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3. Evaluation of antidepressant properties of hydroalcoholic extract of Aegle marmelos fruit (Bael fruit) in Swiss albino mice: A pre-clinical study

Author

Shefeek SN, Sridevi K, Nagapati P Bhat, and Roopa P Nayak

Subjects
aegle marmelos fruit, anti-depressants, forced swimming test, tail suspension test, Medicine
Abstract

Introduction: Depression is a prevalent psychiatric disorder affecting 3.8% of the global population. The clinically available antidepressants can cause serious adverse effects. Aegle marmelos fruit has shown a wide range of pharmacological effects. The present study was carried out to elucidate the possible antidepressant activity of Aegle marmelos (Bael) fruit in Swiss albino mice. Objective: To evaluate the possible antidepressant activity of Aegle marmelos fruit extract in Swiss albino mice. Methods: A total of 30 (n=30) male Swiss albino mice weighing 25-35 g, divided into five groups of six animals each were used for the study. Aegle marmelos fruit powder was subjected to solvent extraction in a soxhlet apparatus. The antidepressant activity of the hydroalcoholic extract of Aegle marmelos fruit was evaluated by using two models –Forced Swimming Test (FST) and Tail Suspension Test (TST). Results: One-way ANOVA was used for multiple comparisons followed by a post hoc (Bonferroni test) for comparison between groups. Aegle marmelos fruit at the dose of 100mg/kg and 200 mg/kg significantly reduced the immobility time in both the tests (TST and FST) compared to the control. The reduction in duration of immobility at the dose of 200 mg/kg was comparable to the standard drug Imipramine. Conclusion: The Hydroalcoholic extract of Aegle marmelos has significant antidepressant activity in both the animal models of depression (FST and TST).

Published
2023
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5. Health systems performance for hypertension control using a cascade of care approach in South Africa, 2011-2017.

Author

Mariet Benade, Zandile Mchiza, Rafeya V Raquib, Sridevi K Prasad, Lily D Yan, Alana T Brennan, Justine Davies, Nikkil Sudharsanan, Jennifer Manne-Goehler, Matthew P Fox, Jacob Bor, Sydney B Rosen, and Andrew C Stokes

Subjects
Public aspects of medicine, RA1-1270
Abstract

Hypertension is a major contributor to global morbidity and mortality. In South Africa, the government has employed a whole systems approach to address the growing burden of non-communicable diseases. We used a novel incident care cascade approach to measure changes in the South African health system's ability to manage hypertension between 2011 and 2017. We used data from Waves 1-5 of the National Income Dynamics Study (NIDS) to estimate trends in the hypertension care cascade and unmet treatment need across four successive cohorts with incident hypertension. We used a negative binomial regression to identify factors that may predict higher rates of hypertension control, controlling for socio-demographic and healthcare factors. In 2011, 19.6% (95%CI 14.2, 26.2) of individuals with incident hypertension were diagnosed, 15.4% (95%CI 10.8, 21.4) were on treatment and 7.1% had controlled blood pressure. By 2017, the proportion of individuals with diagnosed incident hypertension had increased to 24.4% (95%CI 15.9, 35.4). Increases in treatment (23.3%, 95%CI 15.0, 34.3) and control (22.1%, 95%CI 14.1, 33.0) were also observed, translating to a decrease in unmet need for hypertension care from 92.9% in 2011 to 77.9% in 2017. Multivariable regression showed that participants with incident hypertension in 2017 were 3.01 (95%CI 1.77, 5.13) times more likely to have a controlled blood pressure compared to those in 2011. Our data show that while substantial improvements in the hypertension care cascade occurred between 2011 and 2017, a large burden of unmet need remains. The greatest losses in the incident hypertension care cascades came before diagnosis. Nevertheless, whole system programming will be needed to sufficiently address significant morbidity and mortality related to having an elevated blood pressure.

Published
2023
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7. Machine learning predicts nucleosome binding modes of transcription factors

Author

K. C. Kishan, Sridevi K. Subramanya, Rui Li, and Feng Cui

Subjects
Machine learning, Nucleosome binding modes, Transcription factors, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Most transcription factors (TFs) compete with nucleosomes to gain access to their cognate binding sites. Recent studies have identified several TF-nucleosome interaction modes including end binding (EB), oriented binding, periodic binding, dyad binding, groove binding, and gyre spanning. However, there are substantial experimental challenges in measuring nucleosome binding modes for thousands of TFs in different species. Results We present a computational prediction of the binding modes based on TF protein sequences. With a nested cross-validation procedure, our model outperforms several fine-tuned off-the-shelf machine learning (ML) methods in the multi-label classification task. Our binary classifier for the EB mode performs better than these ML methods with the area under precision-recall curve achieving 75%. The end preference of most TFs is consistent with low nucleosome occupancy around their binding site in GM12878 cells. The nucleosome occupancy data is used as an alternative dataset to confirm the superiority of our EB classifier. Conclusions We develop the first ML-based approach for efficient and comprehensive analysis of nucleosome binding modes of TFs.

Published
2021
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8. Rapid evidence assessment of the impacts of sewerage, drainage, and piped water chlorination in urban settings of low- and middle-income countries

Author

Sridevi K. Prasad, Charlotte Lane, and Douglas Glandon

Subjects
chlorination, drainage, impact, lmic, sewerage, wash, Environmental technology. Sanitary engineering, TD1-1066
Abstract

The aim of this review was to rapidly synthesize the available evidence regarding the expected impacts of piped water chlorination, drainage, and sewerage on individuals living in low- and middle-income urban settings. A systematic search was conducted in bibliographic databases and library catalogs. Impact evaluations that included a comparator and one of the three interventions of interest, attempted to control for confounding and selection bias, and took place in urban settings in a low- or middle-income country were considered. Outcomes related to health, well-being, economic growth, and the bacterial content of water were considered. A total of 1,483 articles were identified, with 18 included after final screening. Most studies were case-control and took place in Brazil, the Pacific Islands, or south-western Asia. Fifteen studies considered sewerage, five considered chlorination, and two studies considered drainage with some studies considering multiple interventions. All primary outcomes were related to health. When implemented alone, the sewerage and chlorination interventions were largely successful. The evidence regarding the effects of chlorination, drainage, and sewerage interventions is limited and generally has a high risk of bias. When properly implemented, sewerage and chlorination are likely to have positive health impacts. However, when implemented poorly, all three interventions can have negative health impacts. HIGHLIGHTS Most studies focused on sewerage interventions.; Chlorination and sewerage interventions were successful in reducing disease burden.; Contamination sources included lack of improved WaSH, sources in the nearby environment, and household hygiene practices.; Infrastructure maintenance issues affected the interventions’ impacts.; Proper household hygiene practices should be included for effective interventions.;

Published
2021
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10. A Systematic Approach of Advanced Dilated Convolution Network for Speaker Identification

Author

Hema Kumar Pentapati and Sridevi K

Subjects
Electrical and Electronic Engineering, Engineering (miscellaneous)
Abstract

Over the years, the Speaker recognition area is facing various challenges in identifying the speakers accurately. Remarkable changes came into existence with the advent of deep learning algorithms. Deep learning made a remarkable impact on the speaker recognition approaches. This paper introduces a simple novel architectural approach to an advanced Dilated Convolution network. The novel idea is to induce the well-structured log-Melspectrum to the proposed dilated convolution neural network and reduce the number of layers to 11. The network utilizes the Global average pooling to accumulate the outputs from all layers to get the feature vector representation for classification. Only 13 coefficients are extracted per frame of each speech sample. This novel dilated convolution neural network exhibits an accuracy of 90.97%, Equal Error Rate(EER) of 3.75% and 207 Seconds training time outperforms the existing systems on the LibriSpeech corpus.

Published
2023
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11. Enhancement in Speaker Identification through Feature Fusion using Advanced Dilated Convolution Neural Network

Author

Hema Kumar Pentapati and Sridevi K

Subjects
Computer Networks and Communications, Hardware and Architecture, Electrical and Electronic Engineering, Log-MelSpectrum, MFCC, Speaker Identification, excitation features, Convolution Neural Network(CNN), LP Residual, deep learning, Deep Neural Network
Abstract

There are various challenges in identifying the speakers accurately. The Extraction of discriminative features is a vital task for accurate identification in the speaker identification task. Nowadays, speaker identification is widely investigated using deep learning. The complex and noisy speech data affects the performance of Mel Frequency Cepstral Coefficients (MFCC); hence, MFCC fails to represent the speaker characteristics accurately. In this proposed work, a novel text-independent speaker identification system is developed to enhance the performance by fusion of Log-MelSpectrum and excitation features. The excitation information is obtained due to the vibration of vocal folds, and it is represented using Linear Prediction (LP) residual. The various types of features extracted from the excitation are residual phase, sharpness, Energy of Excitation (EoE), and Strength of Excitation (SoE). The extracted features were processed with the dilated convolution neural network (dilated CNN) to fulfill the identification task. The extensive evaluation showed that the fusion of excitation features gives better results than the existing methods. The accuracy reaches 94.12% for 11 complex classes and 91.34% for 80 speakers, and Equal Error Rate (EER) is reduced to 1.16% for the proposed model. The proposed model is tested with the Librispeech corpus using Matlab 2021b tool, outperforming the existing baseline models. The proposed model achieves an accuracy improvement of 1.34% compared to the baseline system.

Published
2023
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12. Availability and affordability of blood pressure-lowering medicines and the effect on blood pressure control in high-income, middle-income, and low-income countries: an analysis of the PURE study data

Author

Yusuf, S, Rangarajan, S, Teo, K K, Chow, C K, O'Donnell, M, Mente, A, Leong, D, Smyth, A, Joseph, P, Islam, S, Zhang, M, Hu, W, Ramasundarahettige, C, Wong, G, Dayal, L, Casanova, A, Dehghan, M, Lewis, G, Aliberti, A, Reyes, A, Zaki, A, Lewis, B, Zhang, B, Agapay, D, Hari, D, Milazzo, E, Ramezani, E, Hussain, F, Shifaly, F, Kay, I, Rimac, J, Swallow, J, Heldman, L, Mushtaha, M(a), Mushtaha, M(o), Trottier, M, Aoucheva, N, Kandy, N, Mackie, P, Solano, R, Chin, S, Ramacham, S, Shahrook, S, Trottier, S, Tongana, T, ElSheikh, W, Lindeman, J, McQueen, M, Hall, K, Keys, J, Wang, X, Keneth, J, Devanath, A, Diaz, R, Orlandini, A, Linetsky, B, Toscanelli, S, Casaccia, G, Maini Cuneo, JM, Rahman, O, Yusuf, R, Azad, AK, Rabbani, KA, Cherry, HM, Mannan, A, Hassan, I, Talukdar, AT, Tooheen, RB, Khan, MU, Sintaha, M, Choudhury, T, Haque, R, Parvin, S, Avezum, A, Oliveira, GB, Marcilio, CS, Mattos, AC, Teo, K, Dejesus, J, Elsheikh, W, Dagenais, G, Poirier, P, Turbide, G, Auger, D, De Bluts, A LeBlanc, Proulx, MC, Cayer, M, Bonneville, N, Lear, S, Gasevic, D, Corber, E, de Jong, V, Vukmirovich, I, Wielgosz, A, Fodor, G, Pipe, A, Shane, A, Lanas, F, Seron, P, Martinez, S, Valdebenito, A, Oliveros, M, Wei, Li, Lisheng, Liu, Chunming, Chen, Xingyu, Wang, Wenhua, Zhao, Hongye, Zhang, JiaXuan, Bo, Hu, Yi, Sun, Jian, Bo, Xiuwen, Zhao, Xiaohong, Chang, Tao, Chen, Hui, Chen, Qing, Deng, Xiaoru, Cheng, Xinye, He, Jian, Li, Juan, Li, Xu, Liu, Bing, Ren, Wei, Wang, Yang, Wang, Jun, Yang, Yi, Zhai, Manlu, Zhu, Fanghong, Lu, Jianfang, Wu, Yindong, Li, Yan, Hou, Liangqing, Zhang, Baoxia, Guo, Xiaoyang, Liao, Shiying, Zhang, BianRongwen, TianXiuzhen, Dong, Li, Di, Chen, Jianguo, Wu, Yize, Xiao, Tianlu, Liu, Peng, Zhang, Changlin, Dong, Ning, Li, Xiaolan, Ma, Yuqing, Yang, Rensheng, Lei, Minfan, Fu, Jing, He, Yu, Liu, Xiaojie, Xing, Qiang, Zhou, Lopez-Jaramillo, P, Lopez, PA Camacho, Garcia, R, Jurado, LJA, Gómez-Arbeláez, D, Arguello, JF, Dueñas, R, Silva, S, Pradilla, LP, Ramirez, F, Molina, DI, Cure-Cure, C, Perez, M, Hernandez, E, Arcos, E, Fernandez, S, Narvaez, C, Paez, J, Sotomayor, A, Garcia, H, Sanchez, G, David, T, Rico, A, Mony, P, Vaz, M, Bharathi, A V, Swaminathan, S, Shankar, K, Kurpad, AV, Jayachitra, KG, Kumar, N, Hospital, HAL, Mohan, V, Deepa, M, Parthiban, K, Anitha, M, Hemavathy, S, Rahulashankiruthiyayan, T, Anitha, D, Sridevi, K, Gupta, R, Panwar, RB, Mohan, I, Rastogi, P, Rastogi, S, Bhargava, R, Kumar, R, Thakur, J S, Patro, B, Lakshmi, PVM, Mahajan, R, Chaudary, P, Kutty, V Raman, Vijayakumar, K, Ajayan, K, Rajasree, G, Renjini, AR, Deepu, A, Sandhya, B, Asha, S, Soumya, HS, Kelishadi, R, Bahonar, A, Mohammadifard, N, Heidari, H, Yusoff, K, Ismail, TST, Ng, KK, Devi, A, Nasir, NM, Yasin, MM, Miskan, M, Rahman, EA, Arsad, MKM, Ariffin, F, Razak, SA, Majid, FA, Bakar, NA, Yacob, MY, Zainon, N, Salleh, R, Ramli, MKA, Halim, NA, Norlizan, SR, Ghazali, NM, Arshad, MN, Razali, R, Ali, S, Othman, HR, Hafar, CWJCW, Pit, A, Danuri, N, Basir, F, Zahari, SNA, Abdullah, H, Arippin, MA, Zakaria, NA, Noorhassim, I, Hasni, MJ, Azmi, MT, Zaleha, MI, Hazdi, KY, Rizam, AR, Sazman, W, Azman, A, Khatib, R, Khammash, U, Khatib, A, Giacaman, R, Iqbal, R, Afridi, A, Khawaja, R, Raza, A, Kazmi, K, Dans, A, Co, HU, Sanchez, JT, Pudol, L, Zamora-Pudol, C, Palileo-Villanueva, LAM, Aquino, MR, Abaquin, C, Pudol, SL, Cabral, ML, Zatonski, W, Szuba, A, Zatonska, K, Ilow#, R, Ferus, M, Regulska-Ilow, B, Różańska, D, Wolyniec, M, AlHabib, KF, Hersi, A, Kashour, T, Alfaleh, H, Alshamiri, M, Altaradi, HB, Alnobani, O, Bafart, A, Alkamel, N, Ali, M, Abdulrahman, M, Nouri, R, Kruger, A, Voster, H H, Schutte, A E, Wentzel-Viljoen, E, Eloff, FC, de Ridder, H, Moss, H, Potgieter, J, Roux, AA, Watson, M, de Wet, G, Olckers, A, Jerling, JC, Pieters, M, Hoekstra, T, Puoane, T, Igumbor, E, Tsolekile, L, Sanders, D, Naidoo, P, Steyn, N, Peer, N, Mayosi, B, Rayner, B, Lambert, V, Levitt, N, Kolbe-Alexander, T, Ntyintyane, L, Hughes, G, Swart, R, Fourie, J, Muzigaba, M, Xapa, S, Gobile, N, Ndayi, K, Jwili, B, Ndibaza, K, Egbujie, B, Rosengren, A, Boström, K Bengtsson, Lindblad, U, Langkilde, P, Gustavsson, A, Andreasson, M, Snällman, M, Wirdemann, L, Pettersson, K, Moberg, E, Yeates, K, Sleeth, J, Kilonzo, K, Oguz, A, Akalin, AAK, Calik, KBT, Imeryuz, N, Temizhan, A, Alphan, E, Gunes, E, Sur, H, Karsidag, K, Gulec, S, Altuntas, Y, Yusufali, AM, Almahmeed, W, Swidan, H, Darwish, EA, Hashemi, ARA, Al-Khaja, N, Muscat-Baron, JM, Ahmed, SH, Mamdouh, TM, Darwish, WM, Abdelmotagali, MHS, Awed, SA Omer, Movahedi, GA, Shaibani, H Al, Gharabou, RIM, Youssef, DF, Nawati, AZS, Salah, ZAR Abu, Abdalla, RFE, Shuwaihi, SM Al, Omairi, MA Al, Cadigal, OD, Alejandrino, R.S., Chifamba, J, Gwaunza, L, Terera, G, Mahachi, C, Murambiwa, P, Machiweni, T, Mapanga, R, Attaei, Marjan W, Khatib, Rasha, McKee, Martin, Lear, Scott, Dagenais, Gilles, Igumbor, Ehimario U, AlHabib, Khalid F, Kaur, Manmeet, Kruger, Lanthe, Teo, Koon, Lanas, Fernando, Yusoff, Khalid, Oguz, Aytekin, Gupta, Rajeev, Yusufali, Afzalhussein M, Bahonar, Ahmad, Kutty, Raman, Rosengren, Annika, Mohan, Viswanathan, Avezum, Alvaro, Yusuf, Rita, Szuba, Andrzej, Rangarajan, Sumathy, Chow, Clara, and Yusuf, Salim

Published
2017
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17. Occurrence of Lead and Other Toxic Metals Derived from Drinking-Water Systems in Three West African Countries

Author

Fisher, Michael B., Guo, Amy Z., Tracy, J. Wren, Prasad, Sridevi K., Cronk, Ryan D., Browning, Emily G., Liang, Kaida R., Kelly, Emma R., and Bartram, Jamie K.

Subjects
Risk factors, Contamination, Health aspects, Environmental aspects, Lead (Metal) -- Health aspects -- Environmental aspects, Toxicity -- Risk factors, Drinking water -- Contamination -- Health aspects, Rural water supply -- Health aspects -- Environmental aspects -- Ghana -- Niger -- Mali, Water-supply, Rural -- Health aspects -- Environmental aspects -- Ghana -- Niger -- Mali, Lead -- Health aspects -- Environmental aspects
Abstract

Introduction The United Nations Sustainable Development Goal (SDG) Target 6.1 calls for 'universal and equitable access to safe and affordable drinking-water for all' (United Nations 2015) International policy defines 'safe' [...], Background: Exposure to toxic metals (TMs) such as lead can cause lifelong neurodevelopmental impairment and other adverse outcomes. TMs enter drinking water from human activity, geogenic contamination, and corrosion of water system components. Several studies report TM contamination in piped systems and private wells in high-income countries (HICs). However, few robust studies report on TM contamination in low- and middle-income countries (LMICs). Objectives: We characterized the occurrence and investigated sources of TM contamination in 261 rural water systems in three West African LMICs to inform prevention and management. Methods: Water samples were collected from 261 community water systems (handpumps and public taps) across rural Ghana, Mali, and Niger. Scrapings were collected from accessible components of a subset of these systems using a drill with acid-washed diamond-tipped bits. Samples were analyzed by inductively coupled plasma (ICP) mass spectrometry or ICP optical emission spectroscopy. Results: Of the TMs studied, lead most frequently occurred at levels of concern in sampled water system components and water samples. Lead mass fractions exceeded International Plumbing Code (IPC) recommended limits (0.25% wt/wt) for components in 82% (107/130) of systems tested; brass components proved most problematic, with 72% (26/36) exceeding IPC limits. Presence of a brass component in a water system increased expected lead concentrations in drinking-water samples by 3.8 times. Overall, lead exceeded World Health Organization (WHO) guideline values in 9% (24/261) of drinking-water samples across countries; these results are broadly comparable to results observed in many HICs. Results did not vary significantly by geography or system type. Discussion: Ensuring use of lead-free (

Published
2021
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18. Evaluation of Anti-Diabetic Activity of Zinc Oxide Nanoparticles of Gymnema sylvestre Extract on Wistar Rats

Author

Gotteparthi, Sravani, Kotaru, Manvitha, Krishnan, S. Ashok, Sridevi, K., Gotteparthi, Sravani, Kotaru, Manvitha, Krishnan, S. Ashok, and Sridevi, K.

Abstract

Diabetes mellitus is described as a metabolic disorder, which was characterised by high blood glucose levels, which were resulted due to insufficient insulin secretion. There were major complications related to diabetes mellitus. To evaluate the antidiabetic effect of Gymnema sylvestre Zinc Oxide Nanoparticles. Streptozotocin (STZ) of 50mg/kg is used for the induction of diabetes into Wistar rats. The animals were divided into 6 groups. Group-I represented as Control; Group-II represented as diabetic control (STZ ); Group-III represented as 5 mg/kg body weight of glibenclamide + diabetes; Group-IV represented as Gymnema sylvestre extract + diabetes; Group-V represented as 100 µg Gymnema sylvestre Zinc Oxide nanoparticles + diabetes; group-6-  Gymnema sylvestre Zinc Oxide Nanoparticles 200 µg + diabetes. The GsZnONPs were inspected to morphological properties using UV spectrophotometer and FTIR. The GsZnONPs shown characterization peak at 300nm. The study has shown that GsZnONPs treated group has shown reduced glucose concentration. The histo-pathological alterations were also studied in all experimental groups. The pathology results of GsZnONPs (200 µg) group has shown the regeneration of islets cells of pancreas. The research study has proved that Gymnema sylvestre ZnO NPs exerts antidiabetic properties. Keywords: Diabetes, Gymnema sylvestre, Zinc Oxide nanoparticles

Published
2023

19. Synthesis of sol-gel synthesized ZnO-CdO nanocomposite for photovoltaic applications.

Author

Sridevi, K. P., Revathi, V., Sangeethac, P., Manjunatha, B., and Sivakumar, S.

Subjects
*NANOCOMPOSITE materials, *CADMIUM oxide, *SEMICONDUCTOR synthesis, *TRANSMISSION electron microscopy, *SEMICONDUCTOR materials, *ZINC oxide
Abstract

Nanocomposites comprising semiconductor materials hold immense potential for advancing photovoltaic technologies due to their unique optoelectronic properties. This research focuses on the synthesis and characterization of a ZnO-CdO (zinc oxide and cadmium oxide) nanocomposite using the sol-gel method for potential application in photovoltaic devices. The sol-gel approach provides a versatile platform for tailoring material properties to enhance photovoltaic performance. The structural, morphological, and optical characteristics of the ZnO-CdO nanocomposite were extensively analyzed using techniques including X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and UV-visible spectroscopy. The XRD analysis confirmed the crystalline nature of the nanoparticles and assessed potential changes in their crystal structure upon nanocomposite formation. SEM and TEM images provided insights into particle size, shape, and distribution, corroborating successful nanocomposite fabrication. This study underscores the significance of sol-gel synthesis in tailoring semiconductor nanocomposites for photovoltaic applications. The characterized structural, optical, and photovoltaic properties provide a foundation for further optimization and integration into advanced photovoltaic devices. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Role of an Optimal Multiagent Scheduling in Different Applications Using ML

Author

Fahmina, Taranum, Sridevi, K, Maniza, Hijab, Fouzia, Sayeedunissa, Syeda, Afshan, Kaleem, and Niraja, K.S

Abstract

Scheduling is regarded as one of the vital decision-making processes used frequently in many real-time cases. It manages everything from resource allocation to the task completion, with the goal to optimize the desired objectives. Subject to the problem, the resources, tasks, and goals can differ. The aim is to design a corporative multiagent system for optimal scheduling. Many of the scheduling available algorithms calculate optimality based on different perspectives. The proposal is to create the dataset using multiple algorithms with different performance metrics to find an optimal one. This data can be imported into machine learning tools for training and predicting, based on the selected performance metrics. The algorithm considered in the empirical analysis includes first come first serve, Round robin, and Ant colony approach. The major finding shows that scheduling using Ant colony is an optimal algorithm, which is based on speed and velocity. The future extension would be to check the correctness of optimality using machine learning tools.

Published
2023
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23. AUTOIMPLANTATION – A SIMPLE AND EFFECTIVE TREATMENT OF MULTIPLE AND RESISTANT WARTS.

Author

BHARATHI, G., USHA, G., KUMARI, A.VIJAYA, and SRIDEVI, K.

Subjects
WARTS, HUMAN papillomavirus, HARVESTING, TREATMENT effectiveness, PATIENT monitoring, TOOTH transplantation
Abstract

Background: Treatment of multiple warts is one of the challenges dermatologists face because of their persistent and resistant nature. Patients with warts are treated with a variety of medical and surgical methods, but their resistance requires innovative treatment options to prevent recurrence. Auto-implantation is a simple procedure which is yielding good results after single treatment session. Aims and Objectives: To determine the efficacy of subcutaneous auto-implantation of wart tissue for the treatment of viral warts and to ascertain whether auto-implantation therapy reduces the number, size, and recurrence of warts. Materials and Methods: Between March 2021 and February 2022, 36 patients with persistent warts underwent homologous auto-implantation after harvesting full depth wart tissue. Patients were monitored for recurrence over a total period of six months. Results: Verrucae occurred most frequently in individuals aged 18 to 27 years (72.22%). With a male-to-female ratio of 2.27:1, more males were affected than females were infected in the current investigation. In the current study, common warts were the most common type with 18 cases (50%), followed by periungual warts in 9 cases (25%), palmar and plantar warts were observed in 6 cases (16.67%). Three patients (8.33%) had planar warts. In our study, the earliest response to auto-implantation therapy was observed after four weeks and most patients were cured of their lesions after 12 weeks. In current study, the average auto-implantation cure rate was 69.3%. Conclusion: Auto-implantation therapy is a safe, simple and effective treatment for resistant and multiple warts. Therefore multiple recalcitrant warts can be successfully treated with autoimplantation therapy. [ABSTRACT FROM AUTHOR]

Published
2023

24. Superficial dermatomycoses: a prospective clinico-mycological study

Author

Surekha A, Ramesh Kumar G, Sridevi K, Murthy DS, Usha G, and Bharathi G

Subjects
Superficial dermatomycoses, Dermatophytoses, Pityriasis versicolor, Candidal intertrigo, Medicine
Abstract

Background: Dermatomycoses are more prevalent in India due to favourable climatic conditions, poverty, poor hygiene and overcrowding. Sparse published data are available regarding superficial dermatomycoses from India. Methods: In this prospective study, demographic characteristics, clinical spectrum and risk factors for the development were studied in 198 patients with superficial dermatomycoses. Results: Their mean age was 34.1 ± 15.3 years; there were 108 (54.5%) males. Majority of the patients (50.5%) belonged to upper-lower socio-economic status (Class IV as per modified Kuppuswamy’s classification). Most of the patients (69.7%) had presented with dermatophytoses. Among superficial dermatomy-coses, tinea corporis was the most common (29.3%) clinical type. Potassium hydroxide mount was positive in 77.7% and culture was positive in 30.8%. Trichophyton rubrum was the most common species isolated (64%). Multivariable analysis using logistic regression revealed older age (> 50 years) to be an independent predictor for the development of tinea corporis (p

Published
2015
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27. Machine learning predicts nucleosome binding modes of transcription factors

Author

Kishan Kc, Feng Cui, Rui Li, and Sridevi K. Subramanya

Subjects
Machine learning, computer.software_genre, lcsh:Computer applications to medicine. Medical informatics, Biochemistry, Nucleosome occupancy, 03 medical and health sciences, 0302 clinical medicine, Structural Biology, Transcription factors, Nucleosome, Nucleosome binding modes, Amino Acid Sequence, Binding site, Molecular Biology, Transcription factor, lcsh:QH301-705.5, 030304 developmental biology, Physics, 0303 health sciences, Nucleosome binding, Binding Sites, business.industry, Applied Mathematics, Nucleosomes, Computer Science Applications, Binary classification, lcsh:Biology (General), lcsh:R858-859.7, Artificial intelligence, DNA microarray, business, computer, 030217 neurology & neurosurgery, Protein Binding, Research Article
Abstract

Background Most transcription factors (TFs) compete with nucleosomes to gain access to their cognate binding sites. Recent studies have identified several TF-nucleosome interaction modes including end binding (EB), oriented binding, periodic binding, dyad binding, groove binding, and gyre spanning. However, there are substantial experimental challenges in measuring nucleosome binding modes for thousands of TFs in different species. Results We present a computational prediction of the binding modes based on TF protein sequences. With a nested cross-validation procedure, our model outperforms several fine-tuned off-the-shelf machine learning (ML) methods in the multi-label classification task. Our binary classifier for the EB mode performs better than these ML methods with the area under precision-recall curve achieving 75%. The end preference of most TFs is consistent with low nucleosome occupancy around their binding site in GM12878 cells. The nucleosome occupancy data is used as an alternative dataset to confirm the superiority of our EB classifier. Conclusions We develop the first ML-based approach for efficient and comprehensive analysis of nucleosome binding modes of TFs.

Published
2021

32. Health systems performance for hypertension control using a cascade of care approach in South Africa, 2008-2017

Author

Sydney Rosen, Sridevi K. Prasad, Zandile Mchiza, Nikkil Sudharsanan, Andrew Stokes, Jennifer Manne-Goehler, Lily D. Yan, Matthew P. Fox, Jacob Bor, Mariet Benade, Alana T. Brennan, and Justine Davies

Subjects
education.field_of_study, Hypertension control, Population level, business.industry, Population, Human immunodeficiency virus (HIV), medicine.disease_cause, Whole systems, Unmet needs, Medicine, business, education, Treatment need, Demography, Healthcare system
Abstract

BackgroundHypertension is a major contributor to global morbidity and mortality. In South Africa, the government has employed a whole systems approach to address the growing burden of non-communicable diseases. We used a novel incident care cascade approach to measure changes in the South African health system’s ability to manage hypertension between 2008 and 2017.MethodsWe used data from Waves 1-5 of the National Income Dynamics Study (NIDS) to estimate trends in the hypertension care cascade and unmet treatment need across four successive cohorts with incident hypertension. We used a negative binomial regression to identify factors that may predict higher rates of hypertension control, controlling for socio-demographic and healthcare factors. The largest cascade attrition occurred prior to diagnosis.ResultsIn 2011, 19·6% (95%CI 14·2, 26·2) of individuals with incident hypertension were diagnosed, 15·4% (95%CI 10·8, 21·4) were on treatment and 7.1% had controlled blood pressure. By 2017, the proportion of individuals with diagnosed incident hypertension had increased to 24·4% (95%CI 15·9, 35·4) with increases in treatment (23·3%, 95%CI 15·0, 34·3) and control (22·1%, 95%CI 14·1, 33·.0) were also observed, translating to a decrease in unmet need from 92·9% in 2011 to 77·9% in 2017. Multivariable regression showed that participants with incident hypertension in 2017 were 3·01 (95%CI 1·77, 5·13) times more likely to have a controlled blood pressure compared to those in 2011.ConclusionsThe proportion of people with incident hypertension who successfully progressed to controlled blood pressure tripled between 2011 and 2017 in South Africa. Despite these improvements, a low absolute proportion of the population were able to control their blood pressure and a high burden of unmet need remains.Summary BoxWhat is already knownPrevalent cascades provide insight to where losses in care cascades occur.While mostly used in the management of HIV, recently they have also been adopted in studying the management of non-communicable diseases on a population level.Prevalent hypertension cascades in South Africa showed a high burden of unmet need, with the biggest losses where lost between disease development and diagnosis.What are the new findingsIncident hypertension cascades improved from 2008 to 2017 in South Africa.What do the new findings implyIncident cascades provide an improved means to measure changes in management cascades as this allows us to distinguish between historical and current health system performance.Our data show that while substantial improvements in the care cascade occurred between 2008 and 2017, a large burden of unmet need remains.

Published
2021
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33. Resource Optimized Security Coding In Light Weight Security Protocol

Author

Sridevi K

Subjects
General Computer Science, Mechanics of Materials, Electrical and Electronic Engineering, Civil and Structural Engineering
Abstract

The overhead for resource utilization in the round coding operation of security coding is large. Though lightweight protocols are used as a measure of provisioning, higher level of security in many real time applications, the need of key scheduling, key generation and s-box operation leads to large resource utilization. This resource consumption intern leads to large power consumption and area overhead. To minimize the resource utilization in this paper, a new resource optimization technique following resource reutilization scheme is proposed. The resource utilization is synchronized by the delay term instruction application in cryptography coding.

Published
2019
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34. An assessment of knowledge and attitude towards leprosy among undergraduate medical students

Author

Sridevi K, Chintaginjala Aruna, Senthil Kumar Al, Kameti Swapna, and Dvsb Ramamurthy

Subjects
medicine.medical_specialty, Bacterial disease, Transmission (medicine), business.industry, education, Stigma (botany), Disease, medicine.disease, World health, Test (assessment), Family medicine, medicine, Leprosy, Positive attitude, business
Abstract

Introduction: Inappropriate knowledge and erroneous beliefs about leprosy and the disabilities caused by the disease are the main reasons for the stigma attached to the disease. The current research was embarked to determine the knowledge and attitude of the medical students towards leprosy and to compare them between freshers and outgoing students and to know the effect of undergraduate medical teaching. Materials and Methods: This is a cross-sectional study done at a medical college in South India. The freshers and outgoing students were given a pre-contrived, pre-verified, organized questionnaire on leprosy. The results were analysed using percentage proportions, Z test and P-values. Results: The test was answered by 66 outgoing students and 129 freshers. Outgoing students had better knowledge about leprosy being a bacterial disease, mode of transmission, cardinal signs, diagnostic test, medications used in multi-drug therapy (MDT) and cause of deformity when compared to the first years with a statistically significant difference. But the knowledge regarding few signs and symptoms of leprosy, nerve commonly affected, medical emergency in leprosy, duration of World Health Organisation (WHO) recommended paucibacillary and muiltibacillary MDT, deformities, vaccines and prevention of the disease was inadequate. The knowledge of the outgoing students about the present day situation of leprosy in India was superior than their counterparts. All the outgoing students had positive attitude towards leprosy when compared to first years, which was statistically significant. Conclusion: The knowledge and attitude reflected in the data obtained from the students revealed the need for an increased emphasis on imparting adequate leprosy related knowledge. Keywords: Leprosy, Knowledge, Attitude, Medical students, Undergraduates. Introduction Leprosy is a chronic infective disease caused by Mycobacterium leprae and the main mode of transmission

Published
2019
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37. A Study on the Relationship Between Emotional Intelligence and Organisational Commitment in Manufacturing Sector With Special Reference to a Private Tea Manufacturing Company in Nilgiris

Author

et. al., Dr. Sridevi K B and et. al., Dr. Sridevi K B

Abstract

Emotional Intelligence is one of the most talked topics in the human resource domain today. Many organisations have recognized the importance of studying and analyzing the Emotional Intelligence of their employees as it helps the organisation in understanding their employees, solving critical interpersonal problems, curating appropriate training programs and on a broader basis helps improving productivity. The study involves in assessment of the relationship between Emotional Intelligence and Organisational Commitment in manufacturing sector with special reference to a private tea manufacturing company in Nilgiris with 60 employees. The factors of Emotional Intelligence that have a significant impact on Organisational Commitment have also been analyzed and insights have been obtained.

Published
2021

38. Fr336 RISK FACTORS FOR DEVELOPMENT OF PANCREATIC CANCER AMONG PATIENTS WITH CHRONIC PANCREATITIS: A CASE-CONTROL STUDY

Author

Kowalczyk, Mark, primary, Pokala, Sridevi K., additional, Demb, Joshua, additional, Youssef, Fady, additional, Liu, Lin, additional, Bustamante, Ranier, additional, Earles, Ashley, additional, Fehmi, Syed M., additional, Savides, Thomas J., additional, Kwong, Wilson, additional, Chang, Michael A., additional, Gupta, Samir, additional, and Anand, Gobind S., additional

Published
2021
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39. An unusual presentation of Gomm-Button disease: a diagnostic enigma

Author

Nagapadma Lakamsani, Sridevi K., Ramamurthy D. V. S. B., Senthil Kumar A. L., and Akshay Jain Salecha

Abstract

Gomm-Button disease (Sweet syndrome) typically presents with abrupt onset of tender skin lesions accompanied by fever and neutrophilia. Histopathology shows the presence of dense neutrophilic infiltrates, oedema without vasculitis. One of the criteria for diagnosis of sweets syndrome is the absence of vasculitis. However, recent reports suggest that vasculitis should not exclude the diagnosis. We present a case of Sweet syndrome with an atypical clinical and histopathological presentation.

Published
2022
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43. Sa1376 PANCREAS CANCER ASSOCIATED MORTALITY IS LOW IN A NATIONAL COHORT OF 28,249 PATIENTS WITH CHRONIC PANCREATITIS

Author

Pokala, Sridevi K., primary, Youssef, Fady, additional, Liu, Lin, additional, Bustamante, Ranier, additional, Catari, Mythri, additional, Earles, Ashley, additional, Savides, Thomas J., additional, Fehmi, Syed M., additional, Chang, Michael A., additional, Kwong, Wilson, additional, Gupta, Samir, additional, and Anand, Gobind S., additional

Published
2020
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45. Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Author

Shupler, Matthew, Hystad, Perry, Gustafson, Paul, Rangarajan, Sumathy, Mushtaha, Maha, Jayachtria, KG, Mony, Prem K, Mohan, Deepa, Kumar, Parthiban, Lakshmi, PVM, Sagar, Vivek, Gupta, Rajeev, Mohan, Indu, Nair, Sanjeev, Varma, Ravi Prasad, Li, Wei, Hu, Bo, You, Kai, Ncube, Tatenda, Ncube, Brian, Chifamba, Jephat, West, Nicola, Yeates, Karen, Iqbal, Romaina, Khawaja, Rehman, Yusuf, Rita, Khan, Afreen, Seron, Pamela, Lanas, Fernando, Lopez-Jaramillo, Patricio, Camacho, Paul A, Puoane, Thandi, Yusuf, Salim, Brauer, Michael, Yusuf, S, Rangarajan, S, Teo, KK, Anand, SS, Chow, CK, O'Donnell, M, Mente, A, Leong, D, Smyth, A, Joseph, P, Duong, M, Kurmi, O, D'Souza, R, Walli-Attaei, M, Balaji, B, Naito, R, Islam, S, Hu, W, Ramasundarahettige, C, Sheridan, P, Bangdiwala, S, Dyal, L, Casanova, A, Dehghan, M, Lewis, G, Agapay, D, Aliberti, A, Aoucheva, N, Arshad, A, Reyes, A, Bideri, B, Buthool, R, Chin, S, Di Marino, M, Frances, R, Gopal, S, Jakymyshn, M, Kandy, N, Kay, I, Lindeman, J, McAlpine, G, McNeice, E, Mushtaha, M, Patel, R, Pattath, D, Ramacham, S, Ramezani, E, Rimac, J, Shifaly, F, Swallow, J, Trottier, M, Trottier, S, Solano, R, Zaki, A, Zhang, B, Zhang, V, Rahman, O, Yusuf, R, Ahmed, SAKS, Choudhury, T, Sintaha, M, Khan, A, Alam, O, Nayeem, N, Mitra, SN, Pasha, F, Lanas, F, Seron, P, Oliveros, MJ, Cazor, F, Palacios, Y, Wei, Li, Lisheng, Liu, Jian, Bo, Bo, Hu, Lu, Yin, Wenhua, Zhao, Hongye, Zhang, Xuan, Jia, Yi, Sun, Xingyu, Wang, Xiuwen, Zhao, Xinye, He, Tao, Chen, Hui, Chen, Xiaohong, Chang, Qing, Deng, Xiaoru, Cheng, Liya, Xie, Zhiguang, Liu, Juan, Li, Jian, Li, Xu, Liu, Bing, Ren, Wei, Wang, Yang, Wang, Jun, Yang, Yi, Zhai, Manlu, Zhu, Fanghong, Lu, Jianfang, Wu, Yindong, Li, Yan, Hou, Liangqing, Zhang, Baoxia, Guo, Xiaoyang, Liao, Shiying, Zhang, BianRongwen, Xiuzhen, Tian, Dong, Li, Di, Chen, Jianguo, Wu, Yize, Xiao, Tianlu, Liu, Peng, Zhang, Changlin, Dong, Ning, Li, Xiaolan, Ma, Yuqing, Yang, Rensheng, Lei, Minfan, Fu, Jing, He, Yu, Liu, Xiaojie, Xing, Qiang, Zhou, Lopez-Jaramillo, P, Camacho-Lopez, PA, Otero-Wandurraga, J, Molina, DI, Cure-Cure, C, Perez, M, Hernandez, E, Arcos, E, Narvaez, C, Sotomayor, A, Garcia, H, Sanchez, G, Cotes, F, Rico, A, Duran, M, Torres, C, Mony, P, Vaz, M, Swaminathan, S, Shankar, K, Kurpad, AV, Jayachitra, KG, Kumar, N, Hospital, HAL, Mohan, V, Deepa, M, Parthiban, K, Anitha, M, Hemavathy, S, Rahulashankiruthiyayan, T, Anitha, D, Anjana, RM, Dhanasekar, R, Sureshkumar, S, Sridevi, K, Gupta, R, Panwar, RB, Mohan, I, Rastogi, P, Rastogi, S, Bhargava, R, Kumar, R, Thakur, JS, Patro, B, Mahajan, R, Chaudary, P, Kutty, V Raman, Vijayakumar, K, Ajayan, K, Rajasree, G, Renjini, AR, Deepu, A, Sandhya, B, Asha, S, Soumya, HS, Kaur, M, Sagar, V, Iqbal, R, Khawaja, R, Azam, I, Kazmi, K, Kruger, L, Kruger, A, Bestra, P, Voster, HH, Schutte, AE, Wentzel-Viljoen, E, Eloff, FC, de Ridder, H, Moss, H, Potgieter, J, Roux, AA, Watson, M, de Wet, G, Olckers, A, Jerling, JC, Pieters, M, Hoekstra, T, Puoane, T, Swart, R, Igumbor, E, Tsolekile, L, Ndayi, K, Sanders, D, Naidoo, P, Steyn, N, Peer, N, Mayosi, B, Rayner, B, Lambert, V, Levitt, N, Kolbe-Alexander, T, Ntyintyane, L, Hughes, G, Fourie, J, Muzigaba, M, Xapa, S, Gobile, N, Jwili, B, Ndibaza, K, Egbujie, B, Yeates, K, Oresto, M, West, N, Chifamba, J, Ncube, T, Ncube, B, Chimhete, C, Neya, GK, Manenji, T, Gwaunza, L, Mapara, V, Terera, G, Mahachi, C, Murambiwa, P, Mapanga, R, Chinhara, A, Epidemiolo, Prospective Urban Rural, and Everest

Subjects
010504 meteorology & atmospheric sciences, Air pollution, 010501 environmental sciences, medicine.disease_cause, 01 natural sciences, Agricultural economics, Article, Country level, 11. Sustainability, medicine, Coal, Baseline (configuration management), 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Kerosene, Renewable Energy, Sustainability and the Environment, business.industry, Multilevel model, 1. No poverty, Public Health, Environmental and Occupational Health, 13. Climate action, Environmental science, Survey data collection, Community setting, business
Abstract

Digital, Introduction. Switching from polluting (e.g. wood, crop waste, coal) to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions. While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods. We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study. We assessed household-level primary cooking fuel switching during a median of 10 years of follow up (∼2005–2015). We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households (12 369) reported changing their primary cooking fuels between baseline and follow up surveys. Of these, 61% (7582) switched from polluting (wood, dung, agricultural waste, charcoal, coal, kerosene) to clean (gas, electricity) fuels, 26% (3109) switched between different polluting fuels, 10% (1164) switched from clean to polluting fuels and 3% (522) switched between different clean fuels. Among the 17 830 households using polluting cooking fuels at baseline, household-level factors (e.g. larger household size, higher wealth, higher education level) were most strongly associated with switching from polluting to clean fuels in India; in all other countries, community-level factors (e.g. larger population density in 2010, larger increase in population density between 2005 and 2015) were the strongest predictors of polluting-to-clean fuel switching. Conclusions. The importance of community and sub-national factors relative to household characteristics in determining polluting-to-clean fuel switching varied dramatically across the nine countries examined. This highlights the potential importance of national and other contextual factors in shaping large-scale clean cooking transitions among rural communities in low- and middle-income countries., Ciencias Médicas y de la Salud

Published
2019
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46. Method Development and Validation for Valsartan and Sacubitril by RP-HLPC

Author

Sireesha, G., Narendra, D., Prasanna, M. Lakshmi, Priya, M. Laxmi, Sridevi, K. V. R. L., Sireesha, G., Narendra, D., Prasanna, M. Lakshmi, Priya, M. Laxmi, and Sridevi, K. V. R. L.

Abstract

The estimation of Saccubitril and Valsartan was done by RP-HPLC. The assay of Saccubitril and Valsartan was performed with tablets and the % assay was found to be 99.11and 100.76. and it’s linearity was found to be linear with a correlation coefficient of 0.999 and 0.99. The acceptance criteria of precision is RSD should be not more than 2.0% and the method show precision 0.43 and 0.68. The acceptance criteria of intermediate precision is RSD should be not more than 2.0% and the method show precision 0.61 and 0.85. The accuracy limit is the percentage recovery should be in the range of 97.0% - 103.0%. The total recovery was found to be 100.34% and 100.22% for Saccubitril and Valsartan. The validation of developed method shows that the accuracy is well within the limit, which shows that the method is capable of showing good accuracy and reproducibility. The acceptance criteria for LOD and LOQ is 3 and 10. The LOD and LOQ for Saccubitril was found to be 3.02 and 9.98 and LOD and LOQ for Valsartan was found to be 3.00 and 10.00. The robustness limit for mobile phase variation and flow rate variation are well within the limit.

Published
2020

47. Fr336 RISK FACTORS FOR DEVELOPMENT OF PANCREATIC CANCER AMONG PATIENTS WITH CHRONIC PANCREATITIS: A CASE-CONTROL STUDY

Author

Sridevi K. Pokala, Wilson Kwong, Mark Kowalczyk, Joshua Demb, Syed M. Fehmi, Fady Youssef, Michael A. Chang, Lin Liu, Ashley Earles, Ranier Bustamante, Gobind S. Anand, Samir Gupta, and Thomas J. Savides

Subjects
medicine.medical_specialty, Hepatology, business.industry, Pancreatic cancer, Internal medicine, Gastroenterology, medicine, Case-control study, Pancreatitis, medicine.disease, business
Published
2021
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49. Sa1376 PANCREAS CANCER ASSOCIATED MORTALITY IS LOW IN A NATIONAL COHORT OF 28,249 PATIENTS WITH CHRONIC PANCREATITIS

Author

Wilson Kwong, Thomas J. Savides, Samir Gupta, Lin Liu, Syed M. Fehmi, Ranier Bustamante, Fady Youssef, Mythri Catari, Ashley Earles, Sridevi K. Pokala, Gobind S. Anand, and Michael A. Chang

Subjects
medicine.medical_specialty, Hepatology, business.industry, Gastroenterology, Cancer, medicine.disease, National cohort, medicine.anatomical_structure, Internal medicine, medicine, Pancreatitis, Pancreas, business
Published
2020
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50. Contributory presentations/posters

Author

Gries, A., Singh, Balwinder, Nakazawal, Chicko, Genest, D., Getzoff, E. D., Matsuo, H., Kaur, Harpreet, Borst, J. W., Chadha, K. C., Tingyun, Kuang, Jagannadham, M. V., Leijon, Mikael, Sato, S., Bhakuni, Vlnod, Vijayan, M., Surolia, A., Suguna, K., Manoj, N., Srinivas, V. R., Ravishankar, R., Laggner, P., Prassl, R., Schwarzenbacher, R., Zeth, K., Kostner, G. M., Taylor, Susan S., Xuong, Nguyen-huu, Akamine, Pearl, Sagar, Bidva M., Saikrishnan, K., Purnapatre, K., Handa, P., Roy, S., Varshney, U., Biswal, B. K., Sukumar, N., Rao, J. K. Mohana, Johnson, A., Pattabhi, Vasantha, Murthy, M. R. N., Krishna, Sri S., Savithri, H. S., Sastri, Mira, Hosur, M. V., Pillai, Bindu, Kannan, K. K., Kumar, Mukesh, Patwardhan, Swati, Padmanabhaa, B., Sasaki-Sugio, S., Matsuzaki, T., Nukaga, M., Singh, T. P., Sharma, A. K., Srinivasan, A., Khan, J. A., Paramasivam, M., Kumar, P., Karthikevan, S., Sharma, S., Yadav, S., Srintvasan, A., Alam, Neelima, Gourinath, S., Kaur, Punit, Chandra, Vikas, Betzel, Ch., Ghosh, S., Bera, A. K., Pal, A. K., Baneriee, Asok, Mukhopadhyay, B. P., Bhattacharya, S., Chakraborty, S., Haldar, U., Dey, I., Solovicova, Adriana, Sevcik, Jozef, Sekar, K., Sundaralingam, M., Genov, N., Liang, Dong-cai, Zhang, Ji-ping, Jiang, Tao, Chang, Wen-rui, Blommers, Marcel, Jahnke, Wolfgang, Hosur, R. V., Panchal, S. C., Pillay, Bindu, Jaganathan, N. R., Mathur, Puniti, Srivatsun, S., Joshi, Ratan Mani, Chauhan, V. S., Govil, Girjesh, Atreya, H. S., Sahu, S. C., Quinjou, Éric, Adjadj, Elisabeth, Mispelter, Joël, Izadi-Pruneyre, Nadia, Blouquit, Yves, Heyd, Bernadette, Lerat, Guilhem, Desmadreil, Michel, Milnard, Philippe, Lin, Y., Rao, B. D. Nageswara, Raghunathan, Vidva, Chau, Mei H., Coutinho, Evans, Pesais, Prashant, Srivastava, Sudha, Saran, Anil, Srikrishnan, Thamarapu, Lijima, Herbert, Gesme, Jayson, Sapico, Leizl F., Paxton, Raymond, Grace, C. R., Nagenagowda, G., Lynn, A. M., Cowsik, Sudha M., Govil, G., Sahu, Sarata C., Bhattacharya, A., Chauhan, S., Kumar, Anil, Zuiderweg, Erik R. P., Pellecchia, Maurizio, Nitta, Katsutoshi, Ohnishi, Atsushi, Kawano, Keiichi, Hikichi, Kunio, Fujitani, Naoki, Ohkubo, Tadayasu, Aizawa, Tomoyasu, Kumaki, Yasuhiro, Hayakawa, Yoichi, Parvathy, Rani V., Kini, R. M., Nakagawa, Astushi, Tanaka, Isao, Demura, Makoto, Yao, Min, Koshiba, Takumi, Kobashigawa, Yoshihiro, Kuwajima, Kunihiro, Linge, Jens, Nilges, Michael, Donoghue, Seán O., Chakshusmathi, G., Ratnaparkhi, Girish S., Madhu, P. K., Varadarajan, R., Tetreau, C., Tourbez, M., Lavalette, D., Bulone, D., Manno, M., Emanuele, A., Palma-Vittorelli, M. B., Palma, M. U., Vaiana, S. M., Martorana, V., Biagio, P. L. San, Chang, D. K., Cheng, S. F., Yang, S. H., Francis, S., Trivedi, V. D., Chien, W. J., Manstein, Dietmar J., Batra, Renn, Geeves, Michael A., Geller, Maciej, Trvlska, Joanna, Grochowski, Pawel, Lesyng, B., Ginalski, K., Grochowski, P., Lavalette, P., Blouquit, Y., Roccatano, D., Berendsen, H. J. C., Amadei, A., Nola, Di A., Ho, Bosco, Curmi, P. M. G., Berry, H., Pelta, J., Pauthe, E., Lairez, D., Srinivasan, M., Sahi, Shakti, Kothekar, V., Madhusudnan, Kartha S., Nandel, Fateh S., Jain, D. V. S., Berendsen, Herman J. C., Feenstra, Anton K., Tama, F., Sanejouand, Y.-H., Go, N., Sharma, Deepak, Pasha, Santosh, Sharma, Sunita, Brahmachari, Samir K., Makker, Jyoti, Viiavaraghavan, R., Kumar, S., Dey, Sharmisllia, Krishnamoorthy, G., Lakshmikanth, G. S., Zaitseva, E. M., Mazhul, V. M., Kierdaszuk, Borys, Widengren, J., Rigler, R., Terry, B., Mets, Ü., Swaminathan, R., Yathindra, N., Thamotharan, S., Chosrowjan, H., Mataga, N., Shibata, Y., Morisima, I., Xiao, Ming, Selvin, Paul, Chakraharty, Tania, Cooke, Roger, Faraone, A., Branca, C., Maisano, G., Migliardo, P., Magazù, S., Villari, V., Behere, Digambar V., Deva, Sharique Zahida Waheed M., Vallone, B., Savino, C., Travaglini-Allocatelli, C., Cutruzzolà, F., Brunori, M., Gibson, Q. H., Mazumdar, Shyamalava, Mitra, Samaresh, Prasad, Swati, Soto, P., Fayad, R., Tyulkova, N. A., Sukovataya, I. E., Mamedov, Sh. V., Aksakal, B., Canturk, M., Aktas, B., Yilgin, R., Bogutska, K. I., Miroshnichenko, N. S., Wein, A. J., Hypolite, J. A., DiSanto, M., Chacko, S., Zheng, Y-M., Antosiewicz, J., Wojciechowski, M., Grycuk, T., Di Nola, Alfredo, Ceruso, Marc A., Chatterjee, Bishnu P., Bandvopadhvay, Subhasis, Choudhury, Devapriva, Khight, Stefan, Thompson, Andrew, Stojanoff, Vivian, Pinkner, Jerome, Hultgren, Scott, Flatters, Delphine, Goodfellow, Julia, Takazawatt, Fumi, Kanehisa, Minoru, Sasai, Masaki, Nakamura, Hironori, Wang, Bao Han, Pan, xin Min, Zheng, Yuan, Wang, Zhi Xin, Ahmad, Atta, Kulkarni, Sangeeta, Prakash, Koodathingal, Prajapati, Shashi, Surin, Alexey, Kihara, Hiroshi, Yang, Li, Matsumoto, Tomoharu, Nakagawa, Yuki, Semisotnov, Gennady V., Kimura, Kazumoto, Amemiya, Yoshiyuki, Tayyab, Saad, Muzammil, Salman, Kumar, Yogesh, Bhakuni, Vinod, Sundd, Monica, Kundu, Suman, Jagannadham, Medicherla V., Chandani, Bina, Warrier, Deepti, Sinha, Lalankumar, Dhar, Ruby, Mehrotra, Sonam, Khandelwal, Purnima, Seth, Subhendu, Gidwani, Arun, Prabha, Ratna C., Sasidhar, Y. U., Madhusudan, K. P., Nishikawa, Ken, Kinjo, Akira R., Varadarajan, Raghavan, Chakravarty, Suvobrata, Van Dael, H., Noyelle, K., Joniau, M., Haezebrouck, P., Jha, Indra Brata, Bhat, Rajiv, Dash, Sheffali, Mohanty, Prasanna, Bandyopadhyay, A. K., Sonawat, H. M., Rao, Ch. Mohan, Datta, Siddhartha, Raman, B., Rajaraman, K., Ramakrishna, T., Pande, A., Benedek, G., King, J., Betts, S., Pande, J., Asherie, N., Ogun, O., Kalacheva, G. S., Sokolova, I. V., Mitaku, Shigeki, Sonoyama, Masashi, Taira, Kunihiro, Yokoyama, Yasunori, Sasakil, Takanori, Kamo, Naoki, Mukai, Yuri, Dalal, Seema, Regan, Lynne, Mituku, Shigeki, Kumar, Devesh, Roychoudhury, Mihir, Lőrinczv, Dénes, Könczöl, Franciska, Farkas, László, Belagyi, Joseph, Schick, Christoph, Thomson, Christy A., Ananthanarayanan, Vettai S., Alirzayeva, E. G., Baba-Zade, S. N., Sarai, A., Kono, H., Uedaira, H., An, J., Gromiha, Michael M., Oobatake, M., Yutani, Katsuhide, Takano, Kazufumi, Yamagata, Yuriko, Jas, Gouri S., Hofrichter, James, Muñoz, Victor, Eaton, William A., Penoyar, Jonathan, Lo Verde, Philip T., Bódi, Á., Venekei, I., Kardos, J., Gráf, L., Závodszky, P., Szilágyi, András, Závodszky, Péter, Woolfson, D. N., Walshaw, J., Allan, R. D., Funahashi, Jun, Gupta, Savan, Di Nola, A., Mangoni, M., Roccatano, P., Ramachandraiah, Gosu, Chandra, Nagasuma R., Ciani, Barbara, Woolfson, Derek N., Nair, Usha B., Salunke, Dinakar M., Kaur, Kanwal J., Swaminathan, Chittoor P., Surolia, Avadhesha, Pramanik, A., Jörnvall, H., Nygren, P.-Å., Jonasson, P., Ståhl, S., Johansson, B.-L., Kratz, G., Wahren, J., Ekberg, K., Uhlén, M., Jansson, O. T., Uhlén, S., Misselwitz, Rolf, Welfle, Heinz, Welfle, Karin, Höhne, Wolfgang, Kurganov, B. I., Mitskevich, L. G., Fedurkina, N. V., Jarori, Gotam K., Maity, Haripada, Guharay, J., Sengupta, P. 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1999
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