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Lambert TP, Chan M, Sanchez-Perez JA, Nikbakht M, Lin DJ, Nawar A, Bashar SK, Kimball JP, Zia JS, Gazi AH, Cestero GI, Corporan D, Padala M, Hahn JO, Inan OT. A Comparison of Normalization Techniques for Individual Baseline-Free Estimation of Absolute Hypovolemic Status Using a Porcine Model. Biosensors (Basel) 2024; 14:61. [PMID: 38391980 PMCID: PMC10886994 DOI: 10.3390/bios14020061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/07/2024] [Accepted: 01/16/2024] [Indexed: 02/24/2024]
Abstract
Hypovolemic shock is one of the leading causes of death in the military. The current methods of assessing hypovolemia in field settings rely on a clinician assessment of vital signs, which is an unreliable assessment of hypovolemia severity. These methods often detect hypovolemia when interventional methods are ineffective. Therefore, there is a need to develop real-time sensing methods for the early detection of hypovolemia. Previously, our group developed a random-forest model that successfully estimated absolute blood-volume status (ABVS) from noninvasive wearable sensor data for a porcine model (n = 6). However, this model required normalizing ABVS data using individual baseline data, which may not be present in crisis situations where a wearable sensor might be placed on a patient by the attending clinician. We address this barrier by examining seven individual baseline-free normalization techniques. Using a feature-specific global mean from the ABVS and an external dataset for normalization demonstrated similar performance metrics compared to no normalization (normalization: R2 = 0.82 ± 0.025|0.80 ± 0.032, AUC = 0.86 ± 5.5 × 10-3|0.86 ± 0.013, RMSE = 28.30 ± 0.63%|27.68 ± 0.80%; no normalization: R2 = 0.81 ± 0.045, AUC = 0.86 ± 8.9 × 10-3, RMSE = 28.89 ± 0.84%). This demonstrates that normalization may not be required and develops a foundation for individual baseline-free ABVS prediction.
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Affiliation(s)
- Tamara P. Lambert
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (M.C.); (O.T.I.)
| | - Michael Chan
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (M.C.); (O.T.I.)
| | - Jesus Antonio Sanchez-Perez
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (J.A.S.-P.); (M.N.); (D.J.L.); (A.N.); (S.K.B.); (G.I.C.)
| | - Mohammad Nikbakht
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (J.A.S.-P.); (M.N.); (D.J.L.); (A.N.); (S.K.B.); (G.I.C.)
| | - David J. Lin
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (J.A.S.-P.); (M.N.); (D.J.L.); (A.N.); (S.K.B.); (G.I.C.)
| | - Afra Nawar
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (J.A.S.-P.); (M.N.); (D.J.L.); (A.N.); (S.K.B.); (G.I.C.)
| | - Syed Khairul Bashar
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (J.A.S.-P.); (M.N.); (D.J.L.); (A.N.); (S.K.B.); (G.I.C.)
| | - Jacob P. Kimball
- The Donald P. Shiley School of Engineering, University of Portland, Portland, OR 97203, USA;
| | - Jonathan S. Zia
- Division of Neurology & Neurological Sciences, Stanford School of Medicine, Palo Alto, CA 94304, USA;
| | - Asim H. Gazi
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA;
| | - Gabriela I. Cestero
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (J.A.S.-P.); (M.N.); (D.J.L.); (A.N.); (S.K.B.); (G.I.C.)
| | - Daniella Corporan
- Structural Heart Research and Innovation Laboratory, Carlyle Fraser Heart Center, Emory University Hospital Midtown, Atlanta, GA 30308, USA; (D.C.); (M.P.)
- Division of Cardiothoracic Surgery, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Muralidhar Padala
- Structural Heart Research and Innovation Laboratory, Carlyle Fraser Heart Center, Emory University Hospital Midtown, Atlanta, GA 30308, USA; (D.C.); (M.P.)
- Division of Cardiothoracic Surgery, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Jin-Oh Hahn
- Department of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA;
| | - Omer T. Inan
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (M.C.); (O.T.I.)
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; (J.A.S.-P.); (M.N.); (D.J.L.); (A.N.); (S.K.B.); (G.I.C.)
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Bremner JD, Gazi AH, Lambert TP, Nawar A, Harrison AB, Welsh JW, Vaccarino V, Walton KM, Jaquemet N, Mermin-Bunnell K, Mesfin H, Gray TA, Ross K, Saks G, Tomic N, Affadzi D, Bikson M, Shah AJ, Dunn KE, Giordano NA, Inan OT. Noninvasive Vagal Nerve Stimulation for Opioid Use Disorder. Ann Depress Anxiety 2023; 10:1117. [PMID: 38074313 PMCID: PMC10699253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Background Opioid Use Disorder (OUD) is an escalating public health problem with over 100,000 drug overdose-related deaths last year most of them related to opioid overdose, yet treatment options remain limited. Non-invasive Vagal Nerve Stimulation (nVNS) can be delivered via the ear or the neck and is a non-medication alternative to treatment of opioid withdrawal and OUD with potentially widespread applications. Methods This paper reviews the neurobiology of opioid withdrawal and OUD and the emerging literature of nVNS for the application of OUD. Literature databases for Pubmed, Psychinfo, and Medline were queried for these topics for 1982-present. Results Opioid withdrawal in the context of OUD is associated with activation of peripheral sympathetic and inflammatory systems as well as alterations in central brain regions including anterior cingulate, basal ganglia, and amygdala. NVNS has the potential to reduce sympathetic and inflammatory activation and counter the effects of opioid withdrawal in initial pilot studies. Preliminary studies show that it is potentially effective at acting through sympathetic pathways to reduce the effects of opioid withdrawal, in addition to reducing pain and distress. Conclusions NVNS shows promise as a non-medication approach to OUD, both in terms of its known effect on neurobiology as well as pilot data showing a reduction in withdrawal symptoms as well as physiological manifestations of opioid withdrawal.
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Affiliation(s)
- J Douglas Bremner
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta GA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta GA
- Atlanta Veterans Affairs Healthcare System, Decatur GA
| | - Asim H Gazi
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
| | - Tamara P Lambert
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA
| | - Afra Nawar
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
| | - Anna B Harrison
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
| | - Justine W Welsh
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta GA
| | - Viola Vaccarino
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
- Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta GA
| | - Kevin M Walton
- Clinical Research Grants Branch, Division of Therapeutics and Medical Consequences, National Institute on Drug Abuse, Bethesda, MD
| | - Nora Jaquemet
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta GA
| | - Kellen Mermin-Bunnell
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta GA
| | - Hewitt Mesfin
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta GA
| | - Trinity A Gray
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta GA
| | - Keyatta Ross
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta GA
| | - Georgia Saks
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA
| | - Nikolina Tomic
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
| | - Danner Affadzi
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta GA
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York, New York, NY
| | - Amit J Shah
- Atlanta Veterans Affairs Healthcare System, Decatur GA
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA
- Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta GA
| | - Kelly E Dunn
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore MD
| | | | - Omer T Inan
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA
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Nawar A, Gazi AH, Chan M, Sanchez-Perez JA, Rahman FN, Ziegler C, Daaboul O, Haddad G, Al-Abboud OA, Ahmed H, Murrah N, Vaccarino V, Shah AJ, Inan OT. Towards Quantifying Stress in Patients with a History of Myocardial Infarction: Validating ECG-Derived Patch Features. Annu Int Conf IEEE Eng Med Biol Soc 2023; 2023:1-4. [PMID: 38083211 DOI: 10.1109/embc40787.2023.10340614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Patients with prior myocardial infarction (MI) have an increased risk of experiencing a secondary event which is exacerbated by mental stress. Our team has developed a miniaturized patch with the capability to capture electrocardiogram (ECG), seismocardiogram (SCG) and photoplethysmogram (PPG) signals which may provide multimodal information to characterize stress responses within the post-MI population in ambulatory settings. As ECG-derived features have been shown to be informative in assessing the risk of MI, a critical first step is to ensure that the patch ECG features agree with gold-standard devices, such as the Biopac. However, this is yet to be done in this population. We, thus, performed a comparative analysis between ECG-derived features (heart rate (HR) and heart rate variability (HRV)) of the patch and Biopac in the context of stress. Our dataset contained post-MI and healthy control subjects who participated in a public speaking challenge. Regression analyses for patch and Biopac HR and HRV features (RMSSD, pNN50, SD1/SD2, and LF/HF) were all significant (p<0.001) and had strong positive correlations (r>0.9). Additionally, Bland-Altman analyses for most features showed tight limits of agreement: 0.999 bpm (HR), 11.341 ms (RMSSD), 0.07% (pNN50), 0.146 ratio difference (SD1/SD2), 0.750 ratio difference (LF/HF).Clinical relevance- This work demonstrates that ECG-derived features obtained from the patch and Biopac are in agreement, suggesting the clinical utility of the patch in deriving quantitative metrics of physiology during stress in post-MI patients. This has the potential to improve post-MI patients' outcomes, but needs to be further evaluated.
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Gazi AH, Harrison AB, Lambert TP, Nawar A, Obideen M, Driggers EG, Vaccarino V, Shah AJ, Rozell CJ, Bikson M, Welsh JW, Inan OT, Bremner JD. Pain is reduced by transcutaneous cervical vagus nerve stimulation and correlated with cardiorespiratory variability measures in the context of opioid withdrawal. Front Pain Res 2022; 3:1031368. [PMID: 36438447 PMCID: PMC9682166 DOI: 10.3389/fpain.2022.1031368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 10/20/2022] [Indexed: 11/10/2022] Open
Abstract
Over 100,000 individuals in the United States lost their lives secondary to drug overdose in 2021, with opioid use disorder (OUD) being a leading cause. Pain is an important component of opioid withdrawal, which can complicate recovery from OUD. This study's objectives were to assess the effects of transcutaneous cervical vagus nerve stimulation (tcVNS), a technique shown to reduce sympathetic arousal in other populations, on pain during acute opioid withdrawal and to study pain's relationships with objective cardiorespiratory markers. Twenty patients with OUD underwent opioid withdrawal while participating in a two-hour protocol. The protocol involved opioid cues to induce opioid craving and neutral conditions for control purposes. Adhering to a double-blind design, patients were randomly assigned to receive active tcVNS (n = 9) or sham stimulation (n = 11) throughout the protocol. At the beginning and end of the protocol, patients' pain levels were assessed using the numerical rating scale (0–10 scale) for pain (NRS Pain). During the protocol, electrocardiogram and respiratory effort signals were measured, from which heart rate variability (HRV) and respiration pattern variability (RPV) were extracted. Pre- to post- changes (denoted with a Δ) were computed for all measures. Δ NRS Pain scores were lower (P = 0.045) for the active group (mean ± standard deviation: −0.8 ± 2.4) compared to the sham group (0.9 ± 1.0). A positive correlation existed between Δ NRS pain scores and Δ RPV (Spearman's ρ = 0.46; P = 0.04). Following adjustment for device group, a negative correlation existed between Δ HRV and Δ NRS Pain (Spearman's ρ = −0.43; P = 0.04). This randomized, double-blind, sham-controlled pilot study provides the first evidence of tcVNS-induced reductions in pain in patients with OUD experiencing opioid withdrawal. This study also provides the first quantitative evidence of an association between breathing irregularity and pain. The correlations between changes in pain and changes in objective physiological markers add validity to the data. Given the clinical importance of reducing pain non-pharmacologically, the findings support the need for further investigation of tcVNS and wearable cardiorespiratory sensing for pain monitoring and management in patients with OUD.
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Affiliation(s)
- Asim H. Gazi
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
- Correspondence: Asim H. Gazi J. Douglas Bremner
| | - Anna B. Harrison
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Tamara P. Lambert
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Afra Nawar
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Malik Obideen
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Emily G. Driggers
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Viola Vaccarino
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
- Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, United States
| | - Amit J. Shah
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
- Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, United States
- Atlanta Veterans Affairs Health Care System, Decatur, GA, United States
| | - Christopher J. Rozell
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York, New York, NY, United States
| | - Justine W. Welsh
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Omer T. Inan
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - J. Douglas Bremner
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
- Atlanta Veterans Affairs Health Care System, Decatur, GA, United States
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States
- Correspondence: Asim H. Gazi J. Douglas Bremner
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Amin MR, Islam MR, Bhuiyan M, Islam MS, Islam F, Tuli HJ, Nawar A, Tabassum T, Fardous J, Hasan MJ. Sketch of 2018 dengue outbreak in a megacity, Bangladesh. Trop Med Health 2022; 50:80. [PMID: 36289528 PMCID: PMC9598007 DOI: 10.1186/s41182-022-00470-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 10/09/2022] [Indexed: 12/04/2022] Open
Abstract
Background Dengue has become a major public health threat in Bangladesh since 2000, when the first outbreak was reported. Each outbreak has distinct characteristics, and thus, the report of the outbreak helps to understand the disease process and subsequent clinical management of these patients. On that ground, the study was designed to sketch the clinico-epidemiological characteristics of the 2018 dengue outbreak in Bangladesh. Methods This hospital-based cross-sectional study was conducted in one of the largest public medical college hospitals and a single private hospital located in the southern and northern parts of the megacity of the country. A total of 297 confirmed dengue cases were assessed with a preformed pretested questionnaire. Clinico-epidemiological and laboratory parameters were reported along with sociodemographic details. Statistical analysis was performed with SPSS 20. Results Male patients were predominantly affected by dengue infection. The mean age of the patients was 31.24 ± 13.99 (SD) years, with a range from 2 to 85 years. Eighty-two percent of patients reported from the Dhaka metropolitan city. The highest percentage of cases (37.1%) was isolated from Bansree, Dhaka city, followed by Rampura (21.4%) and Khilgaon (6.2%). In addition to common symptoms, e.g., fever (90.6%), headache (90.6%), chills (81.8%), anorexia and vomiting (76.4%), backache, and redness of the eyes were two prominent symptoms that affected more than two-thirds of the study population. On the other hand, less common symptoms, such as cough, abdominal pain, and respiratory distress, were present in 39.7%, 33.7%, and 15.5% of patients, respectively. Overall, 17.6% of patients were hypotensive during admission, with a mean systolic blood pressure of 107.65 ± 18.17 (SD) mmHg. Other prominent signs were dehydration (80.5%) and rash (33%). Conclusion This outbreak was especially characterized by gastrointestinal symptoms, which were predominant along with other typical features.
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Affiliation(s)
- Mohammad Robed Amin
- grid.413674.30000 0004 5930 8317Department of Medicine, Dhaka Medical College, Dhaka, Bangladesh
| | | | - Muktadir Bhuiyan
- grid.413674.30000 0004 5930 8317Department of Medicine, Dhaka Medical College, Dhaka, Bangladesh
| | - Md. Shahnoor Islam
- grid.413674.30000 0004 5930 8317Department of Medicine, Dhaka Medical College, Dhaka, Bangladesh
| | - Fathema Islam
- grid.413674.30000 0004 5930 8317Department of Medicine, Dhaka Medical College, Dhaka, Bangladesh
| | - Habiba Jannatun Tuli
- grid.413674.30000 0004 5930 8317Department of Medicine, Dhaka Medical College, Dhaka, Bangladesh
| | - Afra Nawar
- grid.413674.30000 0004 5930 8317Department of Medicine, Dhaka Medical College, Dhaka, Bangladesh
| | | | - Jannatul Fardous
- Tropical and Infectious Disease Division, Tropical Disease and Health Research Center, Dhaka, Bangladesh
| | - Mohammad Jahid Hasan
- Tropical and Infectious Disease Division, Tropical Disease and Health Research Center, Dhaka, Bangladesh
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Bahalul Haque AKM, Bhushan B, Nawar A, Talha KR, Ayesha SJ. Attacks and Countermeasures in IoT Based Smart Healthcare Applications. Intelligent Systems Reference Library 2022:67-90. [DOI: 10.1007/978-3-030-90119-6_6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
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Nawar A, Rahman F, Krishnamurthi N, Som A, Turaga P. Topological Descriptors for Parkinson's Disease Classification and Regression Analysis. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2020:793-797. [PMID: 33018105 DOI: 10.1109/embc44109.2020.9176285] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together with machine learning tools to automate the process of Parkinson's disease classification and severity assessment. An automated, stable, and accurate method to evaluate Parkinson's would be significant in streamlining diagnoses of patients and providing families more time for corrective measures. We propose a methodology which incorporates TDA into analyzing Parkinson's disease postural shifts data through the representation of persistence images. Studying the topology of a system has proven to be invariant to small changes in data and has been shown to perform well in discrimination tasks. The contributions of the paper are twofold. We propose a method to 1) classify healthy patients from those afflicted by disease and 2) diagnose the severity of disease. We explore the use of the proposed method in an application involving a Parkinson's disease dataset comprised of healthy-elderly, healthy-young and Parkinson's disease patients. Our code is available at https://github.com/itsmeafra/Sublevel-Set-TDA.
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Attallah AM, Attia H, El-Nashar EM, Nawar A, Abdel Kader K, Ismail H, El Ebeidy G. Induction of resistance against Schistosoma mansoni infection by passive transfer of an IgG2a monoclonal antibody. Vaccine 1999; 17:2306-10. [PMID: 10403599 DOI: 10.1016/s0264-410x(98)00451-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Monoclonal antibodies can confer resistance to schistosome infections. This has led to identification of several protective antigens. An IgG2a monoclonal antibody designated BRL4 mAb identified a 74-kDa antigen in antigenic extract of Schistosoma mansoni adult worms. The target antigen was localized in gut and tegument. In 3 passive transfer experiments, the BRL4 mAb conferred 51.6, 41.9 and 53.8% protection levels into female Swiss mice. Histopathological examination revealed a marked decrease in number, size, collagen and reticular fibers of the liver granulomas. Further experiments using purified 74-kDa-target antigen as a candidate vaccine will be performed.
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Affiliation(s)
- A M Attallah
- Biotechnology Research Center, New Damietta City, Egypt
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