ExpHBA Deep-IoT: Exponential Honey Badger Optimized Deep Learning For Breast Cancer Detection in IoT Healthcare System.

Breast cancer (BC) is the most widely found disease among women in the world. The early detection of BC can frequently lessen the mortality rate as well as progress the probability of providing proper treatment. Hence, this paper focuses on devising the Exponential Honey Badger Optimization-based Deep Covolutional Neural Network (EHBO-based DCNN) for early identification of BC in the Internet of Things (IoT). Here, the Honey Badger Optimization (HBO) and Exponential Weighted Moving Average (EWMA) algorithms have been combined to create the EHBO. The EHBO is created to transfer the acquired medical data to the base station (BS) by choosing the best cluster heads to categorize the BC. Then, the statistical and texture features are extracted. Further, data augmentation is performed. Finally, the BC classification is done by DCNN. Thus, the observational outcome reveals that the EHBO-based DCNN algorithm attained outstanding performance concerning the testing accuracy, sensitivity, and specificity of 0.9051, 0.8971, and 0.9029, correspondingly. The accuracy of the proposed method is 7.23%, 6.62%, 5.39%, and 3.45% higher than the methods, such as multi-layer perceptron (MLP) classifier, deep learning, support vector machine (SVM), and ensemble-based classifier.

Smart IoT in Breast Cancer Detection Using Optimal Deep Learning.

IoT in healthcare systems is currently a viable option for providing higher-quality medical care for contemporary e-healthcare. Using an Internet of Things (IoT)-based smart healthcare system, a trustworthy breast cancer classification method called Feedback Artificial Crow Search (FACS)-based Shepherd Convolutional Neural Network (ShCNN) is developed in this research. To choose the best routes, the secure routing operation is first carried out using the recommended FACS while taking fitness measures such as distance, energy, link quality, and latency into account. Then, by merging the Crow Search Algorithm (CSA) and Feedback Artificial Tree, the produced FACS is put into practice (FAT). After the completion of routing phase, the breast cancer categorization process is started at the base station. The feature extraction step is then introduced to the pre-processed input mammography image. As a result, it is possible to successfully get features including area, mean, variance, energy, contrast, correlation, skewness, homogeneity, Gray Level Co-occurrence Matrix (GLCM), and Local Gabor Binary Pattern (LGBP). The quality of the image is next enhanced through data augmentation, and finally, the developed FACS algorithm's ShCNN is used to classify breast cancer. The performance of FACS-based ShCNN is examined using six metrics, including energy, delay, accuracy, sensitivity, specificity, and True Positive Rate (TPR), with the maximum energy of 0.562 J, the least delay of 0.452 s, the highest accuracy of 91.56%, the higher sensitivity of 96.10%, the highest specificity of 91.80%, and the maximum TPR of 99.45%.

FWLICM-Deep Learning: Fuzzy Weighted Local Information C-Means Clustering-Based Lung Lobe Segmentation with Deep Learning for COVID-19 Detection.

Coronavirus (COVID-19) creates an extensive range of respiratory contagions, and it is a kind of ribonucleic acid (RNA) virus, which affects both animals and humans. Moreover, COVID-19 is a new disease, which produces contamination in upper respiration alterritory and lungs. The new COVID is a rapidly spreading pathogen globally, and it threatens billions of humans' lives. However, it is significant to identify positive cases in order to avoid the spread of plague and to speedily treat infected patients. Hence, in this paper, the WSCA-based RMDL approach is devised for COVID-19 prediction by means of chest X-ray images. Moreover, Fuzzy Weighted Local Information C-Means (FWLICM) approach is devised in order to segment lung lobes. The developed FWLICM method is designed by modifying the Fuzzy Local Information C-Means (FLICM) technique. Additionally, random multimodel deep learning (RMDL) classifier is utilized for the COVID-19 prediction process. The new optimization approach, named water sine cosine algorithm (WSCA), is devised in order to obtain an effective prediction. The developed WSCA is newly designed by incorporating sine cosine algorithm (SCA) and water cycle algorithm (WCA). The developed WSCA-driven RMDL approach outperforms other COVID-19 prediction techniques with regard to accuracy, specificity, sensitivity, and dice score of 92.41%, 93.55%, 92.14%, and 90.02%.

Computer-Aided Diagnosis System for Alzheimer's Disease Using Positron Emission Tomography Images.

Alzheimer's disease (AD) is a kind of neurological brain disease. It is an irretrievable, neurodegenerative brain disorder. There are no pills or drugs to cure AD. Therefore, an early diagnosis may help the physician to make accurate analysis and to provide better treatment. With the advent of computational intelligence techniques, machine learning models have made tremendous progress in brain images analysis using MRI, SPECT and PEI. However, accurate analysis of brain scans is an extremely challenging task. The main focus of this paper is to design a Computer Aided Diagnosis (CAD) system using Long-Term Short Memory (LSTM) to improve classification rate and determine suitable attributes that can differentiate AD from Healthy Control (HC) subjects. First, 3D PET images are preprocessed, converted into many groups of 2D images and then grouped into many subsets at certain interval. Subsequently, different features including first order statistical, Gray Level Co-occurrence Matrix and wavelet energy of all sub-bands are extracted from each group, combined and taken as feature vectors. LSTM is designed and employed for classifying PET brain images into HC and AD subjects based on the feature vectors. Finally, the developed system is validated on 18FDG-PET images collected from 188 subjects including 105 HC and 83 AD subjects from ADNI database. Efficacy of the developed CAD system is analyzed using different features. Numerical results revealed that the developed CAD system yields classification accuracy of 98.9% when using combined features, showing outstanding performance.

Evaluation of diuretic efficacy and antiurolithiatic potential of ethanolic leaf extract of Annona squamosa Linn. in experimental animal models.

OBJECTIVE: The study is to investigate the diuretic and antiurolithiatic activities of ethanolic leaf extract of Annona squamosa Linn. in experimental animals. MATERIALS AND METHODS: For both studies, Wistar albino rats and two doses of extract (250 and 500 mg/kg) were used. Diuretic activity was evaluated by Lipschitz model. Urine volume and urine pH were noted, the concentration of sodium and potassium was estimated by flame photometry, and diuretic index, natriuretic index, and Lipschitz values were calculated from the results. Furosemide was used as a positive control. Ethylene glycol-induced urolithiasis model was used for antiurolithiatic study. Urine volume, urine pH, body weight, and biochemical parameters such as calcium, urea, uric acid, and creatine both from serum and urine were estimated. Antioxidant parameters and histopathological analysis of the kidney were evaluated. Cystone was used as a positive control in this study. Results were expressed as mean ± standard error of mean. Statistical analysis was carried out using one-way analysis of variance, followed by Dunnett's multiple comparison tests. RESULTS: In both diuretic and antiurolithiatic studies, both doses of the extract showed efficacy, and the dose of 500 mg/kg has shown a significant effect compared to positive control and negative control. CONCLUSION: The dose of 500 mg/kg showed a promising diuretic and antiurolithiatic activity.

No changes in heme synthesis in human Friedreich´s ataxia erythroid progenitor cells.

Friedreich's ataxia (FRDA) is a neurodegenerative disease caused by reduced expression of the protein frataxin. Frataxin is thought to play a role in iron-sulfur cluster biogenesis and heme synthesis. In this study, we used erythroid progenitor stem cells obtained from FRDA patients and healthy donors to investigate the putative role, if any, of frataxin deficiency in heme synthesis. We used electrochemiluminescence and qRT-PCR for frataxin protein and mRNA quantification. We used atomic absorption spectrophotometry for iron levels and a photometric assay for hemoglobin levels. Protoporphyrin IX and Ferrochelatase were analyzed using auto-fluorescence. An "IronChip" microarray analysis followed by a protein-protein interaction analysis was performed. FRDA patient cells showed no significant changes in iron levels, hemoglobin synthesis, protoporphyrin IX levels, and ferrochelatase activity. Microarray analysis presented 11 genes that were significantly changed in all patients compared to controls. The genes are especially involved in oxidative stress, iron homeostasis and angiogenesis. The mystery about the involvement of frataxin on iron metabolism raises the question why frataxin deficiency in primary FRDA cells did not lead to changes in biochemical parameters of heme synthesis. It seems that alternative pathways can circumvent the impact of frataxin deficiency on heme synthesis. We show for the first time in primary FRDA patient cells that reduced frataxin levels are still sufficient for heme synthesis and possibly other mechanisms can overcome reduced frataxin levels in this process. Our data strongly support the fact that so far no anemia in FRDA patients was reported.

A method for extracting task-oriented information from biological text sources.

A method for information extraction which processes the unstructured data from document collection has been introduced. A dynamic programming technique adopted to find relevant genes from sequences which are longest and accurate is used for finding matching sequences and identifying effects of various factors. The proposed method could handle complex information sequences which give different meanings in different situations, eliminating irrelevant information. The text contents were pre-processed using a general-purpose method and were applied with entity tagging component. The bottom-up scanning of key-value pairs improves content finding to generate relevant sequences to the testing task. This paper highlights context-based extraction method for extracting food safety information, which is identified from articles, guideline documents and laboratory results. The graphical disease model verifies weak component through utilisation of development data set. This improves the accuracy of information retrieval in biological text analysis and reporting applications.

Prevalence of Risk Factors of Diabetes Among Urban Poor South Indian Population.

OBJECTIVE: The objective of the study was to assess the prevalence of risk factors of diabetes among urban poor population in Chennai, Tamil Nadu, South India. STUDY AND METHODS: A cross-sectional study was conducted from Dec-2010 to Feb-2011 in Chennai city. Five hundred twenty-nine subjects aged above 18 years (409 women and 120 men) habitants of three slums were randomly selected. A structured questionnaire was used to collect the socio-demographic and clinical information. Anthropometric measures, blood pressure and random blood glucose (RCBG) estimation were done. Dietary intake was assessed using 24-hour diet recall and duration of physical activity/day in all components was recorded. RESULTS: The mean age and BMI of the study population was 45.4±12.8 years and 25.8±4.9 kg/m2 respectively. About 20.4% were illiterate and 34.8% were either unemployed, retired or housewives. Median family income per month was 3000 INR. Prevalence of obesity (≥25 kg/m2) was 57.3% and central obesity (≥90 cms in male and ≥80 cms in female) was 75.7%. The median duration spent in walking, standing and sitting were 30, 120, and 240 minutes/day respectively. There was a gross inadequacy in vegetable intake. The prevalence of self-reported diabetes and hypertension was 20.8% and 24.2%, respectively. Among the subjects without a previous diagnosis of diabetes, 12.5% had RCBG ≥140 mgs. 10.6% were diagnosed with hypertension. CONCLUSIONS: Sedentarism coupled with unhealthy diet pattern are the major contributing factors for the higher prevalence of diabetes and hypertension in urban poor population.

Effect of diabetes on treatment outcome of smear-positive pulmonary tuberculosis--a report from South India.

AIM: To assess the effect of diabetes on tuberculosis (TB) treatment outcome and sputum conversion among new smear-positive (NSP) cases registered under Directly Observed Treatment Short Course in South India. METHODS: Details on sputum conversion and TB treatment outcome were collected from case records of NSP cases (N = 332; M/F 247:85) registered at TB units of three districts in Tamil Nadu. Subjects were screened for diabetes and categorized as diabetic (TBDM) (n = 96; 73:23) and non-diabetic (TBnonDM) (n = 149; 109:40). RESULTS: Among 245 selected TB patients, 93.5% were cured, 1.6% completed TB treatment, 2% had TB treatment failure (TF), and 0.4% had treatment default (TD), 0.4% with MDR-TB and 2% death rate. At the end of intensive phase of TB treatment, 14.7% remained sputum positive in the TBDM group, whereas it was 3.5% in the TBnonDM group. Mean duration (days) for sputum conversion was higher in the TBDM group (64.2 ± 10.5) compared to the TBnonDM group (61.5 ± 7.5) (p<0.001). TF rate was higher (4.2% vs 0.7%) and MDR-TB (1%) was also seen in the TBDM group. No death and TD were seen among DM whereas it was 3.4 and 0.7% in TBnonDM. CONCLUSIONS: Delayed sputum conversion and high TB treatment failure rates were common in NSP cases with diabetes.

Conformational stability of OXA-51 ß-lactamase explains its role in carbapenem resistance of Acinetobacter baumannii.

Acinetobacter baumannii, an important nosocomial pathogen, is increasingly becoming resistant to antibiotics including recent ß-lactam like imipenem. Production of different types of ß-lactamases is one of the major resistance mechanisms which bacteria adapt. We recently reported the presence of a ß-lactamase, OXA-51, in clinical strains of A. baumannii in ICUs of our hospital. This study is an attempt to understand the structure-function relationship of purified OXA-51 in carbapenem resistance in A. baumannii. The OXA-51 was cloned, expressed in E. coli Bl-21(DE3) and further purified. The in vitro enzyme activity of purified OXA-51 was confirmed by two independent techniques; in-gel assay and spectrophotometric method using nitrocefin. Further in vivo effect of OXA-51 was followed by transmission electron microscopy of bacterium. Biophysical and biochemical investigations of OXA-51 were done using LC-MS/MS, UV-Vis absorption, fluorescence, circular dichroic spectroscopy and isothermal calorimetry. Native OXA-51 was characterized as 30.6 kDa, pI 8.43 with no disulphide bonds and comprising of 30% α-helix, 27% ß-sheet. Secondary structure of OXA-51 was significantly unchanged in broad pH (4-10) and temperature (30-60 °C) range with only local alterations at tertiary structural level. Interestingly, enzymatic activity up to 75% was retained under above conditions. Hydrolysis of imipenem by OXA-51 (k(m),1 µM) was found to be thermodynamically favourable. In the presence of imipenem, morphology of sensitive strain of A. baumannii was drastically changed, while OXA-51-transformed sensitive strain retained the stable coccobacillus shape, which demonstrates that imipenem is able to kill sensitive strain but is unable to do so in OXA-51-transformed strain. Hence the production of pH- and temperature-stable OXA-51 appears to be a major determinant in the resistance mechanisms adopted by A. baumannii in order to evade even the latest ß-lactams, imipenem. It can be concluded from the study that OXA-51 plays a vital role in the survival of the pathogen under stress conditions and thus poses a major threat.

Xylan polysaccharides fabricated into nanofibrous substrate for myocardial infarction.

Myocardial infarction, a main cause of heart failure, leads to loss of cardiac tissue impairment of left ventricular function. Repair of diseased myocardium with in vitro engineered cardiac muscle patch/injectable biopolymers with cells may become a viable option for myocardial infarction. We attempted to solve these problems by in vitro study by selecting a plant based polysaccharides beech wood Xylan for the normal functioning of infarcted myocardium. The present study fabricated Xylan based nanofibrous scaffolds cross-linked with glutaraldehyde (Glu) vapors for 24 h, 48 h and 1% Glu blended fibers for the culture of neonatal rat cardiac cells for myocardial infarction. These nanofibers were characterized by SEM, FT-IR, tensile testing and cell culture studies for the normal expression of cardiac proteins. The observed results showed that the Xylan/polyvinyl alcohol (PVA) 24h Glu vapor cross-linked nanofibers (427 nm) having mechanical strength of 2.43 MPa and Young modulus of 3.74 MPa are suitable for the culture of cardiac cells. Cardiac cells proliferation increased only by 11% in Xylan/PVA 24h Glu cross-linked nanofibers compared to control tissue culture plate (TCP). The normal cardiac cell morphology was observed in 24h cross-linked Xylan/PVA nanofibers but 48 h cross-linked fibers cell morphology was changed to flattened and elongated on the fibrous surfaces. Confocal analysis for cardiac expression proteins actinin, connexin 43 was observed normally in 24h Glu cross-linked nanofibers compared to all other nanofibrous scaffolds. The fabricated Xylan/PVA nanofibrous scaffold may have good potential for the normal functioning of infarcted myocardium.

Quantitative profiling and identification of plasma proteins of spinocerebellar ataxia type 2 patients.

BACKGROUND: Spinocerebellar ataxia type 2 (SCA2) is an autosomal-dominant hereditary ataxia characterized by progressive gait and limb ataxia, dysarthria, slow saccades, neuropathy and dementia. The expansion of trinucleotide CAG repeats in the coding region of the ATXN-2 gene leads to expanded polyglutamine stretch in the mutated protein which causes neuronal death. OBJECTIVE: In this study, we investigated the blood plasma of SCA2 patients to find protein biomarkers. METHODS: Thirty-two ataxia patients clinically suspected for SCA2 were evaluated by the International Co-operative Ataxia Rating Scale followed by genetic analysis using PCR. Plasma proteomics of SCA2 patients and age- and gender-matched healthy controls was done using 2D-difference in-gel electrophoresis, LC-MS/MS and Western blot. RESULTS: Genetic analysis confirmed 10 of 32 suspected SCA2 patients. Proteomic data revealed nine differentially expressed proteins in SCA2. These proteins find good association with oxidative stress, calcium-dependent apoptosis, neuropathy, and cognitive impairment in SCA2 patients. Interestingly, the elevated levels of the voltage-dependent calcium channel γ-3 subunit showed a direct correlation with calcium-generated apoptosis of Purkinje cells. The cognitive deficit, a common symptom in SCA2 patients, seems to correlate with decreased levels of transthyretin and retinol-binding protein-4. CONCLUSIONS: Some of these identified proteins in SCA2 can be useful for therapeutic, diagnostic and prognostic purposes.

Electrosprayed hydroxyapatite on polymer nanofibers to differentiate mesenchymal stem cells to osteogenesis.

Electrospraying of hydroxyapatite (HA) nanoparticles onto the surface of polymer nanofibers provides a potentially novel substrate for the adhesion, proliferation and differentiation of mesenchymal stem cells (MSCs) into bone tissue regeneration. HA nanoparticles (4%) were electrosprayed on the surface of electrospun polycaprolactone (PCL) nanofibers (420 ± 15 nm) for bone tissue engineering. PCL/HA nanofibers were comparatively characterized with PCL/Collagen (275 ± 56 nm) nanofibers by FT-IR analysis to confirm the presence of HA. Fabricated PCL/HA and PCL/Collagen nanofibers and TCP (control) were used for the differentiation of equine MSC into osteogenic lineages in the presence of DMEM/F12 medium supplemented with ß-glycerophosphate, ascorbic acid and dexamethasone. Cell proliferation and differentiation into an osteogenic lineage was evaluated by MTS assay, SEM observation, ALP activity, ARS staining, quantification of mineral deposition and expression of osteocalcin. Proliferation of MSCs increased significantly (P ⩽ 0.05) up to 12% in PCL/Collagen (day 15) compared to PCL/HA nanofibrous substrate. ALP activity was increased 20% in PCL/HA by day 10 confirming the direction of osteogenic lineage from MSCs differentiation. PCL/HA stimulated an increased mineral secretion up to 26% by day 15 on ARS staining compared to PCL/Collagen nanofibers and showing cuboidal morphology by expressing osteocalcin. These results confirmed that the specifically fabricated PCL/HA composite nanofibrous substrate enhanced the differentiation of MSCs into osteogenesis.

Structural studies on New Delhi Metallo-ß-lactamase (NDM-2) suggest old ß-lactam, penicillin to be better antibiotic for NDM-2-harbouring Acinetobacter baumanni.

Acinetobacter baumannii, a Gram-negative pathogen causes nosocomial infections including pneumonia, urinary tract and respiratory infections. Carbapenem group of ß-lactam antibiotics are routinely used to treat A. baumannii including multidrug-resistant clinical strains. The emergence of New Delhi Metallo-ß-lactamase (NDM-2), a new type of ß-lactamase and one of the major resistant determinants in A. baumannii, opened up challenges in the treatment of resistant strains. Thus, understanding the structure-function relationship of NDM-2 with different analogues of ß-lactams becomes crucial. We carried out in silico studies on the interaction of various ß-lactams with NDM-2 and with OXA-24, a carbapenem hydrolyzing non-NDM type ß-lactamase. The binding affinity of the ß-lactams to NDM-2 was found to be in the order: ceftazidime ≈ imipenem ≈ doripenem > oxacillin > aztreonam > penicillin; however, the order of their affinity to OXA-24 was quite different: ceftazidime > aztreonam > penicillin > oxacillin > doripenem > imipenem. Further, NDM-2 in comparison to OXA-24 showed stronger interaction (less X-score) with most of the ß-lactams except penicillin. This suggests higher lethality posed by clinical strains expressing NDM-2 than those without NDM-2. Weak interaction between NDM-2 and penicillin clearly points out that penicillin is perhaps better option in treating A. baumannii harbouring NDM-2. Present findings provide new insights in drug resistance at the molecular level of NDM-2 and can help in designing structure-based drugs.

Comparative proteomics of inner membrane fraction from carbapenem-resistant Acinetobacter baumannii with a reference strain.

Acinetobacter baumannii has been identified by the Infectious Diseases Society of America as one of the six pathogens that cause majority of hospital infections. Increased resistance of A.baumannii even to the latest generation of ß-lactams like carbapenem is an immediate threat to mankind. As inner-membrane fraction plays a significant role in survival of A.baumannii, we investigated the inner-membrane fraction proteome of carbapenem-resistant strain of A.baumannii using Differential In-Gel Electrophoresis (DIGE) followed by DeCyder, Progenesis and LC-MS/MS analysis. We identified 19 over-expressed and 4 down-regulated proteins (fold change>2, p<0.05) in resistant strain as compared to reference strain. Some of the upregulated proteins in resistant strain and their association with carbapenem resistance in A.baumannii are: i) ß-lactamases, AmpC and OXA-51: cleave and inactivate carbapenem ii) metabolic enzymes, ATP synthase, malate dehydrogenase and 2-oxoglutarate dehydrogenase: help in increased energy production for the survival and iii) elongation factor Tu and ribosomal proteins: help in the overall protein production. Further, entry of carbapenem perhaps is limited by controlled production of OmpW and low levels of surface antigen help to evade host defence mechanism in developing resistance in A.baumannii. Present results support a model for the importance of proteins of inner-membrane fraction and their synergistic effect in the mediation of resistance of A.baumannii to carbapenem.

Carbapenem-hydrolyzing oxacillinase in high resistant strains of Acinetobacter baumannii isolated from India.

Acinetobacter baumannii, a Gram negative bacterium causes nosocomial infections including bacteremia, secondary meningitis and urinary tract infections. Increased resistance of A. baumannii has been global concern. Till recently, carbapenems, latest generation of ß-lactams are used for treating infections caused by A. baumannii. Emerging resistance to carbapenem class is an immediate threat to mankind. The objective of present study is to understand the growing carbapenem resistance of A. baumannii. By using iso-electric focusing followed by (in-gel) nitrocefin assay of carbapenem resistant strains of A. baumannii, we could identify three ß-lactamases with pIs in the range 5.4-9.5. Expression of the ß-lactamase with a pI ≈ 8.5, was found only in very high carbapenem resistant (MIC for imipenem 128 µg/ml) strains. On PCR analysis and sequencing of PCR product, this ß-lactamase was confirmed to be OXA-51. Identification of this protein from IEF gel was reconfirmed with the help of Liquid chromatography and Tandem mass spectrometry (LC-MS/MS). Based on the amino acid sequence, OXA-51 found to be a 30 kDa ß-lactamase containing conserved functional motifs of class D serine ß-lactamase. In the present study, we have established the emergence of OXA-51 in clinical strains of A. baumannii in India which suggests its role in carbapenem resistance.

Polysaccharide nanofibrous scaffolds as a model for in vitro skin tissue regeneration.

Tissue engineering and nanotechnology have advanced a general strategy combining the cellular elements of living tissue with sophisticated functional biocomposites to produce living structures of sufficient size and function at a low cost for clinical relevance. Xylan, a natural polysaccharide was electrospun along with polyvinyl alcohol (PVA) to produce Xylan/PVA nanofibers for skin tissue engineering. The Xylan/PVA glutaraldehyde (Glu) vapor cross-linked nanofibers were characterized by SEM, FT-IR, tensile testing and water contact angle measurements to analyze the morphology, functional groups, mechanical properties and wettability of the fibers for skin tissue regeneration. The cell-biomaterial interactions were studied by culturing human foreskin fibroblasts on Xylan/PVA Glu vapor cross-linked and Xylan/PVA/Glu blend nanofibrous scaffolds. The observed results showed that the mechanical properties (72 %) and fibroblast proliferation significantly increased up to 23 % (P < 0.05) in 48 h Glu vapor cross-linked nanofibers compared to 24 h Glu vapor cross-linked Xylan/PVA nanofibers. The present study may prove that the natural biodegradable Xylan/PVA nanofibrous scaffolds have good potential for fibroblast adhesion, proliferation and cell matrix interactions relevant for skin tissue regeneration.

In-silico modeling of a novel OXA-51 from ß-lactam-resistant Acinetobacter baumannii and its interaction with various antibiotics.

Acinetobacter baumannii, one of the major Gram negative bacteria, causes nosocomial infections such as pneumonia, urinary tract infection, meningitis, etc. ß-lactam-based antibiotics like penicillin are used conventionally to treat infections of A. baumannii; however, they are becoming progressively less effective as the bacterium produces diverse types of ß-lactamases to inactivate the antibiotics. We have recently identified a novel ß-lactamase, OXA-51 from clinical strains of A. baumannii from our hospital. In the present study, we generated the structure of OXA-51 using MODELLER9v7 and studied the interaction of OXA-51 with a number of ß-lactams (penicillin, oxacillin, ceftazidime, aztreonam and imipenem) using two independent programs: GLIDE and GOLD. Based on the results of different binding parameters and number of hydrogen bonds, interaction of OXA-51 was found to be maximum with ceftazidime and lowest with imipenem. Further, molecular dynamics simulation results also support this fact. The lowest binding affinity of imipenem to OXA-51 indicates clearly that it is not efficiently cleaved by OXA-51, thus explaining its high potency against resistant A. baumannii. This finding is supported by experimental results from minimum inhibitory concentration analysis and transmission electron microscopy. It can be concluded that carbapenems (imipenem) are presently effective ß-lactam antibiotics against resistant strains of A. baumannii harbouring OXA-51. The results presented here could be useful in designing more effective derivatives of carbapenem.