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Finite Element Analysis of effect of cusp inclination and occlusal contacts in PFM and PEEK implant-supported crowns on resultant stresses.

Medical journal, Armed Forces India

Manchikalapudi G, Basapogu S.
PMID: 35035048
Med J Armed Forces India. 2022 Jan;78(1):80-87. doi: 10.1016/j.mjafi.2020.11.014. Epub 2021 Jan 16.

BACKGROUND: Effect of prosthesis design on occlusal overload and long-term implant stability cannot be overstated. In Porcelain Fused to Metal (PFM) crowns, low cusp inclination and occlusal contacts limited to central fossa ensure axially directed forces on an implant...

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Manchikalapudi G, Basapogu S. Finite Element Analysis of effect of cusp inclination and occlusal contacts in PFM and PEEK implant-supported crowns on resultant stresses. Med J Armed Forces India. 2021;78(1):80-87doi: 10.1016/j.mjafi.2020.11.014.
Manchikalapudi, G., & Basapogu, S. (2022). Finite Element Analysis of effect of cusp inclination and occlusal contacts in PFM and PEEK implant-supported crowns on resultant stresses. Medical journal, Armed Forces India, 78(1), 80-87. https://doi.org/10.1016/j.mjafi.2020.11.014
Manchikalapudi, Githanjali, and Basapogu, Sreeramulu. "Finite Element Analysis of effect of cusp inclination and occlusal contacts in PFM and PEEK implant-supported crowns on resultant stresses." Medical journal, Armed Forces India vol. 78,1 (2022): 80-87. doi: https://doi.org/10.1016/j.mjafi.2020.11.014
Manchikalapudi G, Basapogu S. Finite Element Analysis of effect of cusp inclination and occlusal contacts in PFM and PEEK implant-supported crowns on resultant stresses. Med J Armed Forces India. 2022 Jan;78(1):80-87. doi: 10.1016/j.mjafi.2020.11.014. Epub 2021 Jan 16. PMID: 35035048; PMCID: PMC8737102.
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Cloning, expression and characterization of arcelin and its impact on digestive enzymes of the stored product insect pest, Callosobruchus maculatus (F.).

Pesticide biochemistry and physiology

Hilda K, Bhuvaragavan S, Kamatchi R, Meenakumari M, Janarthanan S.
PMID: 34955175
Pestic Biochem Physiol. 2022 Jan;180:104982. doi: 10.1016/j.pestbp.2021.104982. Epub 2021 Nov 03.

The pulse beetle Callosobruchus maculatus causes potential damage to legume crops by infesting the seeds, leading to a reduction of total protein content. Arcelin found in the wild accessions of the common bean, is an insecticidal protein that has...

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Hilda K, Bhuvaragavan S, Kamatchi R, et al. Cloning, expression and characterization of arcelin and its impact on digestive enzymes of the stored product insect pest, Callosobruchus maculatus (F.). Pestic Biochem Physiol. 2021;180:104982doi: 10.1016/j.pestbp.2021.104982.
Hilda, K., Bhuvaragavan, S., Kamatchi, R., Meenakumari, M., & Janarthanan, S. (2022). Cloning, expression and characterization of arcelin and its impact on digestive enzymes of the stored product insect pest, Callosobruchus maculatus (F.). Pesticide biochemistry and physiology, 180104982. https://doi.org/10.1016/j.pestbp.2021.104982
Hilda, Karuppiah, et al. "Cloning, expression and characterization of arcelin and its impact on digestive enzymes of the stored product insect pest, Callosobruchus maculatus (F.)." Pesticide biochemistry and physiology vol. 180 (2022): 104982. doi: https://doi.org/10.1016/j.pestbp.2021.104982
Hilda K, Bhuvaragavan S, Kamatchi R, Meenakumari M, Janarthanan S. Cloning, expression and characterization of arcelin and its impact on digestive enzymes of the stored product insect pest, Callosobruchus maculatus (F.). Pestic Biochem Physiol. 2022 Jan;180:104982. doi: 10.1016/j.pestbp.2021.104982. Epub 2021 Nov 03. PMID: 34955175.
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Curved Nanomembrane-Based Concentric Ring Cavities for Supermode Hybridization.

Nano letters

Wang J, Yin Y, Hao Q, Yang YD, Valligatla S, Saei Ghareh Naz E, Li Y, Saggau CN, Ma L, Schmidt OG.
PMID: 30339757
Nano Lett. 2018 Nov 14;18(11):7261-7267. doi: 10.1021/acs.nanolett.8b03453. Epub 2018 Oct 24.

We report the mode interactions and resonant hybridization in nanomembrane-formed concentric dual ring cavities supporting whispering gallery mode resonances. Utilizing a rolled-up nanomembrane with subwavelength thickness as an interlayer, dual concentric microring cavities are formed by coating high-index nanomembranes...

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Wang J, Yin Y, Hao Q, et al. Curved Nanomembrane-Based Concentric Ring Cavities for Supermode Hybridization. Nano Lett. 2018;18(11):7261-7267doi: 10.1021/acs.nanolett.8b03453.
Wang, J., Yin, Y., Hao, Q., Yang, Y. D., Valligatla, S., Saei Ghareh Naz, E., Li, Y., Saggau, C. N., Ma, L., & Schmidt, O. G. (2018). Curved Nanomembrane-Based Concentric Ring Cavities for Supermode Hybridization. Nano letters, 18(11), 7261-7267. https://doi.org/10.1021/acs.nanolett.8b03453
Wang, Jiawei, et al. "Curved Nanomembrane-Based Concentric Ring Cavities for Supermode Hybridization." Nano letters vol. 18,11 (2018): 7261-7267. doi: https://doi.org/10.1021/acs.nanolett.8b03453
Wang J, Yin Y, Hao Q, Yang YD, Valligatla S, Saei Ghareh Naz E, Li Y, Saggau CN, Ma L, Schmidt OG. Curved Nanomembrane-Based Concentric Ring Cavities for Supermode Hybridization. Nano Lett. 2018 Nov 14;18(11):7261-7267. doi: 10.1021/acs.nanolett.8b03453. Epub 2018 Oct 24. PMID: 30339757.
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A thiazolo[5,4-d]thiazole-bridged porphyrin organic framework as a promising nonlinear optical material.

Chemical communications (Cambridge, England)

Samal M, Valligatla S, Saad NA, Rao MV, Rao DN, Sahu R, Biswal BP.
PMID: 31453586
Chem Commun (Camb). 2019 Sep 21;55(74):11025-11028. doi: 10.1039/c9cc05415d. Epub 2019 Aug 27.

Porphyrin-based porous organic frameworks are an important group of materials gaining interest due to their structural diversity and distinct opto-electronic properties. However, these materials are seldom explored for nonlinear optical (NLO) applications. In this work, we investigate a thiazolo[5,4-d]thiazole-bridged...

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Samal M, Valligatla S, Saad NA, et al. A thiazolo[5,4-d]thiazole-bridged porphyrin organic framework as a promising nonlinear optical material. Chem Commun (Camb). 2019;55(74):11025-11028doi: 10.1039/c9cc05415d.
Samal, M., Valligatla, S., Saad, N. A., Rao, M. V., Rao, D. N., Sahu, R., & Biswal, B. P. (2019). A thiazolo[5,4-d]thiazole-bridged porphyrin organic framework as a promising nonlinear optical material. Chemical communications (Cambridge, England), 55(74), 11025-11028. https://doi.org/10.1039/c9cc05415d
Samal, Mahalaxmi, et al. "A thiazolo[5,4-d]thiazole-bridged porphyrin organic framework as a promising nonlinear optical material." Chemical communications (Cambridge, England) vol. 55,74 (2019): 11025-11028. doi: https://doi.org/10.1039/c9cc05415d
Samal M, Valligatla S, Saad NA, Rao MV, Rao DN, Sahu R, Biswal BP. A thiazolo[5,4-d]thiazole-bridged porphyrin organic framework as a promising nonlinear optical material. Chem Commun (Camb). 2019 Sep 21;55(74):11025-11028. doi: 10.1039/c9cc05415d. Epub 2019 Aug 27. PMID: 31453586.
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Isolation and Characterization of Gut Bacterial Proteases Involved in Inducing Pathogenicity of .

Frontiers in microbiology

Regode V, Kuruba S, Mohammad AS, Sharma HC.
PMID: 27766093
Front Microbiol. 2016 Oct 06;7:1567. doi: 10.3389/fmicb.2016.01567. eCollection 2016.

No abstract available.

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Regode V, Kuruba S, Mohammad AS, et al. Isolation and Characterization of Gut Bacterial Proteases Involved in Inducing Pathogenicity of . Front Microbiol. 2016;7:1567doi: 10.3389/fmicb.2016.01567.
Regode, V., Kuruba, S., Mohammad, A. S., & Sharma, H. C. (2016). Isolation and Characterization of Gut Bacterial Proteases Involved in Inducing Pathogenicity of . Frontiers in microbiology, 71567. https://doi.org/10.3389/fmicb.2016.01567
Regode, Visweshwar, et al. "Isolation and Characterization of Gut Bacterial Proteases Involved in Inducing Pathogenicity of ." Frontiers in microbiology vol. 7 (2016): 1567. doi: https://doi.org/10.3389/fmicb.2016.01567
Regode V, Kuruba S, Mohammad AS, Sharma HC. Isolation and Characterization of Gut Bacterial Proteases Involved in Inducing Pathogenicity of . Front Microbiol. 2016 Oct 06;7:1567. doi: 10.3389/fmicb.2016.01567. eCollection 2016. PMID: 27766093; PMCID: PMC5052264.
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Estimating COVID-19 .

Machine learning with applications

Sreeramula S, Rahardjo D.
PMID: 34939041
Mach Learn Appl. 2021 Dec 15;6:100136. doi: 10.1016/j.mlwa.2021.100136. Epub 2021 Aug 20.

COVID-19 (SARS COV2 n-corona virus) is the newfangled virus of the coronavirus family. COVID-19 can cause serious illness with symptoms of fever, cold, cough, and respiratory blockage. COVID-19 is a contagious virus, which originated in Wuhan, China. After one...

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Sreeramula S, Rahardjo D. Estimating COVID-19 . Mach Learn Appl. 2021;6:100136doi: 10.1016/j.mlwa.2021.100136.
Sreeramula, S., & Rahardjo, D. (2021). Estimating COVID-19 . Machine learning with applications, 6100136. https://doi.org/10.1016/j.mlwa.2021.100136
Sreeramula, Sankaraiah, and Rahardjo, Deny. "Estimating COVID-19 ." Machine learning with applications vol. 6 (2021): 100136. doi: https://doi.org/10.1016/j.mlwa.2021.100136
Sreeramula S, Rahardjo D. Estimating COVID-19 . Mach Learn Appl. 2021 Dec 15;6:100136. doi: 10.1016/j.mlwa.2021.100136. Epub 2021 Aug 20. PMID: 34939041; PMCID: PMC8378038.
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Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications.

Frontiers in molecular biosciences

Altincekic N, Korn SM, Qureshi NS, Dujardin M, Ninot-Pedrosa M, Abele R, Abi Saad MJ, Alfano C, Almeida FCL, Alshamleh I, de Amorim GC, Anderson TK, Anobom CD, Anorma C, Bains JK, Bax A, Blackledge M, Blechar J, Böckmann A, Brigandat L, Bula A, Bütikofer M, Camacho-Zarco AR, Carlomagno T, Caruso IP, Ceylan B, Chaikuad A, Chu F, Cole L, Crosby MG, de Jesus V, Dhamotharan K, Felli IC, Ferner J, Fleischmann Y, Fogeron ML, Fourkiotis NK, Fuks C, Fürtig B, Gallo A, Gande SL, Gerez JA, Ghosh D, Gomes-Neto F, Gorbatyuk O, Guseva S, Hacker C, Häfner S, Hao B, Hargittay B, Henzler-Wildman K, Hoch JC, Hohmann KF, Hutchison MT, Jaudzems K, Jović K, Kaderli J, Kalniņš G, Kaņepe I, Kirchdoerfer RN, Kirkpatrick J, Knapp S, Krishnathas R, Kutz F, Zur Lage S, Lambertz R, Lang A, Laurents D, Lecoq L, Linhard V, Löhr F, Malki A, Bessa LM, Martin RW, Matzel T, Maurin D, McNutt SW, Mebus-Antunes NC, Meier BH, Meiser N, Mompeán M, Monaca E, Montserret R, Mariño Perez L, Moser C, Muhle-Goll C, Neves-Martins TC, Ni X, Norton-Baker B, Pierattelli R, Pontoriero L, Pustovalova Y, Ohlenschläger O, Orts J, Da Poian AT, Pyper DJ, Richter C, Riek R, Rienstra CM, Robertson A, Pinheiro AS, Sabbatella R, Salvi N, Saxena K, Schulte L, Schiavina M, Schwalbe H, Silber M, Almeida MDS, Sprague-Piercy MA, Spyroulias GA, Sreeramulu S, Tants JN, Tārs K, Torres F, Töws S, Treviño MÁ, Trucks S, Tsika AC, Varga K, Wang Y, Weber ME, Weigand JE, Wiedemann C, Wirmer-Bartoschek J, Wirtz Martin MA, Zehnder J, Hengesbach M, Schlundt A.
PMID: 34041264
Front Mol Biosci. 2021 May 10;8:653148. doi: 10.3389/fmolb.2021.653148. eCollection 2021.

The highly infectious disease COVID-19 caused by the

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Altincekic N, Korn SM, Qureshi NS, et al. Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications. Front Mol Biosci. 2021;8:653148doi: 10.3389/fmolb.2021.653148.
Altincekic, N., Korn, S. M., Qureshi, N. S., Dujardin, M., Ninot-Pedrosa, M., Abele, R., Abi Saad, M. J., Alfano, C., Almeida, F. C. L., Alshamleh, I., de Amorim, G. C., Anderson, T. K., Anobom, C. D., Anorma, C., Bains, J. K., Bax, A., Blackledge, M., Blechar, J., Böckmann, A., Brigandat, L., Bula, A., Bütikofer, M., Camacho-Zarco, A. R., Carlomagno, T., Caruso, I. P., Ceylan, B., Chaikuad, A., Chu, F., Cole, L., Crosby, M. G., de Jesus, V., Dhamotharan, K., Felli, I. C., Ferner, J., Fleischmann, Y., Fogeron, M. L., Fourkiotis, N. K., Fuks, C., Fürtig, B., Gallo, A., Gande, S. L., Gerez, J. A., Ghosh, D., Gomes-Neto, F., Gorbatyuk, O., Guseva, S., Hacker, C., Häfner, S., Hao, B., Hargittay, B., Henzler-Wildman, K., Hoch, J. C., Hohmann, K. F., Hutchison, M. T., Jaudzems, K., Jović, K., Kaderli, J., Kalniņš, G., Kaņepe, I., Kirchdoerfer, R. N., Kirkpatrick, J., Knapp, S., Krishnathas, R., Kutz, F., Zur Lage, S., Lambertz, R., Lang, A., Laurents, D., Lecoq, L., Linhard, V., Löhr, F., Malki, A., Bessa, L. M., Martin, R. W., Matzel, T., Maurin, D., McNutt, S. W., Mebus-Antunes, N. C., Meier, B. H., Meiser, N., Mompeán, M., Monaca, E., Montserret, R., Mariño Perez, L., Moser, C., Muhle-Goll, C., Neves-Martins, T. C., Ni, X., Norton-Baker, B., Pierattelli, R., Pontoriero, L., Pustovalova, Y., Ohlenschläger, O., Orts, J., Da Poian, A. T., Pyper, D. J., Richter, C., Riek, R., Rienstra, C. M., Robertson, A., Pinheiro, A. S., Sabbatella, R., Salvi, N., Saxena, K., Schulte, L., Schiavina, M., Schwalbe, H., Silber, M., Almeida, M. D. S., Sprague-Piercy, M. A., Spyroulias, G. A., Sreeramulu, S., Tants, J. N., Tārs, K., Torres, F., Töws, S., Treviño, M. �. �., Trucks, S., Tsika, A. C., Varga, K., Wang, Y., Weber, M. E., Weigand, J. E., Wiedemann, C., Wirmer-Bartoschek, J., Wirtz Martin, M. A., Zehnder, J., Hengesbach, M., & Schlundt, A. (2021). Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications. Frontiers in molecular biosciences, 8653148. https://doi.org/10.3389/fmolb.2021.653148
Altincekic, Nadide, et al. "Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications." Frontiers in molecular biosciences vol. 8 (2021): 653148. doi: https://doi.org/10.3389/fmolb.2021.653148
Altincekic N, Korn SM, Qureshi NS, Dujardin M, Ninot-Pedrosa M, Abele R, Abi Saad MJ, Alfano C, Almeida FCL, Alshamleh I, de Amorim GC, Anderson TK, Anobom CD, Anorma C, Bains JK, Bax A, Blackledge M, Blechar J, Böckmann A, Brigandat L, Bula A, Bütikofer M, Camacho-Zarco AR, Carlomagno T, Caruso IP, Ceylan B, Chaikuad A, Chu F, Cole L, Crosby MG, de Jesus V, Dhamotharan K, Felli IC, Ferner J, Fleischmann Y, Fogeron ML, Fourkiotis NK, Fuks C, Fürtig B, Gallo A, Gande SL, Gerez JA, Ghosh D, Gomes-Neto F, Gorbatyuk O, Guseva S, Hacker C, Häfner S, Hao B, Hargittay B, Henzler-Wildman K, Hoch JC, Hohmann KF, Hutchison MT, Jaudzems K, Jović K, Kaderli J, Kalniņš G, Kaņepe I, Kirchdoerfer RN, Kirkpatrick J, Knapp S, Krishnathas R, Kutz F, Zur Lage S, Lambertz R, Lang A, Laurents D, Lecoq L, Linhard V, Löhr F, Malki A, Bessa LM, Martin RW, Matzel T, Maurin D, McNutt SW, Mebus-Antunes NC, Meier BH, Meiser N, Mompeán M, Monaca E, Montserret R, Mariño Perez L, Moser C, Muhle-Goll C, Neves-Martins TC, Ni X, Norton-Baker B, Pierattelli R, Pontoriero L, Pustovalova Y, Ohlenschläger O, Orts J, Da Poian AT, Pyper DJ, Richter C, Riek R, Rienstra CM, Robertson A, Pinheiro AS, Sabbatella R, Salvi N, Saxena K, Schulte L, Schiavina M, Schwalbe H, Silber M, Almeida MDS, Sprague-Piercy MA, Spyroulias GA, Sreeramulu S, Tants JN, Tārs K, Torres F, Töws S, Treviño MÁ, Trucks S, Tsika AC, Varga K, Wang Y, Weber ME, Weigand JE, Wiedemann C, Wirmer-Bartoschek J, Wirtz Martin MA, Zehnder J, Hengesbach M, Schlundt A. Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications. Front Mol Biosci. 2021 May 10;8:653148. doi: 10.3389/fmolb.2021.653148. eCollection 2021. PMID: 34041264; PMCID: PMC8141814.
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Estimating COVID-19 .

Machine learning with applications

Sreeramula S, Rahardjo D.
PMID: 34939041
Mach Learn Appl. 2021 Dec 15;6:100136. doi: 10.1016/j.mlwa.2021.100136. Epub 2021 Aug 20.

COVID-19 (SARS COV2 n-corona virus) is the newfangled virus of the coronavirus family. COVID-19 can cause serious illness with symptoms of fever, cold, cough, and respiratory blockage. COVID-19 is a contagious virus, which originated in Wuhan, China. After one...

Cite
Sreeramula S, Rahardjo D. Estimating COVID-19 . Mach Learn Appl. 2021;6:100136doi: 10.1016/j.mlwa.2021.100136.
Sreeramula, S., & Rahardjo, D. (2021). Estimating COVID-19 . Machine learning with applications, 6100136. https://doi.org/10.1016/j.mlwa.2021.100136
Sreeramula, Sankaraiah, and Rahardjo, Deny. "Estimating COVID-19 ." Machine learning with applications vol. 6 (2021): 100136. doi: https://doi.org/10.1016/j.mlwa.2021.100136
Sreeramula S, Rahardjo D. Estimating COVID-19 . Mach Learn Appl. 2021 Dec 15;6:100136. doi: 10.1016/j.mlwa.2021.100136. Epub 2021 Aug 20. PMID: 34939041; PMCID: PMC8378038.
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GeneXpert assay - A cutting-edge tool for rapid tissue diagnosis of tuberculous lymphadenitis.

Journal of clinical tuberculosis and other mycobacterial diseases

Raja R, Sreeramulu PN, Dave P, Srinivasan D.
PMID: 33305020
J Clin Tuberc Other Mycobact Dis. 2020 Nov 19;21:100204. doi: 10.1016/j.jctube.2020.100204. eCollection 2020 Dec.

BACKGROUND: The most prevalent clinical entity of extra pulmonary tuberculosis is tuberculous lymphadenitis. However, it resembles other granulomatous conditions pathologically and obtaining tissue for microbiological diagnosis is also difficult. Thus it is a challenging task for diagnosis and early...

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Raja R, Sreeramulu PN, Dave P, et al. GeneXpert assay - A cutting-edge tool for rapid tissue diagnosis of tuberculous lymphadenitis. J Clin Tuberc Other Mycobact Dis. 2020;21:100204doi: 10.1016/j.jctube.2020.100204.
Raja, R., Sreeramulu, P. N., Dave, P., & Srinivasan, D. (2020). GeneXpert assay - A cutting-edge tool for rapid tissue diagnosis of tuberculous lymphadenitis. Journal of clinical tuberculosis and other mycobacterial diseases, 21100204. https://doi.org/10.1016/j.jctube.2020.100204
Raja, Raadhika, et al. "GeneXpert assay - A cutting-edge tool for rapid tissue diagnosis of tuberculous lymphadenitis." Journal of clinical tuberculosis and other mycobacterial diseases vol. 21 (2020): 100204. doi: https://doi.org/10.1016/j.jctube.2020.100204
Raja R, Sreeramulu PN, Dave P, Srinivasan D. GeneXpert assay - A cutting-edge tool for rapid tissue diagnosis of tuberculous lymphadenitis. J Clin Tuberc Other Mycobact Dis. 2020 Nov 19;21:100204. doi: 10.1016/j.jctube.2020.100204. eCollection 2020 Dec. PMID: 33305020; PMCID: PMC7718474.
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