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Analysis of significant factors for dengue infection prognosis using the self organizing map

Faisal T, Ibrahim F, Taib MN

Annu Int Conf IEEE Eng Med Biol Soc, 2008;2008:5140-3.
PMID: 19163874 DOI: 10.1109/IEMBS.2008.4650371

This study presents a new approach to determine the significant prognosis factors in dengue patients utilizing the self-organizing map (SOM). SOM was used to visualize and determine the significant factors that can differentiate between the dengue patients and the healthy subjects. Bioimpedance analysis (BIA) parameters and symptoms/signs obtained from the 210 dengue patients during their hospitalization were used in this study. Database comprised of 329 sample (210 dengue patients and 119 healthy subjects) were used in the study. Accordingly, two maps were constructed. A total of 35 predictors (17 BIA parameters, 18 symptoms/signs) were investigated on the day of defervescence of fever. The first map was constructed based on BIA parameters while the second map utilized the symptoms and signs. The visualized results indicated that, the significant BIA prognosis factors for differentiating the dengue patients from the healthy subjects are reactance, intracellular water, ratio of the extracellular water and intracellular water, and ratio of the extracellular mass and body cell mass.
Reexamination of risk criteria in dengue patients using the self-organizing map

Faisal T, Taib MN, Ibrahim F

Med Biol Eng Comput, 2010 Mar;48(3):293-301.
PMID: 20016950 DOI: 10.1007/s11517-009-0561-x

Even though the World Health Organization criteria's for classifying the dengue infection have been used for long time, recent studies declare that several difficulties have been faced by the clinicians to apply these criteria. Accordingly, many studies have proposed modified criteria to identify the risk in dengue patients based on statistical analysis techniques. None of these studies utilized the powerfulness of the self-organized map (SOM) in visualizing, understanding, and exploring the complexity in multivariable data. Therefore, this study utilized the clustering of the SOM technique to identify the risk criteria in 195 dengue patients. The new risk criteria were defined as: platelet count less than or equal 40,000 cells per mm(3), hematocrit concentration great than or equal 25% and aspartate aminotransferase (AST) rose by fivefold the normal upper limit for AST/alanine aminotransfansferase (ALT) rose by fivefold the normal upper limit for ALT. The clusters analysis indicated that any dengue patient fulfills any two of the risk criteria is consider as high risk dengue patient.
Non-invasive diagnosis of risk in dengue patients using bioelectrical impedance analysis and artificial neural network

Ibrahim F, Faisal T, Salim MI, Taib MN

Med Biol Eng Comput, 2010 Nov;48(11):1141-8.
PMID: 20683676 DOI: 10.1007/s11517-010-0669-z

This paper presents a new approach to diagnose and classify early risk in dengue patients using bioelectrical impedance analysis (BIA) and artificial neural network (ANN). A total of 223 healthy subjects and 207 hospitalized dengue patients were prospectively studied. The dengue risk severity criteria was determined and grouped based on three blood investigations, namely, platelet (PLT) count (less than or equal to 30,000 cells per mm(3)), hematocrit (HCT) (increase by more than or equal to 20%), and either aspartate aminotransferase (AST) level (raised by fivefold the normal upper limit) or alanine aminotransferase (ALT) level (raised by fivefold the normal upper limit). The dengue patients were classified according to their risk groups and the corresponding BIA parameters were subsequently obtained and quantified. Four parameters were used for training and testing the ANN which are day of fever, reactance, gender, and risk group's quantification. Day of fever was defined as the day of fever subsided, i.e., when the body temperature fell below 37.5°C. The blood investigation and the BIA data were taken for 5 days. The ANN was trained via the steepest descent back propagation with momentum algorithm using the log-sigmoid transfer function while the sum-squared error was used as the network's performance indicator. The best ANN architecture of 3-6-1 (3 inputs, 6 neurons in the hidden layer, and 1 output), learning rate of 0.1, momentum constant of 0.2, and iteration rate of 20,000 was pruned using a weight-eliminating method. Eliminating a weight of 0.05 enhances the dengue's prediction risk classification accuracy of 95.88% for high risk and 96.83% for low risk groups. As a result, the system is able to classify and diagnose the risk in the dengue patients with an overall prediction accuracy of 96.27%.
Neural network diagnostic system for dengue patients risk classification

Faisal T, Taib MN, Ibrahim F

J Med Syst, 2012 Apr;36(2):661-76.
PMID: 20703665 DOI: 10.1007/s10916-010-9532-x

With the dramatic increase of the worldwide threat of dengue disease, it has been very crucial to correctly diagnose the dengue patients in order to decrease the disease severity. However, it has been a great challenge for the physicians to identify the level of risk in dengue patients due to overlapping of the medical classification criteria. Therefore, this study aims to construct a noninvasive diagnostic system to assist the physicians for classifying the risk in dengue patients. Systematic producers have been followed to develop the system. Firstly, the assessment of the significant predictors associated with the level of risk in dengue patients was carried out utilizing the statistical analyses technique. Secondly, Multilayer perceptron neural network models trained via Levenberg-Marquardt and Scaled Conjugate Gradient algorithms was employed for constructing the diagnostic system. Finally, precise tuning for the models' parameters was conducted in order to achieve the optimal performance. As a result, 9 noninvasive predictors were found to be significantly associated with the level of risk in dengue patients. By employing those predictors, 75% prediction accuracy has been achieved for classifying the risk in dengue patients using Scaled Conjugate Gradient algorithm while 70.7% prediction accuracy were achieved by using Levenberg-Marquardt algorithm.
Fulltext An in vitro investigation to understand the synergistic role of MMPs-1 and 9 on articular cartilage biomechanical properties

Mixon A, Savage A, Bahar-Moni AS, Adouni M, Faisal T

Sci Rep, 2021 Jul 13;11(1):14409.
PMID: 34257325 DOI: 10.1038/s41598-021-93744-1

Matrix metalloproteinases (MMPs) play a crucial role in enzymatically digesting cartilage extracellular matrix (ECM) components, resulting in degraded cartilage with altered mechanical loading capacity. Overexpression of MMPs is often caused by trauma, physiologic conditions and by disease. To understand the synergistic impact MMPs have on cartilage biomechanical properties, MMPs from two subfamilies: collagenase (MMP-1) and gelatinase (MMP-9) were investigated in this study. Three different ratios of MMP-1 (c) and MMP-9 (g), c1:g1, c3:g1 and c1:g3 were considered to develop a degradation model. Thirty samples, harvested from bovine femoral condyles, were treated in groups of 10 with one concentration of enzyme mixture. Each sample was tested in a healthy state prior to introducing degradative enzymes to establish a baseline. Samples were subjected to indentation loading up to 20% bulk strain. Both control and treated samples were mechanically and histologically assessed to determine the impact of degradation. Young's modulus and peak load of the tissue under indentation were compared between the control and degraded cartilage explants. Cartilage degraded with the c3:g1 enzyme concentration resulted in maximum 33% reduction in stiffness and peak load compared to the other two concentrations. The abundance of collagenase is more responsible for cartilage degradation and reduced mechanical integrity.
EEG spectral analysis on Muslim prayers

Doufesh H, Faisal T, Lim KS, Ibrahim F

Appl Psychophysiol Biofeedback, 2012 Mar;37(1):11-8.
PMID: 21965118 DOI: 10.1007/s10484-011-9170-1

This study investigated the proposition of relaxation offered by performing the Muslim prayers by measuring the alpha brain activity in the frontal (F3-F4), central (C3-C4), parietal (P3-P4), and occipital (O1-O2) electrode placements using the International 10-20 System. Nine Muslim subjects were asked to perform the four required cycles of movements of Dhuha prayer, and the EEG were subsequently recorded with open eyes under three conditions, namely, resting, performing four cycles of prayer while reciting the specific verses and supplications, and performing four cycles of acted salat condition (prayer movements without any recitations). Analysis of variance (ANOVA) tests revealed that there were no significant difference in the mean alpha relative power (RP(α)) between the alpha amplitude in the Dhuha prayer and the acted conditions in all eight electrode positions. However, the mean RP(α) showed higher alpha amplitude during the prostration position of the Dhuha prayer and acted condition at the parietal and occipital regions in comparison to the resting condition. Findings were similar to other studies documenting increased alpha amplitude in parietal and occipital regions during meditation and mental concentration. The incidence of increased alpha amplitude suggested parasympathetic activation, thus indicating a state of relaxation. Subsequent studies are needed to delineate the role of mental concentration, and eye focus, on alpha wave amplitude while performing worshipping acts.
Fulltext The application of biomedical engineering techniques to the diagnosis and management of tropical diseases: a review

Ibrahim F, Thio TH, Faisal T, Neuman M

Sensors (Basel), 2015 Mar 23;15(3):6947-95.
PMID: 25806872 DOI: 10.3390/s150306947

This paper reviews a number of biomedical engineering approaches to help aid in the detection and treatment of tropical diseases such as dengue, malaria, cholera, schistosomiasis, lymphatic filariasis, ebola, leprosy, leishmaniasis, and American trypanosomiasis (Chagas). Many different forms of non-invasive approaches such as ultrasound, echocardiography and electrocardiography, bioelectrical impedance, optical detection, simplified and rapid serological tests such as lab-on-chip and micro-/nano-fluidic platforms and medical support systems such as artificial intelligence clinical support systems are discussed. The paper also reviewed the novel clinical diagnosis and management systems using artificial intelligence and bioelectrical impedance techniques for dengue clinical applications.
Proteomics, functional characterization and antivenom neutralization of the venom of Pakistani Russell's viper (Daboia russelii) from the wild

Faisal T, Tan KY, Sim SM, Quraishi N, Tan NH, Tan CH

J Proteomics, 2018 07 15;183:1-13.
PMID: 29729992 DOI: 10.1016/j.jprot.2018.05.003

The venom proteome of wild Pakistani Russell's viper (Daboia russelii) was investigated through nano-ESI-LCMS/MS of the reverse-phase HPLC fractions. A total of 54 venom proteins were identified and clustered into 11 protein families. Phospholipase A2 (PLA2, 63.8%) and Kunitz-type serine protease inhibitor (KSPI, 16.0%) were most abundant, followed by snake venom serine protease (SVSP, 5.5%, mainly Factor V activating enzyme), vascular endothelial growth factor (VEGF, 4.3%), snake venom metalloproteinase (SVMP, 2.5%, mainly Factor X activating enzyme) and phosphodiesterase (PDE, 2.5%). Other minor proteins include cysteine-rich secretory protein (CRiSP), snake venom C-type lectin/lectin-like protein (snaclec), nerve growth factor, L-amino acid oxidase and 5'-nucleotidase. PLA2, KSPI, SVSP, snaclec and SVMP are hemotoxic proteins in the venom. The study indicated substantial venom variation in D. russelii venoms of different locales, including 3 Pakistani specimens kept in the USA. The venom exhibited potent procoagulant activity on human plasma (minimum clotting dose = 14.5 ng/ml) and high lethality (rodent LD50 = 0.19 μg/g) but lacked hemorrhagic effect locally. The Indian VINS Polyvalent Antivenom bound the venom immunologically in a concentration-dependent manner. It moderately neutralized the venom procoagulant and lethal effects (normalized potency against lethality = 2.7 mg venom neutralized per g antivenom).
BIOLOGICAL SIGNIFICANCE: Comprehensive venom proteomes of D. russelii from different locales will facilitate better understanding of the geographical variability of the venom in both qualitative and quantitative terms. This is essential to provide scientific basis for the interpretation of differences in the clinical presentation of Russell's viper envenomation. The study revealed a unique venom proteome of the Pakistani D. russelii from the wild (Indus Delta), in which PLA2 predominated (~60% of total venom proteins). The finding unveiled remarkable differences in the venom compositions between the wild (present study) and the captive specimens reported previously. The integration of toxicity tests enabled the correlation of the venom proteome with the envenoming pathophysiology, where the venom showed potent lethality mediated through coagulopathic activity. The Indian VINS Polyvalent Antivenom (VPAV) showed binding activity toward the venom protein antigens; however the immunorecognition of small proteins and PLA2-dominating fractions was low to moderate. Consistently, the antivenom neutralized the toxicity of the wild Pakistani Russell's viper venom at moderate efficacies. Our results suggest that it may be possible to enhance the Indian antivenom potency against the Pakistani viper venom by the inclusion of venoms from a wider geographical range including that from Pakistan into the immunogen formulation.
Fulltext Proteomics, toxicity and antivenom neutralization of Sri Lankan and Indian Russell's viper (Daboia russelii) venoms

Faisal T, Tan KY, Tan NH, Sim SM, Gnanathasan CA, Tan CH

J Venom Anim Toxins Incl Trop Dis, 2021 Apr 30;27:e20200177.
PMID: 33995514 DOI: 10.1590/1678-9199-JVATITD-2020-0177

BACKGROUND: The western Russell's viper (Daboia russelii) is widely distributed in South Asia, and geographical venom variation is anticipated among distant populations. Antivenoms used for Russell's viper envenomation are, however, raised typically against snakes from Southern India. The present study investigated and compared the venom proteomes of D. russelii from Sri Lanka (DrSL) and India (DrI), the immunorecognition of Indian VINS Polyvalent Antivenom (VPAV) and its efficacy in neutralizing the venom toxicity.
METHODS: The venoms of DrSL and DrI were decomplexed with C18 high-performance liquid chromatography and SDS-polyacrylamide gel electrophoresis under reducing conditions. The proteins fractionated were identified through nano-ESI-liquid chromatography-tandem mass spectrometry (LCMS/MS). The immunological studies were conducted with enzyme-linked immunosorbent assay. The neutralization of the venom procoagulant effect was evaluated in citrated human plasma. The neutralization of the venom lethality was assessed in vivo in mice adopting the WHO protocol.
RESULTS: DrSL and DrI venom proteomes showed comparable major protein families, with phospholipases A2 (PLA2) being the most abundant (> 60% of total venom proteins) and diverse (six protein forms identified). Both venoms were highly procoagulant and lethal (intravenous median lethal dose in mice, LD50 = 0.24 and 0.32 µg/g, for DrSL and DrI, respectively), while lacking hemorrhagic and anticoagulant activities. VPAV was immunoreactive toward DrSL and DrI venoms, indicating conserved protein antigenicity in the venoms. The high molecular weight venom proteins were, however, more effectively immunorecognized than small ones. VPAV was able to neutralize the coagulopathic and lethal effects of the venoms moderately.
CONCLUSION: Considering that a large amount of venom can be injected by Russell's viper during envenomation, the potency of antivenom can be further improved for optimal neutralization and effective treatment. Region-specific venoms and key toxins may be incorporated into the immunization procedure during antivenom production.