Speckle-enabled in vivo demixing of neural activity in the mouse brain.

Functional imaging of neuronal activity in awake animals, using a combination of fluorescent reporters of neuronal activity and various types of microscopy modalities, has become an indispensable tool in neuroscience. While various imaging modalities based on one-photon (1P) excitation and parallel (camera-based) acquisition have been successfully used for imaging more transparent samples, when imaging mammalian brain tissue, due to their scattering properties, two-photon (2P) microscopy systems are necessary. In 2P microscopy, the longer excitation wavelengths reduce the amount of scattering while the diffraction-limited 3D localization of excitation largely eliminates out-of-focus fluorescence. However, this comes at the cost of time-consuming serial scanning of the excitation spot and more complex and expensive instrumentation. Thus, functional 1P imaging modalities that can be used beyond the most transparent specimen are highly desirable. Here, we transform light scattering from an obstacle into a tool. We use speckles with their unique patterns and contrast, formed when fluorescence from individual neurons propagates through rodent cortical tissue, to encode neuronal activity. Spatiotemporal demixing of these patterns then enables functional recording of neuronal activity from a group of discriminable sources. For the first time, we provide an experimental, in vivo characterization of speckle generation, speckle imaging and speckle-assisted demixing of neuronal activity signals in the scattering mammalian brain tissue. We found that despite an initial fast speckle decorrelation, substantial correlation was maintained over minute-long timescales that contributed to our ability to demix temporal activity traces in the mouse brain in vivo. Informed by in vivo quantifications of speckle patterns from single and multiple neurons excited using 2P scanning excitation, we recorded and demixed activity from several sources excited using 1P oblique illumination. In our proof-of-principle experiments, we demonstrate in vivo speckle-assisted demixing of functional signals from groups of sources in a depth range of 220-320 µm in mouse cortex, limited by available speckle contrast. Our results serve as a basis for designing an in vivo functional speckle imaging modality and for maximizing the key resource in any such modality, the speckle contrast. We anticipate that our results will provide critical quantitative guidance to the community for designing techniques that overcome light scattering as a fundamental limitation in bioimaging.

Enhanced Microstructural Uniformity in Sulfuric-Acid-Treated Poly(3,4-Ethylenedioxythiophene):Poly(Styrene Sulfonate) Films Using Raman Map Analysis.

Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) films have emerged as potential alternatives to indium-tin oxide as transparent electrodes in optoelectronic devices because of their superior transparency, flexibility, and chemical doping stability. However, pristine PEDOT:PSS films show low conductivities because the insulating PSS-rich domains isolate the conductive PEDOT-rich domains. In this study, the conductivities and corresponding spatially resolved Raman properties of PEDOT:PSS thin films treated with various concentrations of H2SO4 are presented. After the PEDOT:PSS films are treated with the H2SO4 solutions, their electrical conductivities are significantly improved from 0.5 (nontreated) to 4358 S cm-1 (100% v/v). Raman heat maps of the peak shifts and widths of the Cα═Cß stretching mode are constructed. A blueshift and width decrease of the Cα═Cß Raman mode in PEDOT are uniformly observed in the entire measurement area (20 × 20 µm2), indicating that microstructural transitions are successfully accomplished across the area from the coiled to linear conformation and high crystallinity upon H2SO4 treatment. Thus, it is proved that comprehensive Raman map analysis can be easily utilized to clarify microstructural properties distributed in large areas induced by various dopants. These results also offer valuable insights for evaluating and optimizing the performance of other conductive thin films.

Clustering plasma concentration-time curves: applications of unsupervised learning in pharmacogenomics.

Pharmaceutical researchers are continually searching for techniques to improve both drug development processes and patient outcomes. An area of recent interest is the potential for machine learning (ML) applications within pharmacology. One such application not yet given close study is the unsupervised clustering of plasma concentration-time curves, hereafter, pharmacokinetic (PK) curves. In this paper, we present our findings on how to cluster PK curves by their similarity. Specifically, we find clustering to be effective at identifying similar-shaped PK curves and informative for understanding patterns within each cluster of PK curves. Because PK curves are time series data objects, our approach utilizes the extensive body of research related to the clustering of time series data as a starting point. As such, we examine many dissimilarity measures between time series data objects to find those most suitable for PK curves. We identify Euclidean distance as generally most appropriate for clustering PK curves, and we further show that dynamic time warping, Fréchet, and structure-based measures of dissimilarity like correlation may produce unexpected results. As an illustration, we apply these methods in a case study with 250 PK curves used in a previous pharmacogenomic study. Our case study finds that an unsupervised ML clustering with Euclidean distance, without any subject genetic information, is able to independently validate the same conclusions as the reference pharmacogenomic results. To our knowledge, this is the first such demonstration. Further, the case study demonstrates how the clustering of PK curves may generate insights that could be difficult to perceive solely with population level summary statistics of PK metrics.

Effect of virtual reality-based biofeedback for depressive and anxiety symptoms: Randomized controlled study.

BACKGROUND: The use of virtual reality (VR)-based biofeedback (BF), a relatively new intervention, is a non-pharmacological treatment of depressive and anxiety symptoms. However, studies on VR-based BF are lacking and inconclusive. METHODS: A total of 131 adults were recruited from the community. Participants who scored ≥10 on the Patient Health Questionnaire-9 (PHQ-9) or ≥9 on the Panic Disorder Severity Scale (PDSS) were included in the group with depressive or anxiety symptoms (DAS group), and others as the healthy control group (HC group). Participants from the DAS group were randomly assigned to VR-based or conventional BF intervention. All individuals visited at three times (weeks 0, 2, and 4), and completed the Montgomery-Asberg Depression Rating Scale (MADRS), the State-Trait Anxiety Inventory (STAI), and a visual analog scale (VAS) before and after the intervention, and PHQ-9 at the beginning and final visit. RESULTS: The analysis included a total of 118 participants (DAS/VR: 40, DAS/BF: 38, HC/VR: 40). There was no significant difference in demographic variables among the three groups. After the intervention, the DAS/VR group exhibited significant decreases in MADRS (70.0 %), PHQ-9 (64.1 %), STAI (29.5 %), and VAS (61.7 %) scores compared to the baseline (p <0.001). There were no significant differences between the effects of VR-based BF and conventional BF with a therapist. The HC group also showed significant decreases in the measures of depression and anxiety after receiving VR-based BF. CONCLUSION: VR-based BF was effective in reducing depressive and anxiety symptoms, even for subthreshold depression and anxiety symptoms in the HC group.

Association between cerebral artery stenosis and depressive symptoms in elderly patients.

OBJECTIVE: To examine the association between cerebral artery stenosis and depressive symptoms in elderly patients. METHODS: The study participants were 365 patients aged ≥65 years who visited the psychiatric outpatient clinic, Samsung Medical Center between January 1, 2000, and December 31, 2019, and were diagnosed with depressive disorder. They had brain imaging tests including magnetic resonance angiography (MRA), psychological evaluations including the 15-item Geriatric Depression Scale (GDS-15), and lab tests. Individuals' cerebral artery stenosis was identified and the association with significant depressive symptoms was examined. RESULTS: Of the 365 subjects, 108 had at least one location of cerebral artery stenosis (29.6 %). The mean score of GDS-15 in the stenosis group was 8.1 (SD, 3.8), higher than the mean GDS-15 score of 6.5 (SD, 4.0) for the group without stenosis (p < 0.001). Compared to no middle cerebral artery (MCA) stenosis, having MCA stenosis was associated with significant depressive symptoms (p = 0.005). Compared to no posterior cerebral artery (PCA) stenosis, having left PCA stenosis was associated with significant depressive symptoms (p = 0.022). In the multivariable linear regression analysis, only bilateral MCA stenosis had a positive association with the score of GDS-15 (p = 0.013). CONCLUSION: Bilateral MCA stenosis and left PCA stenosis are associated with significant depressive symptoms among elderly patients, with bilateral MCA stenosis positively associated with the severity of depression.

Combination of induced pluripotent stem cell-derived motor neuron progenitor cells with irradiated brain-derived neurotrophic factor over-expressing engineered mesenchymal stem cells enhanced restoration of axonal regeneration in a chronic spinal cord injury rat model.

BACKGROUND: Spinal cord injury (SCI) is a disease that causes permanent impairment of motor, sensory, and autonomic nervous system functions. Stem cell transplantation for neuron regeneration is a promising strategic treatment for SCI. However, selecting stem cell sources and cell transplantation based on experimental evidence is required. Therefore, this study aimed to investigate the efficacy of combination cell transplantation using the brain-derived neurotrophic factor (BDNF) over-expressing engineered mesenchymal stem cell (BDNF-eMSC) and induced pluripotent stem cell-derived motor neuron progenitor cell (iMNP) in a chronic SCI rat model. METHOD: A contusive chronic SCI was induced in Sprague-Dawley rats. At 6 weeks post-injury, BDNF-eMSC and iMNP were transplanted into the lesion site via the intralesional route. At 12 weeks post-injury, differentiation and growth factors were evaluated through immunofluorescence staining and western blot analysis. Motor neuron differentiation and neurite outgrowth were evaluated by co-culturing BDNF-eMSC and iMNP in vitro in 2-dimensional and 3-dimensional. RESULTS: Combination cell transplantation in the chronic SCI model improved behavioral recovery more than single-cell transplantation. Additionally, combination cell transplantation enhanced mature motor neuron differentiation and axonal regeneration at the injured spinal cord. Both BDNF-eMSC and iMNP played a critical role in neurite outgrowth and motor neuron maturation via BDNF expression. CONCLUSIONS: Our results suggest that the combined transplantation of BDNF- eMSC and iMNP in chronic SCI results in a significant clinical recovery. The transplanted iMNP cells predominantly differentiated into mature motor neurons. Additionally, BDNF-eMSC exerts a paracrine effect on neuron regeneration through BDNF expression in the injured spinal cord.

The combined effect of epidermal growth factor and keratinocyte growth factor delivered by hyaluronic acid hydrogel on corneal wound healing.

This study strategically incorporates epidermal growth factor (EGF) and keratinocyte growth factor (KGF) within a hyaluronic acid (HA) hydrogel to enhance corneal wound healing. The controlled release of EGF and KGF from the HA hydrogel is engineered to promote the regeneration of both the epithelial and stromal layers. Specifically, EGF plays a pivotal role in the regeneration of the epithelial layer, while KGF exhibits efficacy in the regeneration of the stromal layer. The combination of these growth factors facilitates efficient regeneration of each layer and demonstrates the capability to modulate each other's regenerative effects. The interplay between EGF and KGF provides an understanding of their cooperative influence on the dynamics of corneal wound healing. The results of this study contribute to the development of advanced strategies for corneal wound management and offer insights into the complex process of corneal regeneration.

Nanostructured Substrate-Mediated Bubble Degassing in Microfluidic Systems.

Microfluidic platforms have been widely used in a variety of fields owing to their numerous advantages. The prevention and prompt removal of air bubbles from microchannels are important to ensuring the optimal functioning of microfluidic devices. The entrapment of bubbles in the microchannels can result in flow instability and device performance disruption. Active and passive methods are the primary categories of degassing technologies. Active methods rely on external equipment, and passive methods operate autonomously without any external sources. This study proposed a passive degassing method that employs a nanoscale surface morphology integrated into the substrate of a microfluidic device. Nanostructures exhibit a microchannel geometry and are fabricated based on surface micromachining technology using silver ink and chemical etching. Consequently, the gas permeability is enhanced, resulting in effective degassing through the nanostructure. The performance of this degassing method was characterized under varying substrate permeabilities and input pressure conditions, and it was found that increased permeability facilitates the degassing performance. Furthermore, the applicability of our method was demonstrated by using a serpentine channel design prone to gas entrapment, particularly in the corner regions. The nanostructured substrate exhibited significantly improved degassing performance under the given pressure conditions in comparison to the glass substrate.

Effective Prediction of Concrete Constitutive Models for Reinforced Concrete Shear Walls under Cyclic Loading.

One of the most challenging elements of modeling the behaviour of reinforced concrete (RC) walls is combining realistic material models that can capture the observable behaviour of the physical system. Experiments with realistic loading rates and pressures reveal that steel and concrete display complicated nonlinear behaviour that is challenging to represent in a single constitutive model. To investigate the response of a reinforced concrete structure subjected to dynamic loads, this paper's study is based on many different material models to assess the advantages and disadvantages of the models on 2D and 3D RC walls using the LS-DYNA program. The models consisted of the KCC model and the CDP model, which represented plasticity and distinct tensile/compressive damage models, and the Winfrith model, which represented plasticity and the smeared crack model. Subsequently, the models' performances were assessed by comparing them to experimental data from reinforced concrete structures, in order to validate the accuracy of the overall behaviour prediction. The Winfrith model demonstrated satisfactory results in predicting the behaviour of 2D and 3D walls, including maximum strength, stiffness deterioration, and energy dissipation. The method accurately predicted the maximum strength of the Winfrith concrete model for the 2D wall with an error of 9.24% and for the 3D wall with errors of 3.28% in the X direction and 5.02% in the Y direction. The Winfrith model demonstrated higher precision in predicting dissipation energy for the 3D wall in both the X and Y directions, with errors of 6.84% and 6.62%, correspondingly. Additional parametric analyses were carried out to investigate structural behaviour, taking into account variables such as concrete strength, strain rate, mesh size, and the influence of the element type.

Simultaneous, cortex-wide dynamics of up to 1 million neurons reveal unbounded scaling of dimensionality with neuron number.

The brain's remarkable properties arise from the collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, can such low-dimensional representations truly explain the vast range of brain activity, and if not, what is the appropriate resolution and scale of recording to capture them? Imaging neural activity at cellular resolution and near-simultaneously across the mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number in populations up to 1 million neurons. Although half of the neural variance is contained within sixteen dimensions correlated with behavior, our discovered scaling of dimensionality corresponds to an ever-increasing number of neuronal ensembles without immediate behavioral or sensory correlates. The activity patterns underlying these higher dimensions are fine grained and cortex wide, highlighting that large-scale, cellular-resolution recording is required to uncover the full substrates of neuronal computations.

Association between depression, antidepressant use, and the incidence of atherosclerotic cardiovascular diseases.

OBJECTIVE: To examine the association between depression, the use of antidepressants, and atherosclerotic cardiovascular disease (ASCVD). METHODS: The South Korean national claims data was used. Among a nationally representative population, 273,656 subjects who had been diagnosed with depression and prescribed antidepressants ("DEP with antidepressants") and 78,851 subjects who had been diagnosed with depression but not prescribed antidepressants ("DEP without antidepressants") were identified to be eligible. Healthy controls (HCs) were 1:1 matched with DEP with antidepressants group for age and sex. We followed up on the occurrence of ASCVD including ischemic heart diseases and ischemic stroke. RESULTS: The risk of ASCVD was increased in the DEP with antidepressants group and decreased in the DEP without antidepressants group compared to HCs. Among those under antidepressants, tricyclic antidepressant users showed the highest risk of ASCVD compared to HCs. Among young adults, the risk of ASCVD was increased in both groups. CONCLUSION: The risk of ASCVD increased in depression patients taking antidepressants, while it decreased in depression patients not taking antidepressants. However, the relationship showed differences according to drug class and age group.

Bipolar disorder and the risk of cardiometabolic diseases, heart failure, and all-cause mortality: a population-based matched cohort study in South Korea.

The association of bipolar disorder (BD) with the risk of cardiometabolic diseases and premature death in Asians needs to be further determined. Relatively less attention has been paid to heart failure (HF) among cardiometabolic outcomes. We analyzed the Korean National Health Insurance Service database (2002-2018) for this population-based, matched cohort study. The hazards of ischemic stroke, ischemic heart disease (IHD), hospitalization for HF (hHF), composite cardiometabolic diseases, and all-cause mortality during follow-up were compared between individuals with BD (n = 11,329) and 1:1-matched controls without psychiatric disorders among adults without cardiometabolic disease before or within 3 months of baseline. Hazards of outcomes were higher in individuals with BD than in matched controls (adjusted hazard ratios [95% confidence intervals]: 1.971 [1.414-2.746] for ischemic stroke, 1.553 [1.401-1.721] for IHD, 2.526 [1.788-3.567] for hHF, 1.939 [1.860-2.022] for composite cardiometabolic diseases, and 2.175 [1.875-2.523] for all-cause mortality) during follow-up. Associations between BD and outcome hazards were more prominent in younger individuals (p for interaction < 0.02, except for ischemic stroke) and women (p for interaction < 0.04, except for hHF). Screening and preventive measures for cardiometabolic deterioration and early mortality may need to be intensified in individuals with BD, even in young adults, especially women.

- Invited Review - Hydrogen production and hydrogen utilization in the rumen: key to mitigating enteric methane production.

Molecular hydrogen (H2) and formate (HCOO-) are metabolic end products of many primary fermenters in the rumen ecosystem. Both play a vital role in fermentation where they are electron sinks for individual microbes in an anaerobic environment that lacks external electron acceptors. If H2 and/or formate accumulate within the rumen, the ability of primary fermenters to regenerate electron carriers may be inhibited and microbial metabolism and growth disrupted. Consequently, H2- and/or formate-consuming microbes such as methanogens and possibly homoacetogens play a key role in maintaining the metabolic efficiency of primary fermenters. There is increasing interest in identifying approaches to manipulate the rumen ecosystem for the benefit of the host and the environment. As H2 and formate are important mediators of interspecies interactions, an understanding of their production and utilization could be a significant starting point for the development of successful interventions aimed at redirecting electron flow and reducing methane emissions. We conclude by discussing in brief ruminant methane mitigation approaches as a model to help understand the fate of H2 and formate in the rumen ecosystem.

Psychotic Disorders and the Risk of Type 2 Diabetes Mellitus, Atherosclerotic Cardiovascular Diseases, and All-Cause Mortality: A Population-Based Matched Cohort Study.

BACKGRUOUND: The effects of psychotic disorders on cardiometabolic diseases and premature death need to be determined in Asian populations. METHODS: In this population-based matched cohort study, the Korean National Health Insurance Service database (2002 to 2018) was used. The risk of type 2 diabetes mellitus (T2DM), acute myocardial infarction (AMI), ischemic stroke, composite of all cardiometabolic diseases, and all-cause death during follow-up was compared between individuals with psychotic disorders treated with antipsychotics (n=48,162) and 1:1 matched controls without psychiatric disorders among adults without cardiometabolic diseases before or within 3 months after baseline. RESULTS: In this cohort, 53,683 composite cases of all cardiometabolic diseases (during median 7.38 years), 899 AMI, and 1,216 ischemic stroke cases (during median 14.14 years), 7,686 T2DM cases (during median 13.26 years), and 7,092 deaths (during median 14.23 years) occurred. The risk of all outcomes was higher in subjects with psychotic disorders than matched controls (adjusted hazard ratios [95% confidence intervals]: 1.522 [1.446 to 1.602] for T2DM; 1.455 [1.251 to 1.693] for AMI; 1.568 [1.373 to 1.790] for ischemic stroke; 1.595 [1.565 to 1.626] for composite of all cardiometabolic diseases; and 2.747 [2.599 to 2.904] for all-cause mortality) during follow-up. Similar patterns of associations were maintained in subgroup analyses but more prominent in younger individuals (P for interaction <0.0001) when categorized as those aged 18-39, 40-64, or ≥65 years. CONCLUSION: Patients with psychotic disorders treated with antipsychotics were associated with increased risk of premature allcause mortality and cardiometabolic outcomes in an Asian population. This relationship was more pronounced in younger individuals, especially aged 18 to 39 years.

Weight change in people with depression and the risk of dementia: a nationwide cohort study.

BACKGROUND: Depression is a risk factor for dementia and weight change can appear as a symptom of depression. However, the association between weight change after the diagnosis of depression and the risk of dementia is poorly established. This study aimed to investigate the association between weight change before and after a diagnosis of depression with the subsequent risk of dementia. METHODS: The National Health Insurance Sharing Service database was used. 1 308 730 patients aged ⩾40 years diagnosed with depression were identified to be eligible. Weight changes after their depression diagnosis were categorized and subsequent incidence of dementia was followed up. RESULTS: During an average follow-up period of 5.2 years (s.d., 2.0 years), 69 373 subjects were newly diagnosed with all-cause dementia (56 351 were Alzheimer's disease and 6877 were vascular dementia). Regarding all outcomes, compared to those with a minimal weight change (-5 to 5%), all groups with weight gain or loss showed increased risks of dementia after adjusting potential risk factors for dementia, in all analysis models with a dose-response relationship, showing a U-shaped association. CONCLUSIONS: Weight change as a symptom of depression could be a predictor for the future development of dementia.

Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number.

The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.

Analysis of PM2.5 inorganic and organic constituents to resolve contributing sources in Seoul, South Korea and Beijing, China and their possible associations with cytokine IL-8.

China and South Korea are the most polluted countries in East Asia due to significant urbanization and extensive industrial activities. As neighboring countries, collaborative management plans to maximize public health in both countries can be helpful in reducing transboundary air pollution. To support such planning, PM2.5 inorganic and organic species were determined in simultaneously collected PM2.5 integrated filters. The resulting data were used as inputs to positive matrix factorization, which identified nine sources at the ambient air monitoring sites in both sites. Secondary nitrate, secondary sulfate/oil combustion, soil, mobile, incinerator, biomass burning, and secondary organic carbon (SOC) were found to be sources at both sampling sites. Industry I and II were only identified in Seoul, whereas combustion and road dust sources were only identified in Beijing. A subset of samples was selected for exposure assessment. The expression levels of IL-8 were significantly higher in Beijing (167.7 pg/mL) than in Seoul (72.7 pg/mL). The associations between the PM2.5 chemical constituents and its contributing sources with PM2.5-induced inflammatory cytokine (interleukin-8, IL-8) levels in human bronchial epithelial cells were investigated. For Seoul, the soil followed by the secondary nitrate and the biomass burning showed increase with IL-8 production. However, for the Beijing, the secondary nitrate exhibited the highest association with IL-8 production and SOC and biomass burning showed modest increase with IL-8. As one of the highest contributing sources in both cities, secondary nitrate showed an association with IL-8 production. The soil source having the strongest association with IL-8 production was found only for Seoul, whereas SOC showed a modest association only for Beijing. This study can provide the scientific basis for identifying the sources to be prioritized for control to provide effective mitigation of particulate air pollution in each city and thereby improve public health.

Changes in physical activity and the risk of heart failure in newly diagnosed patients with depression: A nationwide cohort study.

BACKGROUND: Depression is known to increase the risk of heart failure (HF), and physical activity could be a potential mediator of their linkage. In this study, we examined the risk of incident HF according to changes in the level of physical activity before and after the diagnosis of depression. METHODS: A South Korean National Health Insurance Sharing Service database was used. A total of 1,405,655 patients with newly diagnosed depression were included in the analyses. According to the changes in physical activity based on the recommended level of regular physical activity, participants were divided into four groups: never, beginning, maintenance, and discontinuation. The main outcome was the occurrence of HF. RESULTS: During the average follow-up period of 5.28 years (SD, 2.00 years), 69,338 participants were diagnosed with HF, with an incidence rate of 9.34 per 1000 person-years. Compared to the never group, the beginning group showed a decreased risk of HF (aHR, 0.88; 95% CI, 0.86-0.90). Compared to the maintenance group, the discontinuation group showed an increased risk of HF (aHR, 1.16; 95% CI, 1.11-1.20). CONCLUSIONS: In the patients with depression, beginning regular physical activity was associated with a decreased risk of HF, and discontinuing regular physical activity was associated with an increased risk.

Depression, antidepressant use, and the risk of type 2 diabetes: a nationally representative cohort study.

Background: Previous studies have reported that depression can increase the risk of type 2 diabetes. However, they did not sufficiently consider antidepressants or comorbidity. Methods: The National Health Insurance Sharing Service database was used. Among the sample population, 276,048 subjects who had been diagnosed with depression and prescribed antidepressants (DEP with antidepressants group) and 79,119 subjects who had been diagnosed with depression but not prescribed antidepressants (DEP without antidepressants group) were found to be eligible for this study. Healthy controls (HCs) were 1:1 matched with the DEP with antidepressants group for age and sex. We followed up with them for the occurrence of type 2 diabetes. Results: In the group of DEP with antidepressants, although the risk of type 2 diabetes increased compared to HCs in a crude analysis, it decreased when comorbidity was adjusted for. In the group of DEP without antidepressants, the risk of type 2 diabetes decreased both in the crude model and the adjusted models. The risk varied by age group and classes or ingredients of antidepressants, with young adult patients showing an increased risk even in the fully adjusted model. Conclusion: Overall, those with depression had a reduced risk of type 2 diabetes. However, the risk varied according to the age at onset, comorbidity, and type of antidepressants.