The microglial innate immune protein PGLYRP1 mediates neuroinflammation and consequent behavioral changes.

Peptidoglycan recognition protein 1 (PGLYRP1) is a pattern-recognition protein that mediates antibacterial actions and innate immune responses. Its expression and role in neuroinflammatory conditions remain unclear. We observed the upregulation of PGLYRP1 in inflamed human and mouse spinal cord and brain, with microglia being the primary cellular source. Experiments using a recombinant PGLYRP1 protein show that PGLYRP1 potentiates reactive gliosis, neuroinflammation, and consequent behavioral changes in multiple animal models of neuroinflammation. Furthermore, shRNA-mediated knockdown of Pglyrp1 gene expression attenuates this inflammatory response. In addition, we identify triggering receptor expressed on myeloid cell-1 (TREM1) as an interaction partner of PGLYRP1 and demonstrate that PGLYRP1 promotes neuroinflammation through the TREM1-Syk-Erk1/2-Stat3 axis in cultured glial cells. Taken together, our results reveal a role for microglial PGLYRP1 as a neuroinflammation mediator. Finally, we propose that PGLYRP1 is a potential biomarker and therapeutic target in various neuroinflammatory diseases.

Allele-specific control of rodent and human lncRNA KMT2E-AS1 promotes hypoxic endothelial pathology in pulmonary hypertension.

Hypoxic reprogramming of vasculature relies on genetic, epigenetic, and metabolic circuitry, but the control points are unknown. In pulmonary arterial hypertension (PAH), a disease driven by hypoxia inducible factor (HIF)-dependent vascular dysfunction, HIF-2α promoted expression of neighboring genes, long noncoding RNA (lncRNA) histone lysine N-methyltransferase 2E-antisense 1 (KMT2E-AS1) and histone lysine N-methyltransferase 2E (KMT2E). KMT2E-AS1 stabilized KMT2E protein to increase epigenetic histone 3 lysine 4 trimethylation (H3K4me3), driving HIF-2α-dependent metabolic and pathogenic endothelial activity. This lncRNA axis also increased HIF-2α expression across epigenetic, transcriptional, and posttranscriptional contexts, thus promoting a positive feedback loop to further augment HIF-2α activity. We identified a genetic association between rs73184087, a single-nucleotide variant (SNV) within a KMT2E intron, and disease risk in PAH discovery and replication patient cohorts and in a global meta-analysis. This SNV displayed allele (G)-specific association with HIF-2α, engaged in long-range chromatin interactions, and induced the lncRNA-KMT2E tandem in hypoxic (G/G) cells. In vivo, KMT2E-AS1 deficiency protected against PAH in mice, as did pharmacologic inhibition of histone methylation in rats. Conversely, forced lncRNA expression promoted more severe PH. Thus, the KMT2E-AS1/KMT2E pair orchestrates across convergent multi-ome landscapes to mediate HIF-2α pathobiology and represents a key clinical target in pulmonary hypertension.

Incidence and outcomes of intraoperative periprosthetic acetabular fractures during cementless total hip arthroplasty: a prospective three-dimensional computer tomography-based study.

PURPOSE: Unlike periprosthetic femoral fractures, periprosthetic acetabular fractures during total hip arthroplasty (THA) have not been evaluated in detail. We prospectively evaluated the incidence, patterns, risk factors, and clinical outcomes of intraoperative periprosthetic acetabular fractures using pre- and postoperative computer tomography (CT). METHODS: In this prospective single-centre study, we evaluated 234 consecutive patients (250 hips) who underwent THA and three-dimensional CT before and after the surgery. We assessed the incidence, pattern of fractures, outcomes for each fracture pattern, reoperation and revision rates, Harris hip score, and visual analog scale (VAS) for pain. Multivariate regression models were used to identify risk factors for periprosthetic acetabular fractures. RESULTS: In total, 43 periprosthetic acetabular fractures (17.2%) were identified via CT. Fractures occurred most frequently at the superolateral wall. Early cup migration occurred in three hips. None of the patients underwent revision surgery for acetabular loosening. Regression modeling showed that rheumatoid arthritis was a significant predictor of periprosthetic acetabular fractures. CONCLUSIONS: Periprosthetic acetabular fractures are not infrequent during cementless THA and are more common in patients with rheumatoid arthritis.

Shape phenotype of thigh fat and muscle and risk of major adverse cardiovascular events after fragility hip fracture.

BACKGROUND: Although sarcopenia has been recognized as a predictor of mortality in elderly patients with hip fracture, the association of thigh fat and muscle with cardiovascular (CV) outcome remains unclear. We examined the impact of computed tomography (CT)-derived shape features of thigh fat and muscle on major adverse CV events (MACE) in elderly patients with hip fracture. METHODS: We conducted a retrospective analysis of consecutive patients aged ≥65 years who presented with hip fracture confirmed on pelvic bone CT scan and underwent hip fracture surgery at our institution from April 2019 to December 2021. The cross-sectional area (CSA) and compactness (CM) of both the muscle and fat at the upper-thigh level were calculated from two-dimensional CT images using AVIEW Research (v1.1.38, Coreline Soft, Co. Ltd, Seoul, South Korea). The shape features of thigh fat and muscle were categorized into four groups based on the combination of CSA and CM: fat CSA (fat area [FA])/fat CM (FCM), muscle CSA (muscle area [MA])/muscle CM (MCM), FA/MCM and MA/FCM. In each of them, subjects were categorized into four subgroups: high CSA/high CM, high CSA/low CM, low CSA/high CM and low CSA/low CM. The primary outcome was MACE after 30 days of surgery, defined as a composite of all-cause death, acute myocardial infarction, stroke or hospitalization for heart failure. RESULTS: Of 356 patients enrolled (median age, 82 years; 76.7% females), 72 (20.2%) had MACE over a median follow-up of 13.1 months (ranges 5.9-21.0 months). Patients with MACE had a significantly lower median FA (193.7 vs. 226.2 cm2 , P < 0.0001) and FCM (0.443 vs. 0.513, P = 0.001) compared with those without MACE, but no significant differences were found in MA, MCM and FA-MA ratio between the two groups. In a multivariate Cox regression analysis, low FA (<240.1 cm2 ) (adjusted hazard ratio [HR] 2.99, 95% confidence interval [CI] 1.39-6.44, P = 0.005) and low FCM (<0.477) (adjusted HR 2.00, 95% CI 1.10-3.63, P = 0.023) were associated with an increased risk of MACE. Among the shape phenotypes of thigh fat and muscle, the thigh fat phenotype of low FA/low FCM (adjusted HR 3.13, 95% CI 1.81-5.42, P < 0.0001 [reference, high FA/high FCM]) was found to be an independent predictor of MACE. CONCLUSIONS: In elderly patients with fragility hip fracture, thigh CT-derived measures of FA and FCM may provide useful prognostic information for predicting adverse CV outcomes.

Identification of Lineage-specific Transcriptional Factor-defined Molecular Subtypes in Small Cell Bladder Cancer.

Small cell/neuroendocrine bladder cancers (SCBCs) are rare and highly aggressive tumors that are associated with poor clinical outcomes. We discovered that lineage-specific transcription factors (ASCL1, NEUROD1, and POU2F3) defined three SCBC molecular subtypes that resemble well-characterized subtypes in small cell lung cancer. The subtypes expressed various levels of neuroendocrine (NE) markers and distinct downstream transcriptional targets. Specifically, the ASCL1 and NEUROD1 subtypes had high NE marker expression and were enriched with different downstream regulators of the NE phenotype (FOXA2 and HES6, respectively). ASCL1 was also associated with the expression of delta-like ligands that control oncogenic Notch signaling. POU2F3, a master regulator of the NE low subtype, targeted TRPM5, SOX9, and CHAT. We also observed an inverse association between NE marker expression and immune signatures associated with sensitivity to immune checkpoint blockade, and the ASCL1 subtype had distinct targets for clinically available antibody-drug conjugates. These findings provide new insight into molecular heterogeneity in SCBCs with implications for the development of new treatment regimens. PATIENT SUMMARY: We investigated the levels of different proteins in a specific type of bladder cancer (small cell/neuroendocrine; SCBC). We could identify three distinct subtypes of SCBC with similarity to small cell/neuroendocrine cancers in other tissues. The results may help in identifying new treatment approaches for this type of bladder cancer.

Fine-Grained Motion Recognition in At-Home Fitness Monitoring with Smartwatch: A Comparative Analysis of Explainable Deep Neural Networks.

The squat is a multi-joint exercise widely used for everyday at-home fitness. Focusing on the fine-grained classification of squat motions, we propose a smartwatch-based wearable system that can recognize subtle motion differences. For data collection, 52 participants were asked to perform one correct squat and five incorrect squats with three different arm postures (straight arm, crossed arm, and hands on waist). We utilized deep neural network-based models and adopted a conventional machine learning method (random forest) as a baseline. Experimental results revealed that the bidirectional GRU/LSTMs with an attention mechanism and the arm posture of hands on waist achieved the best test accuracy (F1-score) of 0.854 (0.856). High-dimensional embeddings in the latent space learned by attention-based models exhibit more clustered distributions than those by other DNN models, indicating that attention-based models learned features from the complex multivariate time-series motion signals more efficiently. To understand the underlying decision-making process of the machine-learning system, we analyzed the result of attention-based RNN models. The bidirectional GRU/LSTMs show a consistent pattern of attention for defined squat classes, but these models weigh the attention to the different kinematic events of the squat motion (e.g., descending and ascending). However, there was no significant difference found in classification performance.

Robotic Kinesthesia: Estimating Object Geometry and Material With Robot's Haptic Senses.

Humans excel at determining the shape and material of objects through touch. Drawing inspiration from this ability, we propose a robotic system that incorporates haptic sensing capability into its artificial recognition system to jointly learn the shape and material types of an object. To achieve this, we employ a serially connected robotic arm and develop a supervised learning task that learns and classifies target surface geometry and material types using multivariate time-series data from joint torque sensors. Additionally, we propose a joint torque-to-position generation task to derive a one-dimensional surface profile based on torque measurements. Experimental results successfully validate the proposed torque-based classification and regression tasks, suggesting that a robotic system can employ haptic sensing (i.e., perceived force) from each joint to recognize material types and geometry, akin to human abilities.

The incidence of focal osteonecrosis of the femoral head and its impact on conversion hip arthroplasty after screw fixation of femoral neck fractures: a multicenter retrospective study based on postoperative magnetic resonance imaging.

PURPOSE: Osteonecrosis of the femoral head (ONFH) and subsequent head collapse is a major concern after internal fixation of femoral neck fracture (FNF). Previous studies focused on ONFH incidence using plain radiography; postoperative magnetic resonance imaging (MRI) was rarely performed. We performed a multicenter retrospective study to investigate the incidence of ONFH and the need for conversion hip arthroplasty after FNF screw fixation. METHODS: We reviewed 195 patients who underwent screw fixation during closed FNF reduction between 2012 and 2017 at three institutions. Except for patients who did not consent to MRI, all patients underwent postoperative MRI either 1-3 years after screw fixation. The occurrence of ONFH was investigated through plain radiography and MRI. RESULTS: Thirty patients were diagnosed with ONFH through plain radiography, and an additional 33 patients were diagnosed with MRI, resulting in a total of 63 patients (32.3%) diagnosed with ONFH. The mean time to ONFH diagnosis was 18.9 months and the conversion rate to hip arthroplasty was 10.2%. Of the 33 patients who were normal on hip radiography but exhibited ONFH on MRI, all had small focal lesions not associated with head collapse at the last follow-up. The ONFH group diagnosed through plain radiography had more unstable FNFs than the group diagnosed through MRI. CONCLUSION: Although postoperative MRI revealed a higher incidence of ONFH after FNF screw fixation than reported previously, the small focal MRI lesions were not associated with increased risks of femoral head collapse or conversion to arthroplasty.

Anonymizing at-home fitness: enhancing privacy and motivation with virtual reality and try-on.

Introduction: This study aimed to address privacy concerns associated with video conferencing tools used in home-based exercise training. To that end, a method that could anonymize participants' appearances and exercise environments during at-home fitness sessions was proposed. Methods: This method combines virtual reality for 3-D human-model rendering using key-points tracking with a virtual try-on system enhanced by UV mapping and instance segmentation. To validate the proposed method, we conducted a user study by recruiting participants to assess effectiveness of virtual reality and virtual try-on in terms of privacy protection, self-confidence, and coaching satisfaction. Results: Experimental results demonstrated the effectiveness and improved user experience of using virtual reality or virtual try-on in remote fitness, particularly in enhancing privacy protection and self-confidence with statistical significance. However, no significant differences were noted in coaching satisfaction. Discussion: These findings confirmed the efficacy of our proposed approach. We believe that the proposed approach can significantly contribute to the future of remote fitness training, offering a more secure and engaging environment for users, thereby potentially increasing adherence to fitness regimens and overall physical wellbeing.

Caspase-dependent apoptosis induces reactivation and gliogenesis of astrocytes in adult mice.

Astrocytes play an important role in increasing synaptic plasticity, regulating endogenous homeostasis, and contributing to neuroprotection but become overactivated or apoptotic in persistent neuroinflammatory responses or pathological conditions. Although gliogenesis under these conditions may be essential for neuronal protection, much remains unknown. Here, we generated new conditional transgenic mice (cTg) that can induce apoptosis via Cre-dependent active caspase-3 (taCasp3-2A-TEVp) without pathological conditions. We induced apoptosis of hippocampal CA1 astrocytes in cTg mice using GFAP promoter-driven adeno-associated virus (AAV) containing Cre recombinase. Activated caspase-3 was detected in astrocytes of the hippocampal CA1, and the number of astrocytes decreased sharply at 1 week but recovered at 2 weeks and was maintained until 4 weeks. Nuclear factor 1A (NF1A) mRNA, an important transcription factor for hippocampal reactive astrocytes, was significantly increased only at week 1. Interestingly, all reactive markers (pan, A1, A2) increased despite the decreased number of astrocytes at week 1, and there was no change in monoamine oxidase B (MAOB) observed in astrocytes of animal models of degenerative brain disease. Extensive CA1 astrocyte depletion at week 1 induced cognitive deficits; however, both recovered at weeks 2 and 4. Overall, transient hippocampal astrocyte depletion caused by apoptosis restored cell number and function within 2 weeks and did not induce significant neurotoxicity. Therefore, cTg mice are valuable as an in vivo animal model for studying gliogenesis in multiple regions of the adult brain.

Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Imaging tests such as chest X-ray (CXR) and computed tomography (CT) can provide useful information to clinical staff for facilitating a diagnosis of COVID-19 in a more efficient and comprehensive manner. As a breakthrough of artificial intelligence (AI), deep learning has been applied to perform COVID-19 infection region segmentation and disease classification by analyzing CXR and CT data. However, prediction uncertainty of deep learning models for these tasks, which is very important to safety-critical applications like medical image processing, has not been comprehensively investigated. In this work, we propose a novel ensemble deep learning model through integrating bagging deep learning and model calibration to not only enhance segmentation performance, but also reduce prediction uncertainty. The proposed method has been validated on a large dataset that is associated with CXR image segmentation. Experimental results demonstrate that the proposed method can improve the segmentation performance, as well as decrease prediction uncertainty.

O-GlcNAcylation suppresses TRAP1 activity and promotes mitochondrial respiration.

The molecular chaperone TNF-receptor-associated protein-1 (TRAP1) controls mitochondrial respiration through regulation of Krebs cycle and electron transport chain activity. Post-translational modification (PTM) of TRAP1 regulates its activity, thereby controlling global metabolic flux. O-GlcNAcylation is one PTM that is known to impact mitochondrial metabolism, however the major effectors of this regulatory PTM remain inadequately resolved. Here we demonstrate that TRAP1-O-GlcNAcylation decreases TRAP1 ATPase activity, leading to increased mitochondrial metabolism. O-GlcNAcylation of TRAP1 occurs following mitochondrial import and provides critical regulatory feedback, as the impact of O-GlcNAcylation on mitochondrial metabolism shows TRAP1-dependence. Mechanistically, loss of TRAP1-O-GlcNAcylation decreased TRAP1 binding to ATP, and interaction with its client protein succinate dehydrogenase (SDHB). Taken together, TRAP1-O-GlcNAcylation serves to regulate mitochondrial metabolism by the reversible attenuation of TRAP1 chaperone activity.

An Exosome-based Transcriptomic Signature for Noninvasive, Early Detection of Patients With Pancreatic Ductal Adenocarcinoma: A Multicenter Cohort Study.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) incidence is rising worldwide, and most patients present with an unresectable disease at initial diagnosis. Measurement of carbohydrate antigen 19-9 (CA19-9) levels lacks adequate sensitivity and specificity for early detection; hence, there is an unmet need to develop alternate molecular diagnostic biomarkers for PDAC. Emerging evidence suggests that tumor-derived exosomal cargo, particularly micro RNAs (miRNAs), offer an attractive platform for the development of cancer-specific biomarkers. Herein, genomewide profiling in blood specimens was performed to develop an exosome-based transcriptomic signature for noninvasive and early detection of PDAC. METHODS: Small RNA sequencing was undertaken in a cohort of 44 patients with an early-stage PDAC and 57 nondisease controls. Using machine-learning algorithms, a panel of cell-free (cf) and exosomal (exo) miRNAs were prioritized that discriminated patients with PDAC from control subjects. Subsequently, the performance of the biomarkers was trained and validated in independent cohorts (n = 191) using quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays. RESULTS: The sequencing analysis initially identified a panel of 30 overexpressed miRNAs in PDAC. Subsequently using qRT-PCR assays, the panel was reduced to 13 markers (5 cf- and 8 exo-miRNAs), which successfully identified patients with all stages of PDAC (area under the curve [AUC] = 0.98 training cohort; AUC = 0.93 validation cohort); but more importantly, was equally robust for the identification of early-stage PDAC (stages I and II; AUC = 0.93). Furthermore, this transcriptomic signature successfully identified CA19-9 negative cases (<37 U/mL; AUC = 0.96), when analyzed in combination with CA19-9 levels, significantly improved the overall diagnostic accuracy (AUC = 0.99 vs AUC = 0.86 for CA19-9 alone). CONCLUSIONS: In this study, an exosome-based liquid biopsy signature for the noninvasive and robust detection of patients with PDAC was developed.

Cathelicidin-related antimicrobial peptide promotes neuroinflammation through astrocyte-microglia communication in experimental autoimmune encephalomyelitis.

Cathelicidin-related antimicrobial peptide (CRAMP) is an effector molecule of the innate immune system with direct antimicrobial and immunomodulatory activities; however, its role in neuroinflammatory responses and related diseases is not clearly understood. In particular, the expression of CRAMP and its functional role has not been previously studied in experimental autoimmune encephalomyelitis (EAE) or multiple sclerosis (MS). Here, we investigated the role of CRAMP in neuroinflammation, using an EAE mouse model of MS and postmortem patient tissues. We found that the CRAMP expression was increased in the spinal cords of EAE-induced mice. Immunofluorescence analysis revealed that CRAMP is mainly induced in reactive astrocytes in the inflamed spinal cord of EAE mice. A similar pattern of the LL-37 (human CRAMP) expression was observed in the brain and spinal cord tissues of patients with MS. An intrathecal injection of the CRAMP peptide in EAE mice accelerated the onset of symptoms and increased disease severity with augmented expression of inflammatory mediators, glial activation, infiltration of inflammatory cells, and demyelination. In addition, shRNA-mediated knockdown of Cramp in the spinal cord resulted in a milder disease course with less inflammation in EAE mice. We identified FPR2 on microglia as a CRAMP receptor and demonstrated that CRAMP potentiates IFN-γ-induced microglial activation via the STAT3 pathway. Taken together, our findings suggest that CRAMP is a novel mediator of astrocyte-microglia interactions in neuroinflammatory conditions such as EAE. Thus, CRAMP could be exploited as a biomarker or therapeutic target for the diagnosis or treatment of MS.

The Association between Menstrual Irregularities and the Risk of Diabetes in Premenopausal and Postmenopausal Women: A Cross-Sectional Study of a Nationally Representative Sample.

BACKGROUND: Studies have assessed the effects of menstrual irregularities and menopause on diabetes, but no definitive conclusion has been reached. This study investigated for the first time the relationship between menstrual irregularity and diabetes before and after menopause. METHODS: This population-based cross-sectional study included 9043 participants from the Korea National Health and Nutrition Examination Survey (KNHANES) V (2010-2012). Multivariate logistic regression was used to assess the effect of menstrual irregularities on impaired fasting glucose (IFG) and diabetes incidence in women before and after menopause. RESULTS: After adjustment for age and other diabetes-related factors, both menopause (OR = 1.51, 95% CI = 1.101-2.27, p = 0.047) and menstrual irregularities (OR = 1.51, 95% CI = 1.1-2.07, p = 0.011) were found to increase the risk of diabetes. Menstrual irregularities were significantly related to diabetes in the postmenopausal group (OR = 1.65, 95% CI = 1.12-2.42, p = 0.012) but not in the premenopausal group (OR = 1.22, 95% CI = 0.64-2.32, p = 0.555). CONCLUSIONS: In this study, menopausal status appeared to independently affect diabetes risk; menstrual irregularities were found to be a risk factor for postmenopausal diabetes. This study emphasizes the need for monitoring and early prevention, along with medical advice on menstrual irregularities, to reduce the prevalence of diabetes and improve the quality of life of postmenopausal women.

iApp: An Autonomous Inspection, Auscultation, Percussion, and Palpation Platform.

Disease symptoms often contain features that are not routinely recognized by patients but can be identified through indirect inspection or diagnosis by medical professionals. Telemedicine requires sufficient information for aiding doctors' diagnosis, and it has been primarily achieved by clinical decision support systems (CDSSs) utilizing visual information. However, additional medical diagnostic tools are needed for improving CDSSs. Moreover, since the COVID-19 pandemic, telemedicine has garnered increasing attention, and basic diagnostic tools (e.g., classical examination) have become the most important components of a comprehensive framework. This study proposes a conceptual system, iApp, that can collect and analyze quantified data based on an automatically performed inspection, auscultation, percussion, and palpation. The proposed iApp system consists of an auscultation sensor, camera for inspection, and custom-built hardware for automatic percussion and palpation. Experiments were designed to categorize the eight abdominal divisions of healthy subjects based on the system multi-modal data. A deep multi-modal learning model, yielding a single prediction from multi-modal inputs, was designed for learning distinctive features in eight abdominal divisions. The model's performance was evaluated in terms of the classification accuracy, sensitivity, positive predictive value, and F-measure, using epoch-wise and subject-wise methods. The results demonstrate that the iApp system can successfully categorize abdominal divisions, with the test accuracy of 89.46%. Through an automatic examination of the iApp system, this proof-of-concept study demonstrates a sophisticated classification by extracting distinct features of different abdominal divisions where different organs are located. In the future, we intend to capture the distinct features between normal and abnormal tissues while securing patient data and demonstrate the feasibility of a fully telediagnostic system that can support abnormality diagnosis.

Estimation of Fine-Grained Foot Strike Patterns with Wearable Smartwatch Devices.

People who exercise may benefit or be injured depending on their foot striking (FS) style. In this study, we propose an intelligent system that can recognize subtle differences in FS patterns while walking and running using measurements from a wearable smartwatch device. Although such patterns could be directly measured utilizing pressure distribution of feet while striking on the ground, we instead focused on analyzing hand movements by assuming that striking patterns consequently affect temporal movements of the whole body. The advantage of the proposed approach is that FS patterns can be estimated in a portable and less invasive manner. To this end, first, we developed a wearable system for measuring inertial movements of hands and then conducted an experiment where participants were asked to walk and run while wearing a smartwatch. Second, we trained and tested the captured multivariate time series signals in supervised learning settings. The experimental results obtained demonstrated high and robust classification performances (weighted-average F1 score > 90%) when recent deep neural network models, such as 1D-CNN and GRUs, were employed. We conclude this study with a discussion of potential future work and applications that increase benefits while walking and running properly using the proposed approach.

Improved AAV vector system for cell-type-specific RNA interference.

BACKGROUND: RNA interference (RNAi) is a powerful technique to effectively silence or knock down gene function in mammalian cells. For better cell-type RNAi experiments in vivo, AAV vector-based RNA interference systems need to be improved. New method: In this study, we developed an AAV vector (CREon shRNA) that expressed CRE-dependent short hairpin RNA (shRNA) and fluorescent proteins simultaneously. RESULTS: We verified the Cre-dependent knockdown efficiency of the newly developed CREon shRNA vector in both HEK293T cells overexpressing TREK-1 and PC3 cells with endogenous TREK-1. Next, we packaged this TREK-1 CREon vector with AAV and injected it into the hippocampus of the brain together with a synapsin or GFAP promoter-driven CRE virus, confirming that it works well cell-selectively even in vivo. Finally, this viral vector was applied to an animal model of LPS-induced depression to determine whether behavioral changes occurred. Comparison with existing methods: With the existing pSico or pAAV-Sico-Red vectors, expression of fluorescent protein disappears when shRNA is conditionally activated by CRE recombinase, but our Creon shRNA vector showed simultaneous expression of both shRNA and fluorescent protein. Thus, it offers the advantage of allowing easy visual distinction of knocked-down cells. CONCLUSION: The newly improved CREon shRNA vector can be used as a novel research tool for conditional shRNA, and may be useful for various in vivo studies such as cancer and neurobiology.