Enhanced polyubiquitination of Shank3 and NMDA receptor in a mouse model of autism.

We have created a mouse genetic model that mimics a human mutation of Shank3 that deletes the C terminus and is associated with autism. Expressed as a single copy [Shank3(+/ΔC) mice], Shank3ΔC protein interacts with the wild-type (WT) gene product and results in >90% reduction of Shank3 at synapses. This "gain-of-function" phenotype is linked to increased polyubiquitination of WT Shank3 and its redistribution into proteasomes. Similarly, the NR1 subunit of the NMDA receptor is reduced at synapses with increased polyubiquitination. Assays of postsynaptic density proteins, spine morphology, and synapse number are unchanged in Shank3(+/ΔC) mice, but the amplitude of NMDAR responses is reduced together with reduced NMDAR-dependent LTP and LTD. Reciprocally, mGluR-dependent LTD is markedly enhanced. Shank3(+/ΔC) mice show behavioral deficits suggestive of autism and reduced NMDA receptor function. These studies reveal a mechanism distinct from haploinsufficiency by which mutations of Shank3 can evoke an autism-like disorder.

Murine Coronavirus Disease 2019 Lethality Is Characterized by Lymphoid Depletion Associated with Suppressed Antigen-Presenting Cell Functionality.

The disease severity of coronavirus disease 2019 (COVID-19) varies considerably from asymptomatic to serious, with fatal complications associated with dysregulation of innate and adaptive immunity. Lymphoid depletion in lymphoid tissues and lymphocytopenia have both been associated with poor disease outcomes in patients with COVID-19, but the mechanisms involved remain elusive. In this study, human angiotensin-converting enzyme 2 (hACE2) transgenic mouse models susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection were used to investigate the characteristics and determinants of lethality associated with the lymphoid depletion observed in SARS-CoV-2 infection. The lethality of Wuhan SARS-CoV-2 infection in K18-hACE2 mice was characterized by severe lymphoid depletion and apoptosis in lymphoid tissues related to fatal neuroinvasion. The lymphoid depletion was associated with a decreased number of antigen-presenting cells (APCs) and their suppressed functionality below basal levels. Lymphoid depletion with reduced APC function was a specific feature observed in SARS-CoV-2 infection but not in influenza A infection and had the greatest prognostic value for disease severity in murine COVID-19. Comparison of transgenic mouse models resistant and susceptible to SARS-CoV-2 infection revealed that suppressed APC function could be determined by the hACE2 expression pattern and interferon-related signaling. Thus, we demonstrated that lymphoid depletion associated with suppressed APC function characterizes the lethality of COVID-19 mouse models. Our data also suggest a potential therapeutic approach to prevent the severe progression of COVID-19 by enhancing APC functionality.

Nonprehensile Manipulation for Rapid Object Spinning via Multisensory Learning from Demonstration.

Dexterous manipulation concerns the control of a robot hand to manipulate an object in a desired manner. While classical dexterous manipulation strategies are based on stable grasping (or force closure), many human-like manipulation tasks do not maintain grasp stability and often utilize the dynamics of the object rather than the closed form of kinematic relation between the object and the robotic hand. Such manipulation strategies are referred as nonprehensile or dynamic dexterous manipulation in the literature. Nonprehensile manipulation often involves fast and agile movements such as throwing and flipping. Due to the complexity of such motions and uncertainties associated with them, it has been challenging to realize nonprehensile manipulation tasks in a reliable way. In this paper, we propose a new control strategy to realize practical nonprehensile manipulation. First, we make explicit use of multiple modalities of sensory data for the design of control law. Specifically, force data are employed for feedforward control, while position data are used for feedback control. Secondly, control signals (both feedback and feedforward) are obtained through multisensory learning from demonstration (LfD) experiments designed and performed for specific nonprehensile manipulation tasks of concern. To prove the concept of the proposed control strategy, experimental tests were conducted for a dynamic spinning task using a sensory-rich, two-finger robotic hand. The control performance (i.e., the speed and accuracy of the spinning task) was also compared with that of classical dexterous manipulation based on force closure and finger gaiting.

Dynamic Occupancy Grid Map with Semantic Information Using Deep Learning-Based BEVFusion Method with Camera and LiDAR Fusion.

In the field of robotics and autonomous driving, dynamic occupancy grid maps (DOGMs) are typically used to represent the position and velocity information of objects. Although three-dimensional light detection and ranging (LiDAR) sensor-based DOGMs have been actively researched, they have limitations, as they cannot classify types of objects. Therefore, in this study, a deep learning-based camera-LiDAR sensor fusion technique is employed as input to DOGMs. Consequently, not only the position and velocity information of objects but also their class information can be updated, expanding the application areas of DOGMs. Moreover, unclassified LiDAR point measurements contribute to the formation of a map of the surrounding environment, improving the reliability of perception by registering objects that were not classified by deep learning. To achieve this, we developed update rules on the basis of the Dempster-Shafer evidence theory, incorporating class information and the uncertainty of objects occupying grid cells. Furthermore, we analyzed the accuracy of the velocity estimation using two update models. One assigns the occupancy probability only to the edges of the oriented bounding box, whereas the other assigns the occupancy probability to the entire area of the box. The performance of the developed perception technique is evaluated using the public nuScenes dataset. The developed DOGM with object class information will help autonomous vehicles to navigate in complex urban driving environments by providing them with rich information, such as the class and velocity of nearby obstacles.

Visual feedback decoding during bimanual circle drawing.

The between-hand interference during bimanual tasks is a consequence of the connection between the neural controllers of movement. Previous studies showed the existence of an asymmetric between-hand interference (caused by neural cross talk) when different kinematics plans were to be executed by each hand or when only one was visually guided and received perturbed visual feedback. Here, in continuous bimanual circle drawing tasks, we investigated if the central nervous system (CNS) can benefit from visual composite feedback, i.e., a weighted sum of hands' positions presented for the visually guided hand, to control the nonvisible hand. Our results demonstrated improvement in the nonvisible nondominant hand (NDH) performance in the presence of the composite feedback. When NDH was visually guided, the dominant hand's (DH) performance during asymmetric drawing deteriorated, whereas its performance during symmetric drawing improved. This indicates that the CNS's ability to leverage composite feedback, which can be the result of decoding the nonvisible hand positional information from the composite feedback, is task-dependent and can be asymmetric. Also, the nonvisible hand's performance degraded when DH or NDH was visually guided with amplified error feedback. The results of the amplified feedback condition do not strongly support the asymmetry of the interference during asymmetric circle drawing. Comparing muscle activations in the asymmetric experiment, we concluded that the observed kinematic differences were not due to alternation in muscle co-contractions.NEW & NOTEWORTHY Many daily activities involve bimanual coordination while simultaneous movement of the hands may result in interference with their movements. Here, we studied whether the central nervous system could use the relevant information in composite feedback, i.e., a weighted sum of positional information of nonvisible and visible hands, to improve the movement of the nonvisible hand. Our results suggest the ability to decode and associate task-relevant information from the composite feedback.

Immediate Postoperative High Syndecan-1 is Associated with Short-Term Morbidity and Mortality After Robot-Assisted Esophagectomy: A Prospective Observational Study.

BACKGROUND: Disruption of the endothelial glycocalyx (EG) is associated with a poor prognosis in various clinical settings. This study aimed to determine the association between immediate postoperative serum syndecan-1 levels, a representative marker for EG degradation, and major postoperative morbidity and mortality in patients undergoing robot-assisted esophagectomy. METHODS: Patients who underwent robot-assisted esophagectomy between 2018 and 2022 were prospectively enrolled. The primary outcome was the association between immediate postoperative syndecan-1 levels and the occurrence of major postoperative morbidity and mortality within 30 days of surgery. Patients were classified into low and high syndecan-1 groups based on the optimal cut-off value of syndecan-1 for predicting major morbidity and mortality. A multivariable logistic regression analysis was performed to investigate the risk factors for major morbidity and mortality. RESULTS: A total of 207 patients were analyzed. Patients with high syndecan-1 levels (≥48 ng/mL) showed a significantly greater incidence of unexpected returns to the operating room and anastomotic leaks and longer durations of hospital and intensive care unit stays than patients with low syndecan-1 levels (<48 ng/mL). Immediate postoperative syndecan-1 levels ≥48 ng/mL (odds ratio [OR] 2.32, 95% confidence interval [CI] 1.23-4.76), American Society of Anesthesiologists physical status ≥III (OR 3.36, 95% CI 1.56-7.22), and current smoker (OR 4.02, 95% CI 1.52-10.61) were independently associated with major morbidity and mortality within 30 days of esophagectomy. CONCLUSIONS: Immediate postoperative syndecan-1 levels ≥48 ng/mL could be used for the early detection of patients at high risk of complications after robot-assisted esophagectomy.

Establishment of multicenter COVID-19 therapeutics preclinical test system in Republic of Korea.

Throughout the recent COVID-19 pandemic, South Korea led national efforts to develop vaccines and therapeutics for SARS-CoV-2. The project proceeded as follows: 1) evaluation system setup (including Animal Biosafety Level 3 (ABSL3) facility alliance, standardized nonclinical evaluation protocol, and laboratory information management system), 2) application (including committee review and selection), and 3) evaluation (including expert judgment and reporting). After receiving 101 applications, the selection committee reviewed pharmacokinetics, toxicity, and efficacy data and selected 32 final candidates. In the nonclinical efficacy test, we used golden Syrian hamsters and human angiotensin-converting enzyme 2 transgenic mice under a cytokeratin 18 promoter to evaluate mortality, clinical signs, body weight, viral titer, neutralizing antibody presence, and histopathology. These data indicated eight new drugs and one repositioned drug having significant efficacy for COVID-19. Three vaccine and four antiviral drugs exerted significant protective activities against SARS-CoV-2 pathogenesis. Additionally, two anti-inflammatory drugs showed therapeutic effects on lung lesions and weight loss through their mechanism of action but did not affect viral replication. Along with systematic verification of COVID-19 animal models through large-scale studies, our findings suggest that ABSL3 multicenter alliance and nonclinical evaluation protocol standardization can promote reliable efficacy testing against COVID-19, thus expediting medical product development.

Supervised Relation Extraction Between Suicide-Related Entities and Drugs: Development and Usability Study of an Annotated PubMed Corpus.

BACKGROUND: Drug-induced suicide has been debated as a crucial issue in both clinical and public health research. Published research articles contain valuable data on the drugs associated with suicidal adverse events. An automated process that extracts such information and rapidly detects drugs related to suicide risk is essential but has not been well established. Moreover, few data sets are available for training and validating classification models on drug-induced suicide. OBJECTIVE: This study aimed to build a corpus of drug-suicide relations containing annotated entities for drugs, suicidal adverse events, and their relations. To confirm the effectiveness of the drug-suicide relation corpus, we evaluated the performance of a relation classification model using the corpus in conjunction with various embeddings. METHODS: We collected the abstracts and titles of research articles associated with drugs and suicide from PubMed and manually annotated them along with their relations at the sentence level (adverse drug events, treatment, suicide means, or miscellaneous). To reduce the manual annotation effort, we preliminarily selected sentences with a pretrained zero-shot classifier or sentences containing only drug and suicide keywords. We trained a relation classification model using various Bidirectional Encoder Representations from Transformer embeddings with the proposed corpus. We then compared the performances of the model with different Bidirectional Encoder Representations from Transformer-based embeddings and selected the most suitable embedding for our corpus. RESULTS: Our corpus comprised 11,894 sentences extracted from the titles and abstracts of the PubMed research articles. Each sentence was annotated with drug and suicide entities and the relationship between these 2 entities (adverse drug events, treatment, means, and miscellaneous). All of the tested relation classification models that were fine-tuned on the corpus accurately detected sentences of suicidal adverse events regardless of their pretrained type and data set properties. CONCLUSIONS: To our knowledge, this is the first and most extensive corpus of drug-suicide relations.

Prevalence and causative drugs of drug-induced Parkinsonism in pediatric patients.

Although several studies provided evidence on the epidemiology of drug-induced Parkinsonism (DIP) and its causative drugs, it is still limited in pediatrics. This study aimed to investigate the prevalence and risk of DIP in pediatrics. We used the Health Insurance Review and Assessment Service-Pediatric Patients Sample in Korea between 2010 and 2017 to estimate the annual prevalence of DIP and causative drug use using a cross-sectional design. The risk of DIP associated with causative drugs was evaluated using a case-crossover design. Adjusted odds ratios (aOR) with 95% confidence intervals (CI) were calculated using a conditional logistic regression. A total of 2925 pediatric patients had diagnosed with DIP from 2010 to 2017. Most patients were aged between 12 and19 years old, and 99.8% had any diagnosis of mental health disorder (MHD). During the study period, the prevalence of DIP increased by 10.0-fold from 2010 to 2017. All causative drugs showed a corresponding increase in their use, with atypical antipsychotics being the most prominent (increase ratio, 2.07). For both in the prevalence of DIP and atypical antipsychotic use, the increment was much bigger in patients with non-psychotic MHD than that in patients with psychotic MHD. In the case-crossover study, antipsychotics showed the largest aOR with DIP. Risperidone among antipsychotics showed the highest risk for DIP (aOR = 7.09, 95% CI = 3.83-13.09), followed by aripiprazole (aOR = 5.03, 95% CI = 2.88-8.80). This study suggests that the increase in DIP prevalence in pediatric patients might be because of the increased use of atypical antipsychotics.

Unsupervised Stereo Matching with Surface Normal Assistance for Indoor Depth Estimation.

To obtain more accurate depth information with stereo cameras, various learning-based stereo-matching algorithms have been developed recently. These algorithms, however, are significantly affected by textureless regions in indoor applications. To address this problem, we propose a new deep-neural-network-based data-driven stereo-matching scheme that utilizes the surface normal. The proposed scheme includes a neural network and a two-stage training strategy. The neural network involves a feature-extraction module, a normal-estimation branch, and a disparity-estimation branch. The training processes of the feature-extraction module and the normal-estimation branch are supervised while the training of the disparity-estimation branch is performed unsupervised. Experimental results indicate that the proposed scheme is capable of estimating the surface normal accurately in textureless regions, leading to improvement in the disparity-estimation accuracy and stereo-matching quality in indoor applications involving such textureless regions.

Association between 20% Albumin Use and Acute Kidney Injury in Major Abdominal Surgery with Transfusion.

Red blood cell (RBC) transfusion and albumin administration can affect kidney function. We aimed to evaluate the association between intraoperative 20% albumin administration and acute kidney injury (AKI), along with the duration of hospitalization and 30-day mortality in patients undergoing major abdominal surgery with RBC transfusion. This retrospective study included 2408 patients who received transfusions during major abdominal surgery. Patients were categorized into albumin (n = 842) or no-albumin (n = 1566) groups. We applied inverse probability of treatment weighting (IPTW), propensity score (PS) matching (PSM), and PS covariate adjustment to assess the effect of albumin administration on the outcomes. In the unadjusted cohort, albumin administration was significantly associated with increased risk of AKI, prolonged hospitalization, and higher 30-day mortality. However, there was no significant association between albumin administration and AKI after adjustment (OR 1.26, 95% CI 0.90-1.76 for the IPTW; OR 1.03, 95% CI 0.72-1.48 for the PSM; and OR 1.04, 95% CI 0.76-1.43 for the PS covariate adjustment methods). While albumin exposure remained associated with prolonged hospitalization after adjustment, it did not affect 30-day mortality. Our findings suggest that hyper-oncotic albumin can be safely administered to patients who are at risk of developing AKI due to RBC transfusion.

USP13 regulates HMGB1 stability and secretion through its deubiquitinase activity.

BACKGROUND: High mobility group box 1 (HMGB1) is a damage-associated molecular pattern (DAMP) molecule that plays a central role in innate immunity. HMGB1 acts as a late mediator of inflammation when actively secreted in response to inflammatory stimuli. Several post-translational modifications (PTMs), including acetylation, phosphorylation, and oxidation, are involved in HMGB1 secretion. However, the E3 ligases of HMGB1 and the mechanism by which DUBs regulate HMGB1 deubiquitination are not well known. METHODS: LC-MS/MS, proximity ligation assay, immunoprecipitation were used to identify ubiquitin-specific protease 13 (USP13) as a binding partner of HMGB1 and to investigate ubiquitination of HMGB1. USP13 domain mutant was constructed for domain study and Spautin-1 was treated for inhibition of USP13. Confocal microscopy image showed localization of HMGB1 by USP13 overexpression. The data were analyzed using one-way analysis of variance with Tukey's honestly significant difference post-hoc test for multiple comparisons or a two-tailed Student's t-test. RESULTS: We identified ubiquitin-specific protease 13 (USP13) as a novel binding partner of HMGB1 and demonstrated that USP13 plays a role in stabilizing HMGB1 from ubiquitin-mediated degradation. USP13 overexpression increased nucleocytoplasmic translocation of HMGB1 and promoted its secretion, which was inhibited by treatment with Spautin-1, a selective inhibitor of USP13. CONCLUSION: Taken together, we suggest that USP13 is a novel deubiquitinase of HMGB1 that regulates the stability and secretion of HMGB1.

Remission of type 2 diabetes after gastrectomy for gastric cancer: diabetes prediction score.

BACKGROUND: Although type 2 diabetes (T2D) remission after gastric cancer surgery has been reported, little is known about the predictors of postoperative T2D remission. METHODS: This study used data from a nationwide cohort provided by the National Health Insurance Service in Korea. We developed a diabetes prediction (DP) score, which predicted postoperative T2D remissions using a logistic regression model based on preoperative variables. We applied machine-learning algorithms [random forest, XGboost, and least absolute shrinkage and selection operator (LASSO) regression] and compared their predictive performances with those of the DP score. RESULTS: The DP score comprised five parameters: baseline body mass index (< 25 or ≥ 25 kg/m2), surgical procedures (subtotal or total gastrectomy), age (< 65 or ≥ 65 years), fasting plasma glucose levels (≤ 130 or > 130 mg/dL), and antidiabetic medications (combination therapy including sulfonylureas, combination therapy not including sulfonylureas, single sulfonylurea, or single non-sulfonylurea]). The DP score showed a clinically useful predictive performance for T2D remission at 3 years after surgery [training cohort: area under the receiver operating characteristics (AUROC) 0.73, 95% confidence interval (CI), 0.71-0.75; validation cohort: AUROC 0.72, 95% CI 0.69-0.75], which was comparable to that of the machine-learning models (random forest: AUROC 0.71, 95% CI 0.68-0.74; XGboost: AUROC 0.70, 95% CI 0.67-0.73; LASSO regression: AUROC 0.75, 95% CI 0.73-0.78 in the validation cohort). It also predicted the T2D remission at 6 and 9 years after surgery. CONCLUSIONS: The DP score is a useful scoring system for predicting T2D remission after gastric cancer surgery.

Identification of highly selective type II kinase inhibitors with chiral peptidomimetic tails.

Identification of highly selective type II kinase inhibitors is described. Two different chiral peptidomimetic scaffolds were introduced on the tail region of non-selective type II kinase inhibitor GNF-7 to enhance the selectivity. Kinome-wide selectivity profiling analysis showed that type II kinase inhibitor 7a potently inhibited Lck kinase with great selectivity (IC50 of 23.0 nM). It was found that 7a and its derivatives possessed high selectivity for Lck over even structurally conserved all Src family kinases. We also observed that 7a inhibited Lck activation in Jurkat T cells. Moreover, 7a was found to alleviate clinical symptoms in DSS-induced colitis mice. This study provides a novel insight into the design of selective type II kinase inhibitors by adopting chiral peptidomimetic moieties on the tail region.

A Generic Image Processing Pipeline for Enhancing Accuracy and Robustness of Visual Odometry.

The accuracy of pose estimation from feature-based Visual Odometry (VO) algorithms is affected by several factors such as lighting conditions and outliers in the matched features. In this paper, a generic image processing pipeline is proposed to enhance the accuracy and robustness of feature-based VO algorithms. The pipeline consists of three stages, each addressing a problem that affects the performance of VO algorithms. The first stage tackles the lighting condition problem, where a filter called Contrast Limited Adaptive Histogram Equalization (CLAHE) is applied to the images to overcome changes in lighting in the environment. The second stage uses the Suppression via Square Covering (SSC) algorithm to ensure the features are distributed properly over the images. The last stage proposes a novel outliers rejection approach called the Angle-based Outlier Rejection (AOR) algorithm to remove the outliers generated in the feature matching process. The proposed pipeline is generic and modular and can be integrated with any type of feature-based VO (monocular, RGB-D, or stereo). The efficiency of the proposed pipeline is validated using sequences from KITTI (for stereo VO) and TUM (for RGB-D VO) datasets, as well as experimental sequences using an omnidirectional mobile robot (for monocular VO). The obtained results showed the performance gained by enhancing the accuracy and robustness of the VO algorithms without compromising on the computational cost using the proposed pipeline. The results are substantially better as opposed to not using the pipeline.

The collagen structure of C1q induces wound healing by engaging discoidin domain receptor 2.

BACKGROUND: C1q has been reported to reveal complement-independent roles in immune and non-immune cells. C1q binds to its specific receptors to regulate distinct functions that rely on the environment and cell types. Discoidin domain receptor 2 (DDR2) is activated by collagen and functions in wound healing by controlling matrix metalloproteinase (MMP) expression. Since C1q exhibits a collagen-like structure, we hypothesized that C1q might engage DDR2 to regulate wound healing and extracellular matrix (ECM) remodeling. METHODS: Cell-based assay, proximity ligation assay, ELISA, and surface plasmon analysis were utilized to investigate DDR2 and C1q binding. We also investigate the C1q-mediated in vitro wound healing ability using the human fibrosarcoma cell line, HT1080. RESULTS: C1q induced the phosphorylation of DDR2, p38 kinase, and ERK1/2. C1q and DDR2 binding improved cell migration and induced MMP2 and MMP9 expression. DDR2-specific shRNA reduced C1q-mediated cell migration for wound healing. CONCLUSIONS: C1q is a new DDR2 ligand that promotes wound healing. These findings have therapeutic implications in wound healing-related diseases.

Risk of seizures associated with antipsychotic treatment in pediatrics with psychiatric disorders: a nested case-control study in Korea.

Antipsychotic drugs raise seizure risk in adults, and antipsychotic drug use is increasing among pediatric psychiatric disorder patients. However, few studies have examined seizure risk in this younger patient population. To evaluate seizure risk in pediatric patients on antipsychotics, we conducted a nested case-control study using a nationwide database. Patient information was retrieved from the Korean Health Insurance Review and Assessment (HIRA) database from 2008-2018. Antipsychotic use among newly diagnosed psychiatric patients was gathered starting 1 year before the index date and categorized as recent, past, consistent, or none. Seizure cases among these patients were defined based on (1) prescription of antiepileptic drugs or (2) an electroencephalography (EEG) examination among patients with seizure diagnostic code. A conditional logistic regression model was constructed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for seizure risk due to antipsychotic use. In total, 1523 seizure cases and 6092 seizure-free controls aged 8-19 years with newly diagnosed psychiatric disorders were included for analysis. Logistic regression revealed a significant association between antipsychotic use and seizure development (recent users OR = 4.03, 95% CI 3.4-4.79; consistent users: OR = 2.84, 95% CI 2.44-3.3). Seizure risk enhanced further with an increase in the number of antipsychotic drugs used. Risperidone, aripiprazole, quetiapine, olanzapine, paliperidone, and blonanserin were independently associated with greater seizure risk. Pediatric patients receiving antipsychotics, especially new or multiple antipsychotic users, should be carefully monitored for seizure development.

ELF3 Is a Target That Promotes Therapeutic Efficiency in EGFR Tyrosine Kinase Inhibitor-Resistant Non-Small Cell Lung Cancer Cells via Inhibiting PKCί.

(1) Background: Mutations in epidermal growth factor receptor (EGFR) proteins account for many non-small cell lung cancers (NSCLCs), and EGFR tyrosine kinase inhibitors (TKIs) are being used as targeted therapeutics. However, resistance to TKIs continues to increase owing to additional mutations in more than half of the patients receiving EGFR TKI therapy. In addition to targeting new mutations with next-generation therapeutics, it is necessary to find an alternative target to overcome the challenges associated with resistance. (2) Methods: To identify potential alternative targets in patients with NSCLC undergoing targeted therapy, putative targets were identified by transcriptome profiling and validated for their biological and therapeutic effects in vitro and in vivo. (3) Results: ELF3 was found to be differentially expressed in NSCLC, and ELF3 knockdown significantly increased cell death in K-Ras mutant as well as in EGFR L858R/T790M mutation harboring lung cancer cells. We also found that auranofin, an inhibitor of protein kinase C iota (PKCί), a protein upstream of ELF3, effectively induced cell death. (4) Conclusions: Our study suggests that blocking ELF3 is an effective way to induce cell death in NSCLC with K-Ras and EGFR T790M/L858R mutations and thus advocates the use of auranofin as an effective alternative drug to overcome EGFR TKI resistance.

Paricalcitol Improves Hypoxia-Induced and TGF-ß1-Induced Injury in Kidney Pericytes.

Recently, the role of kidney pericytes in kidney fibrosis has been investigated. This study aims to evaluate the effect of paricalcitol on hypoxia-induced and TGF-ß1-induced injury in kidney pericytes. The primary cultured pericytes were pretreated with paricalcitol (20 ng/mL) for 90 min before inducing injury, and then they were exposed to TGF-ß1 (5 ng/mL) or hypoxia (1% O2 and 5% CO2). TGF-ß1 increased α-SMA and other fibrosis markers but reduced PDGFRß expression in pericytes, whereas paricalcitol reversed the changes. Paricalcitol inhibited the TGF-ß1-induced cell migration of pericytes. Hypoxia increased TGF-ß1, α-SMA and other fibrosis markers but reduced PDGFRß expression in pericyte, whereas paricalcitol reversed them. Hypoxia activated the HIF-1α and downstream molecules including prolyl hydroxylase 3 and glucose transporter-1, whereas paricalcitol attenuated the activation of the HIF-1α-dependent molecules and TGF-ß1/Smad signaling pathways in hypoxic pericytes. The gene silencing of HIF-1α vanished the hypoxia-induced TGF-ß1, α-SMA upregulation, and PDGFRß downregulation. The effect of paricalcitol on the HIF-1α-dependent changes of fibrosis markers was not significant after the gene silencing of HIF-1α. In addition, hypoxia aggravated the oxidative stress in pericytes, whereas paricalcitol reversed the oxidative stress by increasing the antioxidant enzymes in an HIF-1α-independent manner. In conclusion, paricalcitol improved the phenotype changes of pericyte to myofibroblast in TGF-ß1-stimulated pericytes. In addition, paricalcitol improved the expression of fibrosis markers in hypoxia-exposed pericytes both in an HIF-1α-dependent and independent manner.

Inflachromene inhibits autophagy through modulation of Beclin 1 activity.

Autophagy is a central intracellular catabolic mechanism that mediates the degradation of cytoplasmic proteins and organelles, and regulation of autophagy is essential for homeostasis. HMGB1 is an important sepsis mediator when secreted and also functions as an inducer of autophagy by binding to Beclin 1. In this study, we studied the effect of inflachromene (ICM), a novel HMGB1 secretion inhibitor, on autophagy. ICM inhibited autophagy by inhibiting nucleocytoplasmic translocation of HMGB1 and by increasing Beclin 1 ubiquitylation for degradation by enhancing the interaction between Beclin 1 and E3 ubiquitin ligase RNF216. These data suggest that ICM could be used as a potential autophagy suppressor.