Insecticidal activities of a Diospyros kaki root-isolated constituent and its derivatives against Nilaparvata lugens and Laodelphax striatellus

a b s t r a c t a r t i c l e i n f o Diospyros kaki root-derived materials were examined for insecticidal properties against Nilaparvata lugens and Laodelphax striatellus. Based on the LD 50 values, the chloroform fraction of D. kaki extracts showed the most activity against N. lugens (3.78 μg/female) and L. striatellus (7.32 μg/female). The active constituent of the chloroform fraction was isolated by various chromatographic methods and was identified as 5-hydroxy-2-methyl-1,4-naphthoquinone by spectroscopic analyses. To establish the structure-activity relationships, the insecticidal effects of 5-hydroxy-2-methyl-1,4-naphthoquinone and its derivatives against N. lugens and L. striatellus were determined using micro-topical application bioassays. On the basis of LD 50 values, 5-hydroxy-1,4-naphthoquinone was the most effective against N. lugens (0.072 μg/female) and L. striatellus (0.183 μg/ female). 2-Bromo-1,4-naphthoquinone, 2-hydroxy-1,4-naphthoquinone, and 5-hydroxy-2-methyl-1,4-naphthoquinone also had potent insecticidal activities against N. lugens and L. striatellus. In contrast, no insecticidal activity was observed with 2-methoxy-1,4-naphthoquinone or 2-methyl-1,4-naphthoquinone. These results indicate that the functional group (bromo-and hydroxyl-) at the C-2 position of the 1,4-naphthoquinone skeleton and the change in position of the hydroxyl group play important roles in insecticidal activity. Therefore, naturally occurring D. kaki root-derived 5-hydroxy-2-methyl-1,4-naphthoquinone and its derivatives may be suitable as insecticides

Successful Treatment of Epstein-Barr Virus-Associated Hemophagocytic Lymphohistiocytosis with HLH-94 Protocol

Hemophagocytic lymphohistiocytosis (HLH) is a rare, fatal disorder of children, affecting predominantly the mononuclear phagocytic system. Previous reports indicate that Epstein-Barr virus (EBV)-associated hemophagocytic lymphohistiocytosis (EBV-HLH) can also be fatal in many cases, although the prognosis for EBV-HLH is better than for the familial form of hemophagocytic lymphohistiocytosis. We treated four patients with EBV-HLH using immunochemotherapy including steroid, etoposide (VP-16), and cyclosporin, according to the HLH-94 protocol. All patients experienced persistent fever, cytopenia, and hypertriglyceridemia. Serological testing for EBV showed reactivated EBV infections in all patients. EBV DNA detected by PCR and EBV-encoded small RNA measured by in situ hybridization were confirmed in the patients' bone marrow specimens. Hemophagocytosis was shown in bone marrow aspirates and liver biopsy specimen. Complete remission was achieved in all patients after induction and continuation therapy for 4-10 months (median, 7 months) and was maintained for 15-27 months (median, 19 months) without the need for bone marrow transplantation. These results suggest that EBV-HLH can be effectively controlled by immunochemotherapy using the HLH-94 protocol

Precise Temperature Mapping of GaN-Based LEDs by Quantitative Infrared Micro-Thermography

A method of measuring the precise temperature distribution of GaN-based light-emitting diodes (LEDs) by quantitative infrared micro-thermography is reported. To reduce the calibration error, the same measuring conditions were used for both calibration and thermal imaging; calibration was conducted on a highly emissive black-painted area on a dummy sapphire wafer loaded near the LED wafer on a thermoelectric cooler mount. We used infrared thermal radiation images of the black-painted area on the dummy wafer and an unbiased LED wafer at two different temperatures to determine the factors that degrade the accuracy of temperature measurement, i.e., the non-uniform response of the instrument, superimposed offset radiation, reflected radiation, and emissivity map of the LED surface. By correcting these factors from the measured infrared thermal radiation images of biased LEDs, we determined a precise absolute temperature image. Consequently, we could observe from where the local self-heat emerges and how it distributes on the emitting area of the LEDs. The experimental results demonstrated that highly localized self-heating and a remarkable temperature gradient, which are detrimental to LED performance and reliability, arise near the p-contact edge of the LED surface at high injection levels owing to the current crowding effect

Genomic profile analysis of diffuse-type gastric cancers

Background: Stomach cancer is the third deadliest among all cancers worldwide. Although incidence of the intestinal-type gastric cancer has decreased, the incidence of diffuse-type is still increasing and its progression is notoriously aggressive. There is insufficient information on genome variations of diffuse-type gastric cancer because its cells are usually mixed with normal cells, and this low cellularity has made it difficult to analyze the genome. Results: We analyze whole genomes and corresponding exomes of diffuse-type gastric cancer, using matched tumor and normal samples from 14 diffuse-type and five intestinal-type gastric cancer patients. Somatic variations found in the diffuse-type gastric cancer are compared to those of the intestinal-type and to previously reported variants. We determine the average exonic somatic mutation rate of the two types. We find associated candidate driver genes, and identify seven novel somatic mutations in CDH1, which is a well-known gastric cancer-associated gene. Three-dimensional structure analysis of the mutated E-cadherin protein suggests that these new somatic mutations could cause significant functional perturbations of critical calcium-binding sites in the EC1-2 junction. Chromosomal instability analysis shows that the MDM2 gene is amplified. After thorough structural analysis, a novel fusion gene TSC2-RNF216 is identified, which may simultaneously disrupt tumor-suppressive pathways and activate tumorigenesis. Conclusions: We report the genomic profile of diffuse-type gastric cancers including new somatic variations, a novel fusion gene, and amplification and deletion of certain chromosomal regions that contain oncogenes and tumor suppressors.open121

Analysis of Hemodialysis-Associated Hypoglycemia in Patients with Type 2 Diabetes Using a Continuous Glucose Monitoring System

Background: Adequate glycemic control is important for patients with end-stage renal disease on maintenance hemodialysis (HD). Continuous glucose monitoring (CGM) systems are reported as a useful method for glucose monitoring in patients under maintenance HD. The object of this study was to describe glucose profiles and hypoglycemia associated with HD in diabetes patients using a CGM system. Methods: We recruited nine medically stable patients with type 2 diabetes under maintenance HD. CGMS (R) System Gold (R) (Medtronic MiniMed, Northridge, CA) was applied to the subjects for 144 h. During the period, HD using glucose-containing dialysate was performed every other day. Various glucose profiles were calculated from the CGM readings and compared between the day on and the day off dialysis. Results: Mean +/- SD for age, duration of diabetes, and hemoglobin A1c were 67 +/- 9 years, 24 +/- 9 years, and 8.6 +/- 1.2%, respectively. Hemoglobin A1c was correlated with mean glucose (rho = 0.780, P < 0.05) and with area under the curve for glucose above 180 mg/ dL (rho = 0.797, P < 0.05). Although there was no difference for mean amplitude of glycemic excursion between the day on and off HD, hypoglycemia occurred predominantly with day on HD. In the subjects who maintained antidiabetes agents with day on HD, glucose levels decreased with initiation of HD, causing significantly lower glucose levels compared to those during the equivalent time of the following day without HD. Conclusions: According to the CGM system, glucose variability was not affected by HD. However, in spite of glucose-containing dialysate, HD seemed to increase the risk of hypoglycemia.This study was supported by a grant from the Korea Science and Engineering Foundation (KOSEF) (0521-20080010) by the Ministry of Education, Science and Technology (MEST), by a grant from the Innovative Research Institute for Cell Therapy (A062260) by the Ministry of Health and Welfare, Republic of Korea, and by WCU project (R31-2008-000- 10103-0) of the MEST and the KOSEF.*INT DIAB FED, 2010, DIAB ATL*AM DIAB ASS, 2010, DIABETES CARE S1, V33, pS4Drechsler C, 2009, CIRCULATION, V120, P2421, DOI 10.1161/CIRCULATIONAHA.109.857268Riveline JP, 2009, NEPHROL DIAL TRANSPL, V24, P2866, DOI 10.1093/ndt/gfp181Kazempour-Ardebili S, 2009, DIABETES CARE, V32, P1137, DOI 10.2337/dc08-1688Kohnert KD, 2009, DIABETES CARE, V32, P1058, DOI 10.2337/dc08-1956SHIM Y, 2009, KOREAN J NUTR, V42, P577Tamborlane WV, 2008, NEW ENGL J MED, V359, P1464Wentholt IME, 2008, DIABETOLOGIA, V51, P183, DOI 10.1007/s00125-007-0842-6*US REN DAT SYST, 2008, USRSD 2008 ANN DAT RKohnert KD, 2007, DIABETES RES CLIN PR, V77, P420, DOI 10.1016/j.diabres.2007.01.021Burmeister JE, 2007, NEPHROL DIAL TRANSPL, V22, P1184, DOI 10.1093/ndt/gfl710Williams ME, 2006, KIDNEY INT, V70, P1503, DOI 10.1038/sj.ki.5001789Monnier L, 2006, JAMA-J AM MED ASSOC, V295, P1681Sangill M, 2006, AM J KIDNEY DIS, V47, P636, DOI 10.1053/j.ajkd.2006.01.007Rigalleau V, 2005, CURR OPIN CLIN NUTR, V8, P463Childs BP, 2005, DIABETES CARE, V28, P1245TANSEY MJ, 2005, DIABETES TECHNOL THE, V7, P109Loipl J, 2005, RENAL FAILURE, V27, P305, DOI 10.1081/JDI-200056608Cryer PE, 2003, DIABETES CARE, V26, P1902Djakoure-Platonoff C, 2003, DIABETES METAB, V29, P159Guerci B, 2003, DIABETES CARE, V26, P582*DIRECNET STUD GRO, 2003, DIABETES TECHNOL THE, V5, P781Boland E, 2001, DIABETES CARE, V24, P1858Morioka T, 2001, DIABETES CARE, V24, P909Kovatchev BP, 2000, J CLIN ENDOCR METAB, V85, P4287Jackson MA, 2000, CLIN NEPHROL, V54, P30Haviv YS, 2000, RENAL FAILURE, V22, P219Mastrototaro J, 1999, J PEDIATR ENDOCR MET, V12, P751Nakao T, 1998, INTERNAL MED, V37, P8261998, LANCET, V352, P837Davis SN, 1997, DIABETES, V46, P1328Morgan L, 1996, DIABETIC MED, V13, P5141993, N ENGL J MED, V329, P977MITRAKOU A, 1991, AM J PHYSIOL, V260, pE67DEFEO P, 1988, J CLIN INVEST, V82, P436SCHWARTZ NS, 1987, J CLIN INVEST, V79, P777SERVICE FJ, 1970, DIABETES, V19, P644

Personalized HRTF Modeling Based on Deep Neural Network Using Anthropometric Measurements and Images of the Ear

This paper proposes a personalized head-related transfer function (HRTF) estimation method based on deep neural networks by using anthropometric measurements and ear images. The proposed method consists of three sub-networks for representing personalized features and estimating the HRTF. As input features for neural networks, the anthropometric measurements regarding the head and torso are used for a feedforward deep neural network (DNN), and the ear images are used for a convolutional neural network (CNN). After that, the outputs of these two sub-networks are merged into another DNN for estimation of the personalized HRTF. To evaluate the performance of the proposed method, objective and subjective evaluations are conducted. For the objective evaluation, the root mean square error (RMSE) and the log spectral distance (LSD) between the reference HRTF and the estimated one are measured. Consequently, the proposed method provides the RMSE of &#8722;18.40 dB and LSD of 4.47 dB, which are lower by 0.02 dB and higher by 0.85 dB than the DNN-based method using anthropometric data without pinna measurements, respectively. Next, a sound localization test is performed for the subjective evaluation. As a result, it is shown that the proposed method can localize sound sources with higher accuracy of around 11% and 6% than the average HRTF method and DNN-based method, respectively. In addition, the reductions of the front/back confusion rate by 12.5% and 2.5% are achieved by the proposed method, compared to the average HRTF method and DNN-based method, respectively

Multi-Task Learning U-Net for Single-Channel Speech Enhancement and Mask-Based Voice Activity Detection

In this paper, a multi-task learning U-shaped neural network (MTU-Net) is proposed and applied to single-channel speech enhancement (SE). The proposed MTU-based SE method estimates an ideal binary mask (IBM) or an ideal ratio mask (IRM) by extending the decoding network of a conventional U-Net to simultaneously model the speech and noise spectra as the target. The effectiveness of the proposed SE method was evaluated under both matched and mismatched noise conditions between training and testing by measuring the perceptual evaluation of speech quality (PESQ) and short-time objective intelligibility (STOI). Consequently, the proposed SE method with IRM achieved a substantial improvement with higher average PESQ scores by 0.17, 0.52, and 0.40 than other state-of-the-art deep-learning-based methods, such as the deep recurrent neural network (DRNN), SE generative adversarial network (SEGAN), and conventional U-Net, respectively. In addition, the STOI scores of the proposed SE method are 0.07, 0.05, and 0.05 higher than those of the DRNN, SEGAN, and U-Net, respectively. Next, voice activity detection (VAD) is also proposed by using the IRM estimated by the proposed MTU-Net-based SE method, which is fundamentally an unsupervised method without any model training. Then, the performance of the proposed VAD method was compared with the performance of supervised learning-based methods using a deep neural network (DNN), a boosted DNN, and a long short-term memory (LSTM) network. Consequently, the proposed VAD methods show a slightly better performance than the three neural network-based methods under mismatched noise conditions

Two-Step Joint Optimization with Auxiliary Loss Function for Noise-Robust Speech Recognition

In this paper, a new two-step joint optimization approach based on the asynchronous subregion optimization method is proposed for training a pipeline model composed of two different models. The first-step processing of the proposed joint optimization approach trains the front-end model only, and the second-step processing trains all the parameters of the combined model together. In the asynchronous subregion optimization method, the first-step processing only supports the goal of the front-end model. However, the first-step processing of the proposed approach works with a new loss function to make the front-end model support the goal of the back-end model. The proposed optimization approach was applied, here, to a pipeline composed of a deep complex convolutional recurrent network (DCCRN)-based speech enhancement model and a conformer-transducer-based ASR model as a front-end and a back-end, respectively. Then, the performance of the proposed two-step joint optimization approach was evaluated on the LibriSpeech automatic speech recognition (ASR) corpus in noisy environments by measuring the character error rate (CER) and word error rate (WER). In addition, an ablation study was carried out to examine the effectiveness of the proposed optimization approach on each of the processing blocks in the conformer-transducer ASR model. Consequently, it was shown from the ablation study that the conformer-transducer-based ASR model with the joint network trained only by the proposed optimization approach achieved the lowest average CER and WER. Moreover, the proposed optimization approach reduced the average CER and WER on the Test-Noisy dataset under matched noise conditions by 0.30% and 0.48%, respectively, compared to the approach of separate optimization of speech enhancement and ASR. Compared to the conventional two-step joint optimization approach, the proposed optimization approach provided average CER and WER reductions of 0.22% and 0.31%, respectively. Moreover, it was revealed that the proposed optimization approach achieved a lower average CER and WER, by 0.32% and 0.43%, respectively, than the conventional optimization approach under mismatched noise conditions