A Machine Learning Model to Predict the Histology of Retroperitoneal Lymph Node Dissection Specimens.

BACKGROUND/AIM: While post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) benefits patients with teratoma or viable germ cell tumors (GCT), it becomes overtreatment if necrosis is detected in PC-RPLND specimens. Serum microRNA-371a-3p correctly predicts residual viable GCT with 100% sensitivity; however, prediction of residual teratoma in PC-RPLND specimens using current modalities remains difficult. Therefore, we developed a machine learning model using CT imaging and clinical variables to predict the presence of residual teratoma in PC-RPLND specimens. PATIENTS AND METHODS: This study included 58 patients who underwent PC-RPLND between 2005 and 2019 at the University of Tsukuba Hospital. On CT imaging, 155 lymph nodes were identified as regions of interest (ROIs). The ResNet50 algorithm and/or Support Vector Machine (SVM) classification were applied and a nested, 3-fold cross-validation protocol was used to determine classifier accuracy. RESULTS: PC-RPLND specimen analysis revealed 35 patients with necrosis and 23 patients with residual teratoma, while histology of 155 total ROIs showed necrosis in 84 ROIs and teratoma in 71 ROIs. The ResNet50 algorithm, using CT imaging, achieved a diagnostic accuracy of 80.0%, corresponding to a sensitivity of 67.3%, a specificity of 90.5%, and an AUC of 0.84, whereas SVM classification using clinical variables achieved a diagnostic accuracy of 74.8%, corresponding to a sensitivity of 59.0%, a specificity of 88.1%, and an AUC of 0.84. CONCLUSION: Our machine learning models reliably distinguish between necrosis and residual teratoma in clinical PC-RPLND specimens.

Quantitative evaluation model of variable diagnosis for chest X-ray images using deep learning.

The purpose of this study is to demonstrate the use of a deep learning model in quantitatively evaluating clinical findings typically subject to uncertain evaluations by physicians, using binary test results based on routine protocols. A chest X-ray is the most commonly used diagnostic tool for the detection of a wide range of diseases and is generally performed as a part of regular medical checkups. However, when it comes to findings that can be classified as within the normal range but are not considered disease-related, the thresholds of physicians' findings can vary to some extent, therefore it is necessary to define a new evaluation method and quantify it. The implementation of such methods is difficult and expensive in terms of time and labor. In this study, a total of 83,005 chest X-ray images were used to diagnose the common findings of pleural thickening and scoliosis. A novel method for quantitatively evaluating the probability that a physician would judge the images to have these findings was established. The proposed method successfully quantified the variation in physicians' findings using a deep learning model trained only on binary annotation data. It was also demonstrated that the developed method could be applied to both transfer learning using convolutional neural networks for general image analysis and a newly learned deep learning model based on vector quantization variational autoencoders with high correlations ranging from 0.89 to 0.97.

Structural Analyses of Designed α-Helix and ß-Sheet Peptide Nanofibers Using Solid-State Nuclear Magnetic Resonance and Cryo-Electron Microscopy and Introduction of Structure-Based Metal-Responsive Properties.

The 21-residue peptide α3, which is artificially designed and consists of three repeats of 7 residues, is known to rapidly assemble into the α-helix nanofiber. However, its molecular structure within the fiber has not yet been fully elucidated. Thus, we conducted a thorough investigation of the fiber's molecular structure using solid-state NMR and other techniques. The molecules were found to be primarily composed of the α-helix structure, with some regions near the C- and N-terminal adopting a 310-helix structure. Furthermore, it was discovered that ß-sheet hydrogen bonds were formed between the molecules at both ends. These intermolecular interactions caused the molecules to assemble parallelly in the same direction, forming helical fibers. In contrast, we designed two molecules, CaRP2 and ßKE, that can form ß-sheet intermolecular hydrogen bonds using the entire molecule instead of just the ends. Cryo-EM and other measurements confirmed that the nanofibers formed in a cross ß structure, albeit at a slow rate, with the formation times ranging from 1 to 42 days. To create peptide nanofibers that instantaneously respond to changes in the external environment, we designed several molecules (HDM1-3) based on α3 by introducing metal-binding sites. One of these molecules was found to be highly responsive to the addition of metal ions, inducing α-helix formation and simultaneously assembling into nanofibers. The nanofibers lost their structure upon removal of the metal ion. The change occurred promptly and was reversible, demonstrating that the intended level of responsiveness was attained.

A step-by-step approach for assessing acute oral toxicity without animal testing for additives of quasi-drugs and cosmetic ingredients.

Animal testing of cosmetic ingredients and products has been banned in the European Union since 2013. However, in Japan, the application of new quasi-drugs requires the generation of data on acute oral toxicity through animal testing. A weight of evidence approach for assessing oral toxicity was challenged. This approach used a combination of safety data, including a neutral red uptake cytotoxicity assay using BALB/c3T3 cells (3T3-NRU cytotoxicity assay), which can assess the acute oral toxicity of quasi-drugs or cosmetic ingredients. We conclude that the step-by-step approach can be used to assess test substances that cause low acute oral toxicity, such as the median lethal dose (LD 50) > 2000 mg/kg, thereby avoiding animal testing.

Prognostic nutritional index of early post-pembrolizumab therapy predicts long-term survival in patients with advanced urothelial carcinoma.

Pembrolizumab has been widely used to treat advanced urothelial carcinoma that has progressed after first-line platinum-based chemotherapy. Because its clinical benefits are limited, biomarkers that can predict a good response to pembrolizumab are required. The prognostic nutritional index (PNI), calculated using the serum albumin level and peripheral lymphocyte count, has been evaluated as a predictive biomarker in cancer immunotherapy. The present study investigated the application of PNI as a predictive biomarker for pembrolizumab response in patients with advanced urothelial cancer. A retrospective study was conducted on 34 patients treated with pembrolizumab at Shiga University of Medical Science Hospital between January 2018 and July 2022. The posttreatment PNI (post-PNI) was calculated within 2 months of starting pembrolizumab. The present study investigated the association between post-PNI and objective response, overall survival (OS) and progression-free survival (PFS). The patient cohort was stratified into two categories, high and low post-PNI groups, with a cutoff value of post-PNI at 40. The higher post-PNI group demonstrated a better disease control rate than the lower post-PNI group (complete response + partial response + stable disease, 75 vs. 21%, P=0.004). Regarding median OS, the higher post-PNI group exhibited a significantly longer survival time than the lower post-PNI group (23.1 vs. 2.9 months, P<0.001). Similarly, the higher post-PNI group exhibited a significantly longer PFS than the lower post-PNI group (10.2 vs.1.9 months, P<0.001). Multivariate analysis showed that a higher post-PNI value was an independent predictor for OS (hazard ratio, 0.04; 95% confidence interval, 0.01-0.14; P<0.001) and PFS (hazard ratio, 0.12; 95% confidence interval, 0.04-0.35; P<0.001). The present study indicated that the post-PNI was a predictor of favorable clinical outcomes in patients treated with pembrolizumab for advanced urothelial carcinoma.

New Platform for Screening Genetic Libraries at Elevated Temperatures: Biological and Genomic Information and Genetic Tools of Geobacillus thermodenitrificans K1041.

Geobacillus thermodenitrificans K1041 is an unusual thermophile that is highly transformable via electroporation, making it a promising host for screening genetic libraries at elevated temperatures. In this study, we determined its biological properties, draft genome sequence, and effective vectors and also optimized the electroporation procedures in an effort to enhance its utilization. The organism exhibited swarming motility but not detectable endospore formation, and growth was rapid at 60°C under neutral and relatively low-salt conditions. Although the cells showed negligible acceptance of shuttle plasmids from general strains of Escherichia coli, methylation-controlled plasmids from dam mutant strains were efficiently accepted, suggesting circumvention of a restriction-modification system in G. thermodenitrificans K1041. We optimized the electroporation procedure to achieve efficiencies of 103 to 105 CFU/µg for five types of plasmids, which exhibited the different copy numbers and segregational stabilities in G. thermodenitrificans K1041. Some sets of plasmids were compatible. Moreover, we observed substantial plasmid-directed production of heterologous proteins in the intracellular or extracellular environments. Our successful construction of a library of promoter mutants using K1041 cells as hosts and subsequent screening at elevated temperatures to identify improved promoters revealed that G. thermodenitrificans K1041 was practical as a library host. The draft genomic sequence of the organism contained 3,384 coding genes, including resA and mcrB genes, which are involved in restriction-modification systems. Further examination revealed that in-frame deletions of resA increased transformation efficiencies, but mcrB deletion had no effect. The ΔresA mutant exhibited transformation efficiencies of >105 CFU/µg for some plasmids. IMPORTANCE Geobacillus thermodenitrificans K1041 has yet to be fully characterized. Although it is transformable via electroporation, it rarely accepts Escherichia coli-derived plasmids. This study clarified the biological and genomic properties of G. thermodenitrificans K1041. Additionally, we developed an electroporation procedure resulting in efficient acceptance of E. coli-derived plasmids. This procedure produced transformants using small amounts of plasmids immediately after the ligation reaction. Thus, G. thermodenitrificans K1041 was identified as a host for screening promoter mutants at elevated temperatures. Furthermore, because this strain efficiently produced heterologous proteins, it could serve as a host for screening thermostable proteins encoded in random mutant libraries or metagenomes. We also generated a ΔresA mutant that exhibited transformation efficiencies of >105 CFU/µg, which were highest in cases of electroporation-based transformation of Geobacillus spp. with E. coli-derived plasmids. Our findings provide a new platform for screening diverse genetic libraries at elevated temperatures.

Comparison of toxicological effects and exposure levels between triclosan and its structurally similar chemicals using in vitro tests for read-across case study.

Read-across based on structural and biological similarities is expected to be a promising alternative method for assessing systemic toxicity. A concrete strategy for quantitative chemical risk assessment would be to stack read-across case studies and extract key considerations from them. Thus, we developed a read-across case study by comparing the toxicological effects based on adverse outcome pathways and exposure levels of different structurally similar chemicals for a target organ. In this study, we selected the hepatotoxicity of triclosan and its structurally similar chemicals including diclosan and 1-chloro-3-(4-chlorophenoxy)benzene. The results of in vitro toxicogenomics showed that disorders of cholesterol synthesis were commonly detected with both triclosan and diclosan. The decrease in hepatocellular cholesterol levels was similar in the cells treated with triclosan and diclosan. Furthermore, the exposure levels of triclosan and diclosan for the liver were similar. Collectively, these results suggest that triclosan and diclosan show similar toxicological effects and severity of hepatotoxicity. Considering the existing repeated dose toxicity data, our prediction results are reasonable regarding the toxicological effect and its severity. Thus, the present study demonstrated the usability of comparing toxicological effects and exposure levels using read-across for quantitative chemical risk assessment.

Urine cell image recognition using a deep-learning model for an automated slide evaluation system.

OBJECTIVES: To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm that classifies urine cell images as negative (benign) or positive (atypical or malignant). PATIENTS AND METHODS: We collected 195 urine cytology slides from consecutive patients with a histologically confirmed diagnosis of urothelial cancer (between January 2016 and December 2017). Two certified cytotechnologists independently evaluated and labelled each slide; 4637 cell images with concordant diagnoses were selected, including 3128 benign cells (negative), 398 atypical cells, and 1111 cells that were malignant or suspicious for malignancy (positive). This pathologically confirmed labelled dataset was used to represent the ground truth for AI training/validation/testing. Customized CutMix (CircleCut) and Refined Data Augmentation were used for image processing. The model architecture included EfficientNet B6 and Arcface. We used 80% of the data for training and validation (4:1 ratio) and 20% for testing. Model performance was evaluated with fivefold cross-validation. A receiver-operating characteristic (ROC) analysis was used to evaluate the binary classification model. Bayesian posterior probabilities for the AI performance measure (Y) and cytotechnologist performance measure (X) were compared. RESULTS: The area under the ROC curve was 0.99 (95% confidence interval [CI] 0.98-0.99), the highest accuracy was 95% (95% CI 94-97), sensitivity was 97% (95% CI 95-99), and specificity was 95% (95% CI 93-97). The accuracy of AI surpassed the highest level of cytotechnologists for the binary classification [Pr(Y > X) = 0.95]. AI achieved >90% accuracy for all cell subtypes. In the subgroup analysis based on the clinicopathological characteristics of patients who provided the test cells, the accuracy of AI ranged between 89% and 97%. CONCLUSION: Our novel AI classification system for urine cytology successfully classified all cell subtypes with an accuracy of higher than 90%, and achieved diagnostic accuracy of malignancy superior to the highest level achieved by cytotechnologists.

Cosmic Birefringence Triggered by Dark Matter Domination.

Cosmic birefringence is predicted if an axionlike particle (ALP) moves after the recombination. We show that this naturally happens if the ALP is coupled to the dark matter density because it then acquires a large effective mass after the matter-radiation equality. Our scenario applies to a broad range of the ALP mass m_{ϕ}≲10^{-28} eV, even smaller than the present Hubble constant. We give a simple model to realize this scenario, where dark matter is made of hidden monopoles, which give the ALP such a large effective mass through the Witten effect. The mechanism works if the ALP decay constant is of order of the grand unified theory scale without a fine-tuning of the initial misalignment angle. For smaller decay constant, the hidden monopole can be a fraction of dark matter. We also study the implications for the QCD axion, and show that the domain wall problem can be solved by the effective mass.

Development of in-house fully residual deep convolutional neural network-based segmentation software for the male pelvic CT.

BACKGROUND: This study aimed to (1) develop a fully residual deep convolutional neural network (CNN)-based segmentation software for computed tomography image segmentation of the male pelvic region and (2) demonstrate its efficiency in the male pelvic region. METHODS: A total of 470 prostate cancer patients who had undergone intensity-modulated radiotherapy or volumetric-modulated arc therapy were enrolled. Our model was based on FusionNet, a fully residual deep CNN developed to semantically segment biological images. To develop the CNN-based segmentation software, 450 patients were randomly selected and separated into the training, validation and testing groups (270, 90, and 90 patients, respectively). In Experiment 1, to determine the optimal model, we first assessed the segmentation accuracy according to the size of the training dataset (90, 180, and 270 patients). In Experiment 2, the effect of varying the number of training labels on segmentation accuracy was evaluated. After determining the optimal model, in Experiment 3, the developed software was used on the remaining 20 datasets to assess the segmentation accuracy. The volumetric dice similarity coefficient (DSC) and the 95th-percentile Hausdorff distance (95%HD) were calculated to evaluate the segmentation accuracy for each organ in Experiment 3. RESULTS: In Experiment 1, the median DSC for the prostate were 0.61 for dataset 1 (90 patients), 0.86 for dataset 2 (180 patients), and 0.86 for dataset 3 (270 patients), respectively. The median DSCs for all the organs increased significantly when the number of training cases increased from 90 to 180 but did not improve upon further increase from 180 to 270. The number of labels applied during training had a little effect on the DSCs in Experiment 2. The optimal model was built by 270 patients and four organs. In Experiment 3, the median of the DSC and the 95%HD values were 0.82 and 3.23 mm for prostate; 0.71 and 3.82 mm for seminal vesicles; 0.89 and 2.65 mm for the rectum; 0.95 and 4.18 mm for the bladder, respectively. CONCLUSIONS: We have developed a CNN-based segmentation software for the male pelvic region and demonstrated that the CNN-based segmentation software is efficient for the male pelvic region.

Grouping of chemicals based on the potential mechanisms of hepatotoxicity of naphthalene and structurally similar chemicals using in vitro testing for read-across and its validation.

Integrated Approaches to Testing and Assessment provides a framework to improve the reliability of read-across for chemical risk assessment of systemic toxicity without animal testing. However, the availability of only a few case studies hinders the use of this concept for regulatory purposes. Thus, we compared the biological similarity of structurally similar chemicals using in vitro testing to demonstrate the validity of this concept for grouping chemicals and to extract key considerations in read-across. We analyzed the hepatotoxicity of naphthalene and three chemicals structurally similar to naphthalene (2,7-naphthalenediol, 1,5-naphthalenediol, and 1-naphthol) for which 90-day repeated dose toxicity data are available. To elucidate and compare their potential mechanisms, we conducted in vitro microarray analysis using rat primary hepatocytes and validated the results using a biomarker and metabolic activation analysis. We observed that 2,7-naphthalenediol, 1,5-naphthalenediol, and 1-naphthol had similar potential mechanisms, namely, induction of oxidative stress by their metabolic activation. Conversely, naphthalene did not show a similar toxicity effect. The existing in vivo data confirmed our grouping of chemicals based on this potential mechanism. Thus, our findings suggest that in vitro toxicogenomics and related biochemical assays are useful for comparing biological similarities and grouping chemicals based on their toxicodynamics for read-across.

Evaluation of Toxic Amyloid 42 Oligomers in Rat Primary Cerebral Cortex Cells and Human iPS-derived Neurons Treated with 10-Me-Aplog-1, a New PKC Activator.

Amyloid ß42 (Aß42), a causative agent of Alzheimer's disease (AD), is derived extracellularly from Aß precursor protein (APP) following the latter's cleavage by ß-secretase, but not α-secretase. Protein kinase Cα (PKCα) activation is known to increase α-secretase activity, thereby suppressing Aß production. Since Aß42 oligomer formation causes potent neurotoxicity, APP modulation by PKC ligands is a promising strategy for AD treatment. Although bryostatin-1 (bryo-1) is a leading compound for this strategy, its limited natural availability and the difficulty of its total synthesis impedes further research. To address this limitation, Irie and colleagues have developed a new PKC activator with few side effects, 10-Me-Aplog-1, (1), which decreased Aß42 in the conditioned medium of rat primary cerebral cortex cells. These results are associated with increased α-secretase but not PKCε-dependent Aß-degrading enzyme. The amount of neuronal embryonic lethal abnormal vision (nELAV), a known ß-secretase stabilizer, was reduced by treatment with 1. Notably, 1 prevented the formation of intracellular toxic oligomers. Furthermore, 1 suppressed toxic oligomerization within human iPS-derived neurons such as bryo-1. Given that 1 was not neurotoxic toward either cell line, these findings suggest that 1 is a potential drug lead for AD therapy.

Comparison of the potential mechanisms for hepatotoxicity of p-dialkoxy chlorobenzenes in rat primary hepatocytes for read-across.

Read-across based on only structural similarity is considered to have a risk of error in chemical risk assessment. Under these circumstances, considering biological similarity based on adverse outcome pathways using in vitro omics technologies is expected to enhance the accuracy and robustness of conclusions in read-across. However, due to a lack of practical case studies, key considerations and use of these technologies for data gap filling are not well discussed. Here we extracted and compared the potential mechanisms for hepatotoxicity for structural analogs of p-dialkoxy chlorobenzenes including 1,4-dichloro-2,5-dimethoxybenzene (DDMB), 2,5-dichloro-1,4-diethoxybenzene (DDEB), 2-chloro-1,4-dimethoxybenzene (CDMB), and 1-chloro-2,5-diethoxybenzene (CDEB) using in vitro omics technologies for read-across. To reveal the potential mechanisms for hepatotoxicity, we conducted microarray analysis with rat primary hepatocytes. The results showed that three (DDMB, DDEB, CDEB) of the four chemicals affected similar biological pathways such as peroxisome proliferation, oxidative stress, and mitochondrial dysfunction. Furthermore, these biological pathways are consistent with in vivo hepatotoxicity in the source chemical, DDMB. In contrast, CDMB did not affect a specific toxicological pathway. Taken together, these data show the potential mechanisms for hepatotoxicity for three chemicals (DDMB, DDEB, CDEB) and provide novel insights into grouping chemicals using in vitro toxicogenomics for read-across.

Increased CCL6 expression in astrocytes and neuronal protection from neuron-astrocyte interactions.

Astrocytes have been reported to exhibit neuroprotective action via various chemokines. Reports of the chemokine CCL6 in central nervous system cells show expression in cultured microglia, but many unexplained effects on neurons and astrocytes remain. In this study, cultured cerebral cortical neurons, astrocytes, and a mixed culture system were constructed, and expression levels of CCL6 and its effects on glutamate neurotoxicity were examined. When neuron cultures and neuron-astrocyte mixed cultures were treated with glutamate, neuronal cell death was observed in both, but was induced by lower concentrations of glutamate in monocultured neurons. In addition, pretreatment of neuron cultures with conditioned media from neuron-astrocyte mixed cultures inhibited glutamate neurotoxicity. CCL6 expression was not observed in fluorescence activated cell sorting analyses of neuron and astrocyte cultures, but was observed in astrocytes from cocultures of neurons and astrocytes. Higher CCL6 concentrations were found in media from cocultures of neurons and astrocytes than in culture media from neuron cultures. Pretreatment of neuron cell cultures with CCL6 for 24 h also protected against glutamate neurotoxicity. This protective effect was suppressed by an antagonist of the chemokine receptor CCR1. Furthermore, glutamate neurotoxicity in mixed neuron and astrocyte cultures was enhanced by pretreatments with the CCR1 antagonist. Finally, cotreatments with the phosphatidylinositol-3 kinase (PI3K) inhibitor and CCL6 abolished the neuroprotective effects of CCL6. These data suggest that astrocytes protect neurons by activating CCR1 in neurons. Moreover, this neuroprotective action of astrocyte CCL6 is mediated by CCR1, and downstream by PI3K.

Donepezil modulates amyloid precursor protein endocytosis and reduction by up-regulation of SNX33 expression in primary cortical neurons.

Donepezil, a therapeutic drug for Alzheimer's disease, ameliorates cognitive dysfunction through selective inhibition of acetylcholinesterase. However, recent studies have also reported off-target effects of donepezil that likely contribute to its therapeutic effects. In this study, we investigated the (i) role of donepezil in amyloid precursor protein (APP) processing and (ii) involvement of sorting nexin protein 33 (SNX33), a member of the sorting nexin protein family, in this processing. Results showed that donepezil induces an increase in SNX33 expression in primary cortical neurons. The secretion of sAPPα in culture media increased, whereas the expression of full-length APP in the cell lysate remained unchanged. Exposure of cortical cultures to donepezil led to a decrease in amyloid ß (Aß) protein levels in a concentration- and time-dependent manner. This decrease was not affected by concomitant treatment with acetylcholine receptor antagonists. SNX33 knockdown by target-specific morpholino oligos inhibited the effects of donepezil. Donepezil treatment increased cell membrane surface expression of APP in SNX33 expression-dependent manner. These results suggested that donepezil decreases the level of Aß by increasing SNX33 expression and APP cleavage by α-secretase in cortical neurons.

Syndrome of inappropriate antidiuretic hormone secretion as a side effect of chemotherapy for testicular cancer: A case report.

INTRODUCTION: Inappropriate antidiuretic hormone secretion syndrome can be a serious adverse event of cisplatin-based chemotherapy. Cisplatin had to be changed to other drugs or chemotherapy completely discontinued in earlier reported cases. CASE PRESENTATION: Three cycles of bleomycin, etoposide, and cisplatin chemotherapy were planned for a 40-year-old man with a diagnosis of lymph node recurrence of testicular cancer. On day 9, he suffered from vomiting and mental disturbance. Severe hyponatremia (110 mEq/L) with low plasma osmolality led to a diagnosis of a syndrome of inappropriate antidiuretic hormone secretion, and infusions of hypertonic saline and salt intake were prescribed. Second and third courses of bleomycin, etoposide, and cisplatin chemotherapy could then be given with careful electrolyte management. CONCLUSION: Continuation of cisplatin administration with precise electrolyte adjustment can be a treatment option in regimens where cisplatin is essential for achieving optimal antitumor efficacy.

In vitro production of insulin-responsive skeletal muscle tissue from mouse embryonic stem cells by spermine-induced differentiation method.

The treatment of an embryoid body with spermine for a short duration can trigger the generation of a 3-dimensional multilayer myotube sheet (MMTS) that shows pulsatile activity. MMTS was previously characterized as a model of skeletal muscle tissue. In the present work, the insulin responsiveness of MMTS was investigated because it is an essential function for a model of skeletal muscle. The glucose uptake activity of MMTS was analyzed by confocal microscopy using fluorescent glucose analogs, namely 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy-D-glucose (2-NBDG) and its L-glucose counterpart, 2-NBDLG. The specific uptake rate of glucose was estimated from the difference between the fluorescent signals of 2-NBDG and 2-NBDLG. It was enhanced by insulin stimulation to 3.6 times higher than the control without insulin, and this insulin responsiveness was maintained for 5 days. The advantages of the 3-dimensional structure of MMTS are discussed in the contexts of its potential in vivo and in vitro uses.

Inhibitory effect of donepezil on bradykinin-induced increase in the intracellular calcium concentration in cultured cortical astrocytes.

Donepezil is a potent and selective acetylcholinesterase inhibitor developed for the treatment of Alzheimer's disease. In the present study, we investigated the responses of astrocytes to bradykinin, an inflammatory mediator, and the effect of donepezil on these responses using cultured cortical astrocytes. Bradykinin induced a transient increase of intracellular calcium concentration ([Ca2+]i) in cultured astrocytes. Bradykinin-induced [Ca2+]i increase was inhibited by the exposure to thapsigargin, which depletes Ca2+ stores on endoplasmic reticulum, but not by the exclusion of extracellular Ca2+. Twenty four hours pretreatment of donepezil reduced the bradykinin-induced [Ca2+]i increase. This reduction was inhibited not only by mecamylamine, a nAChR antagonist, but also by PI3K and Akt inhibitors. In addition, donepezil inhibited bradykinin-induced increase of the intracellular reactive oxygen species level in astrocytes. These results suggest that donepezil inhibits the inflammatory response induced by bradykinin via nAChR and PI3K-Akt pathway in astrocytes.

DJ-1 activates SIRT1 through its direct binding to SIRT1.

The DJ-1 gene is a ras-dependent oncogene and also a causative gene for a familial form of Parkinson's disease park7. DJ-1 is a multi-functional protein and plays roles in regulation of cell growth, cells death, metabolism and mitochondrial homeostasis against oxidative stress. To explore various functions, DJ-1 associates with a number of proteins localized in the nucleus, cytoplasm and mitochondria. The oxidative status of a cysteine residue at an amino acid number 106 (C106) of DJ-1 determines the active level of DJ-1. Precise molecular mechanism of exploration of DJ-1 function is, however, not resolved. In this study, we identified Sirtuin family proteins (SIRT1, 2, and 4-6) as DJ-1-binding proteins, and DJ-1 associated with SIRT1 in cells. Sirtuins like DJ-1 also regulates growth, death and metabolism of cells and mitochondrial homeostasis. We found that DJ-1 stimulated deacetylase activity of SIRT1 and that SIRT1-suppressed transcriptional activity of SIRT1-target p53 was further decreased by DJ-1. Furthermore, SIRT1 activity was reduced in DJ-1-knockout cells, and this reduced activity was restored by re-introduction of wild-type DJ-1 but not of C106-mutant DJ-1 into DJ-1-knockout cells. It is first report showing direct connection of DJ-1 with SIRT1.