers (Q-CHAT) in hospital settings and to identify items sensitive for detecting autism spectrum disorder (ASD) trait. Methods: The Q-CHAT was administered to a clinical sample of children presenting with developmental delays with a high probability of ASD in a hospital setting (n=37), as well as to typically developing community children (n=67), aged 12 to 54 months. Results: The mean Q-CHAT total score in the hospital sample (42.0±13.6) was significantly higher than in the community sample (29.9±7.8), with maximized sensitivity and adequate specificity at 32.5 (sensitivity=0.811, specificity=0.687). The internal consistency of Q-CHAT was 0.764 for the overall sample and 0.825 for the hospital sample. Q-CHAT total scores and item scores in the hospital sample remained stable across age groups, indicating age-invariant properties. The hospital sample showed higher endorsement of less favorable development in social interaction and reciprocity items compared to community sample. No difference in the Q-CHAT item scores was present among age groups in the hospital samples. In the community samples, item scores, such as comprehending a child’s speech, using the hand of others as a tool, adapting to a change in routine, repeating the same action, and making unusual finger movements, decreased with the advance of age. Conclusion The Korean version of the Q-CHAT demonstrates good validity and reliability and is effective in discriminating autistic traits even in children older than 24 months. The items endorsed for hospital samples varied from community samples, implying item-specific sensitivity for hospital samples.

Objective: This study aimed to evaluate the utility of the Korean version of the Quantitative Checklist for Autism in Toddlers (Q-CHAT) in hospital settings and to identify items sensitive for detecting autism spectrum disorder (ASD) trait. Methods: The Q-CHAT was administered to a clinical sample of children presenting with developmental delays with a high probability of ASD in a hospital setting (n=37), as well as to typically developing community children (n=67), aged 12 to 54 months. Results: The mean Q-CHAT total score in the hospital sample (42.0±13.6) was significantly higher than in the community sample (29.9±7.8), with maximized sensitivity and adequate specificity at 32.5 (sensitivity=0.811, specificity=0.687). The internal consistency of Q-CHAT was 0.764 for the overall sample and 0.825 for the hospital sample. Q-CHAT total scores and item scores in the hospital sample remained stable across age groups, indicating age-invariant properties. The hospital sample showed higher endorsement of less favorable development in social interaction and reciprocity items compared to community sample. No difference in the Q-CHAT item scores was present among age groups in the hospital samples. In the community samples, item scores, such as comprehending a child’s speech, using the hand of others as a tool, adapting to a change in routine, repeating the same action, and making unusual finger movements, decreased with the advance of age. Conclusion The Korean version of the Q-CHAT demonstrates good validity and reliability and is effective in discriminating autistic traits even in children older than 24 months. The items endorsed for hospital samples varied from community samples, implying item-specific sensitivity for hospital samples.

Objective: This study aimed to evaluate the utility of the Korean version of the Quantitative Checklist for Autism in Toddlers (Q-CHAT) in hospital settings and to identify items sensitive for detecting autism spectrum disorder (ASD) trait. Methods: The Q-CHAT was administered to a clinical sample of children presenting with developmental delays with a high probability of ASD in a hospital setting (n=37), as well as to typically developing community children (n=67), aged 12 to 54 months. Results: The mean Q-CHAT total score in the hospital sample (42.0±13.6) was significantly higher than in the community sample (29.9±7.8), with maximized sensitivity and adequate specificity at 32.5 (sensitivity=0.811, specificity=0.687). The internal consistency of Q-CHAT was 0.764 for the overall sample and 0.825 for the hospital sample. Q-CHAT total scores and item scores in the hospital sample remained stable across age groups, indicating age-invariant properties. The hospital sample showed higher endorsement of less favorable development in social interaction and reciprocity items compared to community sample. No difference in the Q-CHAT item scores was present among age groups in the hospital samples. In the community samples, item scores, such as comprehending a child’s speech, using the hand of others as a tool, adapting to a change in routine, repeating the same action, and making unusual finger movements, decreased with the advance of age. Conclusion The Korean version of the Q-CHAT demonstrates good validity and reliability and is effective in discriminating autistic traits even in children older than 24 months. The items endorsed for hospital samples varied from community samples, implying item-specific sensitivity for hospital samples.

The orbitofrontal cortex (OFC) plays a crucial role in mood disorders; however, its specific role in the emotional behaviors of mice remains unclear.This study investigates the bidirectional control of emotional behaviors using population calcium dynamics and optogenetic manipulation of OFC neurons. Fiber photometry of OFC neurons revealed that OFC excitatory neurons consistently responded to the onset and offset of aversive conditions, showing decreased activation in response to anxiogenic and stressful stimuli, including tail suspension, restraint stress, and exposure to the center of the open field. The selective activation of excitatory neurons in the OFC reduced the time spent in the center of the open field, whereas optogenetic activation of inhibitory neurons in the OFC induced the opposite behavioral changes. We also provided a brain-wide activation map for OFC excitatory and inhibitory neuron activation. Our findings demonstrate that excitatory and inhibitory neurons in the OFC play opposing roles in the regulation of emotional behaviors. These results provide new insights into the neural mechanisms underlying emotional control and suggest that targeting these specific neuronal populations may offer novel therapeutic strategies for emotional disorders.

The orbitofrontal cortex (OFC) plays a crucial role in mood disorders; however, its specific role in the emotional behaviors of mice remains unclear.This study investigates the bidirectional control of emotional behaviors using population calcium dynamics and optogenetic manipulation of OFC neurons. Fiber photometry of OFC neurons revealed that OFC excitatory neurons consistently responded to the onset and offset of aversive conditions, showing decreased activation in response to anxiogenic and stressful stimuli, including tail suspension, restraint stress, and exposure to the center of the open field. The selective activation of excitatory neurons in the OFC reduced the time spent in the center of the open field, whereas optogenetic activation of inhibitory neurons in the OFC induced the opposite behavioral changes. We also provided a brain-wide activation map for OFC excitatory and inhibitory neuron activation. Our findings demonstrate that excitatory and inhibitory neurons in the OFC play opposing roles in the regulation of emotional behaviors. These results provide new insights into the neural mechanisms underlying emotional control and suggest that targeting these specific neuronal populations may offer novel therapeutic strategies for emotional disorders.

The orbitofrontal cortex (OFC) plays a crucial role in mood disorders; however, its specific role in the emotional behaviors of mice remains unclear.This study investigates the bidirectional control of emotional behaviors using population calcium dynamics and optogenetic manipulation of OFC neurons. Fiber photometry of OFC neurons revealed that OFC excitatory neurons consistently responded to the onset and offset of aversive conditions, showing decreased activation in response to anxiogenic and stressful stimuli, including tail suspension, restraint stress, and exposure to the center of the open field. The selective activation of excitatory neurons in the OFC reduced the time spent in the center of the open field, whereas optogenetic activation of inhibitory neurons in the OFC induced the opposite behavioral changes. We also provided a brain-wide activation map for OFC excitatory and inhibitory neuron activation. Our findings demonstrate that excitatory and inhibitory neurons in the OFC play opposing roles in the regulation of emotional behaviors. These results provide new insights into the neural mechanisms underlying emotional control and suggest that targeting these specific neuronal populations may offer novel therapeutic strategies for emotional disorders.

The orbitofrontal cortex (OFC) plays a crucial role in mood disorders; however, its specific role in the emotional behaviors of mice remains unclear.This study investigates the bidirectional control of emotional behaviors using population calcium dynamics and optogenetic manipulation of OFC neurons. Fiber photometry of OFC neurons revealed that OFC excitatory neurons consistently responded to the onset and offset of aversive conditions, showing decreased activation in response to anxiogenic and stressful stimuli, including tail suspension, restraint stress, and exposure to the center of the open field. The selective activation of excitatory neurons in the OFC reduced the time spent in the center of the open field, whereas optogenetic activation of inhibitory neurons in the OFC induced the opposite behavioral changes. We also provided a brain-wide activation map for OFC excitatory and inhibitory neuron activation. Our findings demonstrate that excitatory and inhibitory neurons in the OFC play opposing roles in the regulation of emotional behaviors. These results provide new insights into the neural mechanisms underlying emotional control and suggest that targeting these specific neuronal populations may offer novel therapeutic strategies for emotional disorders.

The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, has garnered interest in the application of generative artificial intelligence (AI) models in the medical field. This review summarizes different generative AI models and their potential applications in the field of medicine and explores the evolving landscape of Generative Adversarial Networks and diffusion models since the introduction of generative AI models. These models have made valuable contributions to the field of radiology. Furthermore, this review also explores the significance of synthetic data in addressing privacy concerns and augmenting data diversity and quality within the medical domain, in addition to emphasizing the role of inversion in the investigation of generative models and outlining an approach to replicate this process. We provide an overview of Large Language Models, such as GPTs and bidirectional encoder representations (BERTs), that focus on prominent representatives and discuss recent initiatives involving language-vision models in radiology, including innovative large language and vision assistant for biomedicine (LLaVa-Med), to illustrate their practical application.This comprehensive review offers insights into the wide-ranging applications of generative AI models in clinical research and emphasizes their transformative potential.