Symphytum officinale augments osteogenesis in human bone marrow-derived mesenchymal stem cells in vitro as they differentiate into osteoblasts

ETHNOPHARMACOLOGICAL RELEVANCE

Mesenchymal stem cells (MSCs) are multipotent stem cells possessing regenerative potential. Symphytum officinale (SO) is a medicinal plant and in homoeopathic literature, believed to accelerate bone healing.

AIM OF THE STUDY

This study aimed to determine if homoeopathic doses of SO could augment osteogenesis in MSCs as they differentiate into osteoblasts in vitro.

MATERIALS AND METHODS

Bone marrow samples were obtained from patients who underwent bone grafting procedures (n = 15). MSCs were isolated, expanded and characterized by flow cytometry (CD90, CD105). Cytotoxicity of SO was evaluated by MTT assay. Osteogenic differentiation was induced in MSCs with β-glycerophosphate, ascorbic acid and dexamethasone over 2 weeks. Different homoeopathic doses of SO (MT, 3C, 6C, 12C and 30C) were added to the basic differentiation medium (BDM) and efficiency of MSCs differentiating into osteoblasts were measured by evaluating expression of Osteocalcin using flow cytometry, and alkaline phosphatase activity using ELISA. Gene expression analyses for osteoblast markers (Runx-2, Osteopontin and Osteocalcin) were evaluated in differentiated osteoblasts using qPCR.

RESULTS

Flow cytometry (CD90, CD105) detected MSCs isolated from bone marrow (93-98%). MTT assay showed that the selected doses of SO did not induce any cytotoxicity in MSCs (24 hours). The efficiency of osteogenic differentiation (2 weeks) for different doses of Symphytum officinale was determined by flow cytometry (n = 10) for osteoblast marker, Osteocalcin, and most doses of Symphytum officinale enhanced osteogenesis. Interestingly, gene expression analysis for Runx-2 (n = 10), Osteopontin (n = 10), Osteocalcin (n = 10) and alkaline phosphatase activity (n = 8) also showed increased osteogenesis with the addition of Symphytum officinale to BDM, specially mother tincture.

CONCLUSIONS

Our findings suggest that homoeopathic dose (specially mother tincture) of Symphytum officinale has the potential to enhance osteogenesis.

5963Automated quantification of epicardial adipose tissue from non-contrast CT on multi-center and multi-vendor data using deep learning

Background

Epicardial adipose tissue (EAT), a metabolically active visceral fat depot surrounding the coronary arteries, has been shown to promote the development of atherosclerosis in underlying coronary vasculature.

Purpose

We evaluate the performance of deep learning (DL), a sub-group of machine learning algorithms, for robust and fully automated quantification of EAT on multi-center cardiac CT data.

Methods

In this study, 850 non-contrast calcium scoring CT scans, from multiple cohorts, scanners and protocols, with manual measurements of EAT from 3 different readers were considered. The DL method was based on a convolutional neural network trained to reproduce the expert measurement. DL global performance was first assessed using all the scans, and then compared to inter-observer variability on a subset of 141 scans. Finally, automated EAT progression was compared to manual measurement using baseline and follow-up serial scans available for 70 subjects. The proposed model was validated using 10-fold cross validation.

Results

Automated quantification was performed in 1.57±0.49 seconds compared to 15 minutes for manual measurement. DL provided high agreement with expert manual quantification for all scans (R=0.974, p<0.001) with no significant bias (0.53 cm3, p=0.13). EAT volume was higher in patients with hypertension (+18.02 cm3, p<0.001, N=442), with diabetes (+18.33 cm3, p<0.001, N=75) and with hypercholesterolemia (+7.33 cm3, p=0.039, N=508). Manual EAT volumes measured by two experienced readers on 141 scans were highly correlated (R=0.984, p<0.001) but presented a significant difference of 4.35 cm3 (p<0.001). On these 141 scans, DL quantifications were highly correlated to both experts' measurements (R=0.973, p<0.001; R=0.979, p<0.001) with significant and non-significant bias for readers 1 and 2 (5.19 cm3, p<0.001; 0.84 cm3, p=0.26), respectively. In 70 subjects, EAT progression quantified by DL correlated strongly with EAT progression measured by the expert reader (R=0.905, p<0.001) with no significant bias (0.64 cm3, p=0.43), and was related to increased non-calcified plaque burden quantified from coronary CT angiography (5.7% vs 1.8%, p=0.026).

Automated vs. manual EAT volume

Conclusion

Deep learning allows rapid, robust and fully automated quantification of EAT from calcium scoring CT. It performs as an expert reader and can be implemented for routine cardiovascular risk assessment.

Acknowledgement/Funding

1R01HL133616/01EX1012B/Adelson Medical Research Foundation

P6151Fully automated epicardial adipose tissue volume and density measured from non-contrast CT predict major adverse cardiovascular events in asymptomatic subjects

Background

Epicardial adipose tissue (EAT) volume and density has shown to correlate with standard markers of coronary artery disease (CAD) and may predict major adverse cardiovascular events (MACE).

Purpose

We aimed to evaluate the prognostic value of EAT volume and density measured by fully automated deep-learning software from non-contrast cardiac computed tomography (CT).

Methods

We assessed 2071 consecutive asymptomatic subjects (age 56±9 years, 59% male) from the EISNER (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) trial with long-term follow-up after coronary artery calcium (CAC) measurement. EAT volume and mean density were quantified using automated deep-learning software from non-contrast cardiac CT. MACE was defined as myocardial infarction (MI), cardiac death, late (>90 days) revascularization and acute coronary syndrome (ACS). EAT volume and density were systematically compared to CAC score and atherosclerotic cardiovascular disease (ASCVD) risk score using Cox proportional hazards regression for MACE prediction.

Results

At 14±3 years, 217 subjects suffered MACE. In age-and-gender-adjusted multivariate analysis, ASCVD risk score, CAC (two-fold increase) and EAT volume (two-fold increase) were associated with increased risk of suffering MACE [Hazard Ratio (HR) (95% CI): 1.03 (1.01–1.04); 1.25 (1.19–1.30); and 1.36 (1.08–1.70) respectively, p<0.01 for all] (Figure); the corresponding Harrell's C-statistic was 0.76. The area-under-the curve from receiver-operator characteristic analysis for MACE prediction increased significantly from 0.69 to 0.77 (p<0.0001) when EAT volume and CAC were added to the current clinical standard (ASCVD, family history and obesity measures BMI and BSA). Both in men and women, increase in EAT volume was associated with increased risk of MACE, with HR 1.14 (1.06–1.22), p<0.001 in men vs. 1.15 (1.01–1.31), p=0.03 in women, for each 20 cubic centimeter increase in volume. EAT density (HU) was independently inversely associated with MACE [HR: 0.96 (0.93–0.99), p=0.01].

MACE Prediction

Conclusions

EAT volume and density measurements improve prediction of MACE in asymptomatic populations over the current clinical standard. Fully automated EAT volume and density quantification by deep-learning from non-contrast cardiac CT can provide additional prognostic value for the asymptomatic patient.

Acknowledgement/Funding

1R01HL133616, Forschungsstiftung Medizin Universitätsklinikum Erlangen, grant from Dr Miriam and Sheldon G. Adelson Medical Research Foundation

5966Whole-vessel coronary 18F-sodium fluoride coronary microcalfication activity is associated with Low density plaque

Background

18F-sodium fluoride (18F-NaF) showed promise in imaging vulnerable coronary plaques. To date reporting of the highest per patient target to background ratio (TBR), total number of lesions with visual uptake and whole-heart tracer activity have been proposed. Unfortunately, each of these approaches has limitations which become especially prominent in patients with multiple foci of uptake, where reproducible global per-vessel measures are required. In oncology, the total metabolic active tumor volume has been found to be a significant prognostic factor for disease progression, recurrence and death. We evaluated if such methodology could be applied to coronary PET imaging.

Purpose

To quantify whole-vessel coronary 18F-NaF PET activity by utilizing automatically derived coronary vessel regions of interest (ROI) from CT angiography and assess the relationship between coronary microcalcification activity (CMA) and per vessel quantitative plaque characteristics on coronary CT angiography (CTA).

Methods

Twenty patients (68±6 years old, 70% males) with multivessel coronary artery disease underwent a 30 min single bed position PET 1h after a 250mB injection of 18F-NaF and CTA on a hybrid PET/CT scanner. We assessed coronary 18F-NaF uptake using novel whole-vessel tubular and tortuous 3D ROIs which were automatically extracted from CTA datasets. Within such ROIs we measured mean standard uptake value (SUV), maximum TBR (TBRmax) and the activity of voxels (CMA) above 1.25 the background SUV (left atrium activity). We used a previously established 1.25 TBRmax threshold to distinguish vessels positive and negative for 18F-NaF uptake. Coronary CTA datasets were analyzed by semi-automated software to quantify volumes and percentage lesion content of non-calcified plaque (NCP), low-density non-calcified plaque (LD-NCP, attenuation <30 Hounsfield units) and calcified plaque (CP).

Results

13 (65%) patients and 24 (40%) out of 60 main epicardial vessels presented with 18F-NaF uptake exceeding the 1.25 TBRmax threshold. While coronaries positive for uptake had higher CMA 0.92 [0.17, 2.03] vs 0.0, p<0.001 and TBRmax 1.42 [1.35, 1.74] vs 1.09 [1.0, 1.19], there was no difference in whole-vessel SUVmean 0.90 [0.77, 1.17] vs 0.87 [0.78, 0.96], p=0.33 compared to 18F-NaF negative arteries. Of the quantitative plaque characteristics vessels positive for uptake had higher NCP 278.4 [145.6, 576.9] vs 184.6 [63.8, 367.0]mm3, p=0.030; and LD-NCP 8.4 [0.3, 11.0] vs 2.7 [12.1, 43.5]mm3, p=0.01. CMA showed a stronger correlation with LD-NCP (r=0.70, p<0.001) than TBRmax (r=0.52, p<0.001). On regression analysis LD-NCP acted as an independent predictor of CMA after adjustments for CP and vessel SUVmean (p<0.001).

Figure 1

Conclusions

Whole-vessel 18F-NaF coronary microcalcification activity assessment with CT angiography automatically derived 3-dimensional ROIs is feasible and the measured coronary microcalcification burden correlates well with low density plaque.

Acknowledgement/Funding

This research was supported by grants R01HL135557 and R01HL133616 from the NHLBI/NIH and a grant from the Dr. Miriam & Sheldon G. Adelson MRF

P6184Association of coronary plaque characteristics and the translesional gradient by FFRct in asymptomatic patients with newly diagnosed type-2 diabetes mellitus

Background

Coronary CT angiography (CCTA) derived fractional flow reserve (FFRct) is increasingly for decision-making in patients with stable chest pain. The relation between vessel specific plaque characteristics and the translesional gradient by FFRct in patients with type-2 diabetes mellitus (T2DM) is not fully explored.

Purpose

To examine the association between vessel specific plaque characteristics as determined by CCTA and the translesional gradient as assessed by FFRct in asymptomatic patients with newly diagnosed T2DM.

Methods

Total plaque volume and the volumes of calcified plaque (CP), low-density noncalcified plaque (LD-NCP) and non-LD-NCP were assessed on a per-vessel basis by quantitative plaque analysis using Autoplaque. Irregularities of the vessel wall giving a vessel-specific total plaque volume <50 mm3 were excluded from the analyses. Positive remodeling was defined by a remodeling index >1.1. Spotty calcification was defined as calcifications comprising <90° of the vessel circumference and <3 mm length. FFRct-analysis was performed from standard acquired CCTA data sets by HeartFlow. Any FFRct-value in the major coronary arteries >1.8 mm in diameter was registered. The translesional gradient, defined as the difference of FFRct-values immediately proximal and distal to lesion, was calculated in most severe lesion per-vessel. Lesions were categorized according to a ΔFFRct threshold of 0.06. Plaque analysis and comparison to ΔFFRct were performed by staff blinded to patient data.

Results

A total of 76 patients; age, mean (SD): 56 (11) years; males, n (%): 49 (65), with newly diagnosed (<1 year) T2DM were studied. Haemoglobin A1c, median (IQR) was 45 mmol/L (42–50). Risk factors, mean (SD) were as follows: total-cholesterol, 4.4 mmol/L (1.0); LDL-cholesterol, 2.5 mmol/L (0.8); systolic blood pressure, 131 mmHg (12). In the analysis 57 vessels in 30 patients were included, while 24 vessels were classified as having irregularities. ΔFFRct ≥0.06 was registered in 22 (39%) plaques. Vessel specific plaque volumes (mm3), ΔFFRct ≥0.06 vs. ΔFFRct <0.06, were, median (IQR): LD-NCP, 28.1 (9.5–62.3) vs. 18.3 (10.2–27.5); non-LD-NCP, 129.5 (74.1–186.8) vs. 98.1 (65.7–142.1); total plaque volume, 209.4 (137.1–359.3) vs. 139.6 (108.3–220.0), all p>0.05. The vessel-specific CP volume, median (IQR), was higher in vessels with ΔFFRct ≥0.06 vs. ΔFFRct <0.06: 51.9 (20.5–85.4) vs. 13.5 (4.1–68.5), p=0.015. Adverse plaque characteristics ΔFFRct ≥0.06 vs. ΔFFRct <0.06, were, n (%): positive remodeling, 21 (95%) vs. 34 (97%) and spotty calcification, 9 (41%) vs. 14 (40%). The relative distribution of vessel specific plaque components according to ΔFFRct is illustrated in the Figure.

Conclusion

In asymptomatic patients with newly diagnosed and well-controlled T2DM, the occurrence of high-risk coronary plaque features was frequently observed. The applied translesional gradient by FFRct was not predictive of adverse coronary plaque characteristics.

Acknowledgement/Funding

The Danish Diabetes Academy supported by the Novo Nordisk Foundation; University of Southern DenmarkCenter Southwest, Denmark

30Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium and epicardial adipose tissue: a prospective study

Background/Introduction

Machine learning (ML) allows objective integration of clinical and imaging data for the prediction of events. ML prediction of cardiovascular events in asymptomatic subjects over long-term follow-up, utilizing quantitative CT measures of coronary artery calcium (CAC) and epicardial adipose tissue (EAT) have not yet been evaluated.

Purpose

To analyze the ability of machine learning to integrate clinical parameters with coronary calcium and EAT quantification in order to improve prediction of myocardial infarction (MI) and cardiac death in asymptomatic subjects.

Methods

We assessed 2071 consecutive subjects [1230 (59%) male, age: 56.049.03] from the EISNER (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) trial with long-term follow-up after non-enhanced cardiac CT. CAC (Agatston) score, age-and-gender-adjusted CAC percentile, and aortic calcium scores were obtained. EAT volume and density were quantified using a fully automated deep learning method. Extreme gradient boosting, a ML algorithm, was trained using demographic variables, plasma lipid panel measurements, risk factors as well as CAC, aortic calcium and EAT measures from CAC CT scans. ML was validated using 10-fold cross validation; event prediction was evaluated using area-under-receiver operating characteristic curve (AUC) analysis and Cox proportional hazards regression. Optimal ML cut-point for risk of MI and cardiac death was determined by highest Youden's index (sensitivity + specificity – 1).

Results

At 152 years' follow-up, 76 events of MI and/or cardiac death had occurred. ML obtained a significantly higher AUC than the ASCVD risk and CAC score in predicting events (ML: 0.81; ASCVD: 0.76, p<0.05; CAC: 0.75, p<0.01, Figure A). ML performance was mostly driven by age, ASCVD risk and calcium as shown by the variable importance (Figure B); however, all variables with non-zero gain contributed to the ML performance. ML achieved a sensitivity and specificity of 77.6% and 73.5%, respectively. For an equal specificity, ASCVD and CAC scores obtained a sensitivity of 61.8% and 67.1%, respectively. High ML risk was associated with a high risk of suffering an event by Cox regression (HR: 9.25 [95% CI: 5.39–15.87], p<0.001; survival curves in Figure C). The relationships persisted when adjusted for age, gender, CAC, CAC percentile, aortic calcium score, and ASCVD risk score; with a hazard ratio of 3.42 for high ML risk (HR: 3.42 [95% CI: 1.54–7.57], p=0.002).

Conclusion(s)

Machine learning used to integrate clinical and quantitative imaging-based variables significantly improves prediction of MI and cardiac death in asymptomatic subjects undergoing CAC assessment, compared to standard risk assessment methods.

Acknowledgement/Funding

NHLBI 1R01HL13361, Bundesministerium für Bildung und Forschung (01EX1012B), Dr. Miriam and Sheldon G. Adelson Medical Research Foundation

Sex differences in coronary plaque composition evaluated by coronary computed tomography angiography in newly diagnosed Type 2 diabetes: association with low-grade inflammation

AIM

To determine differences in coronary plaque composition and inflammatory biomarkers between men and women with newly diagnosed Type 2 diabetes without known cardiovascular disease.

METHODS

A total of 88 people with newly diagnosed (<1 year) Type 2 diabetes underwent contrast-enhanced coronary computed tomography angiography. Advanced coronary plaque analysis was performed using semi-automated software. Plasma concentrations of inflammatory biomarkers were determined.

RESULTS

There were no significant differences between men (n=60) and women (n=28) regarding age or cardiovascular risk factors (all P>0.05). The median (quartiles) serum levels of fibrinogen [10.9 (9.8-12.6) μmol/l vs 9.7 (8.8-10.9) μmol/l], fibrin d-dimer [0.3 (0.2-0.4) mg/l vs 0.27 (0.2-0.4) mg/l] and C-reactive protein [3.1 (1.1-5.2) mg/l vs (0.8-2.6) 1.6 mg/l] were significantly higher in women (all P<0.05). Overall, men more often had multi-vessel involvement [28 men (47%) vs 4 women (14%)], and higher total plaque burden [median (quartiles) 11.6 (2.3-36.0)% vs 2.0 (0.4-5.4)%; both P<0.05]. The median (quartiles) total plaque volume [269.9 (62.6-641.9) mm³ vs 61.1 (7.6-239.9) mm³ ] and absolute calcified plaque volume [33.5 (8.3-148.3) mm³ vs 4.7 (0.9-17.3) mm³ ] were higher in men (both P<0.05). Women had a lower relative proportion of the calcified plaque component [median (quartiles) 7.8 (4.7-15.4)% vs 23.7 (8.4-31.1)%] and a higher relative proportion (median [quartiles]) of the non-low-density non-calfied plaque component [77.6 (66.0-86.0)% vs 63.6 (54.0-72.9)%; both P<0.05].

CONCLUSIONS

In people with newly diagnosed Type 2 diabetes, women had lower absolute coronary plaque volumes but a more unfavourable plaque composition and enhanced systemic inflammation compared with men.

Exposure to sub-inhibitory concentrations of gentamicin, ciprofloxacin and cefotaxime induces multidrug resistance and reactive oxygen species generation in meticillin-sensitive Staphylococcus aureus

PURPOSE

The role of antibiotics below their MIC in the development of bacterial drug resistance is becoming increasingly important. We investigated the effect of sub-MICs of bactericidal antibiotics on the susceptibility pattern of Staphylococcus aureus and evaluated the role of free radicals.

METHODOLOGY

A total of 12 S. aureus strains were recovered from pus samples and their antibiograms determined. The test isolates were treated with sub-MIC levels of tetracycline, gentamicin, ciprofloxacin and cefotaxime. Alterations in their respective breakpoints were observed along with measurements of free radical generation by nitro blue tetrazolium test.Results/Key findings. Gentamicin, ciprofloxacin and cefotaxime exposure significantly altered the breakpoints of exposed isolates against several tested antibiotics and higher levels of free radicals were generated after antibiotic exposure.

CONCLUSIONS

Our study demonstrates that sub-MIC levels of antimicrobials can lead to resistance and cross-resistance across several classes of antibiotics in wild strains of S. aureus, possibly by free radical production. The molecular mechanisms behind the acquisition of drug resistance at low antibiotic concentrations and the specific target genes of reactive oxygen speciesneed to be explored further.

Urethral involvement of myeloma: A rare case of visible haematuria leading to a diagnosis of relapsed multiple myeloma after curative stem cell transplantation

Extramedullary multiple myeloma involving the urinary tract is extremely rare. We report an unusual case of visible haematuria in a 45-year-old male who had a stem cell transplant for multiple myeloma 18 months previously. Cysto-urethroscopy revealed a mid-urethral lesion that was then fully excised by endoscopic resection. Histology confirmed malignant plasma cell infiltrate with subsequent staging and skeletal biopsy of a rib lesion confirming relapse of multiple myeloma. We believe this is the first case of urethral involvement to reveal a relapse of multiple myeloma after autologous stem cell transplant.

Selective breaking of bonds in water with intense, 2-cycle, infrared laser pulses

One of the holy grails of contemporary science has been to establish the possibility of preferentially breaking one of several bonds in a molecule. For instance, the two O-H bonds in water are equivalent: given sufficient energy, either one of them is equally likely to break. We report bond-selective molecular fragmentation upon application of intense, 2-cycle pulses of 800 nm laser light: we demonstrate up to three-fold enhancement for preferential bond breaking in isotopically substituted water (HOD). Our experimental observations are rationalized by means of ab initio computations of the potential energy surfaces of HOD, HOD(+), and HOD(2+) and explorations of the dissociation limits resulting from either O-H or O-D bond rupture. The observations we report present a formidable theoretical challenge that need to be taken up in order to gain insights into molecular dynamics, strong field physics, chemical physics, non-adiabatic processes, mass spectrometry, and time-dependent quantum chemistry.

Polyphenolic Secondary Metabolites Synergize the Activity of Commercial Antibiotics against Clinical Isolates of β-Lactamase-producing Klebsiella pneumoniae

Emergence of worldwide antimicrobial resistance prompted us to study the resistance modifying potential of plant-derived dietary polyphenols, mainly caffeic acid, ellagic acid, epigallocatechin-3-gallate (EGCG) and quercetin. These compounds were studied in logical combination with clinically significant antibiotics (ciprofloxacin/gentamicin/tetracycline) against Klebsiella pneumoniae, after conducting phenotypic screening of a large number of clinical isolates and selecting the relevant strains possessing extended-spectrum β-lactamase (ESBL) and K. pneumoniae carbapenemase (KPC)-type carbapenemase enzymes only. The study demonstrated that EGCG and caffeic acid could synergize the activity of tested antibiotics within a major population of β-lactamase-producing K. pneumoniae. In spectrofluorimetric assay, ~17-fold greater ciprofloxacin accumulation was observed within K. pneumoniae cells pre-treated with EGCG in comparison with the untreated control, indicating its ability to synergize ciprofloxacin to restrain active drug-efflux. Further, electron micrograph of ESBL-producing K. pneumoniae clearly demonstrated the prospective efficacy of EGCG towards biofilm degradation.

Genetic polymorphisms associated with sulphadoxine-pyrimethamine drug resistance among Plasmodium falciparum field isolates in malaria endemic areas of Assam

Background:

The emergence of antimalarial drug resistance malaria parasite is widespread in North eastern region of India. During January 2012-December 2013, we conducted active surveillance for detection of antifolate resistance-associated genetic polymorphisms in Plasmodium falciparum malaria parasite from different malaria endemic areas of Assam.

Materials and Methods:

A total of 281 field samples were collected from suspected malaria patients of which 106 malaria P. falciparum positive cases were detected in microscopic slide examination. A nested PCR was done for amplification of a 648 bp portion of the dhfr gene and 710 bp portion of the dhps gene.

Results:

Mutation analysis revealed existence of three different haplotypes of the P. falciparum dhfr gene of which ANRNI was highly prevalent (90%). Triple mutant haplotypes AIRNI (N51I + C59R + S108N) of the dhfr gene associated with pyrimethamine resistance were prevalent in Chirang district of Assam. Whereas, dhps mutation study revealed that triple mutant haplotype AGEAA (S436A + A437G + K540E) associated with Sulphadoxine resistance was found among 26% of P. falciparum field isolates. However, P. falciparum dhfr-dhps two locus mutation analysis showed that there were a total of nine dhfr-dhps genotypes.

Conclusion:

It was noticed that 93.62% (88/94) isolates had mutations in the sequences of both enzymes, which is an indication of prevalence of high grade of Sulphadoxine — pyrimethamine resistance in P. falciparum malaria parasites in Assam.

Antimicrobial activity of pomegranate fruit constituents against drug-resistant Mycobacterium tuberculosis and β-lactamase producing Klebsiella pneumoniae

CONTEXT

The global surge in multi-drug resistant bacteria and the imminence of tuberculosis pandemic necessitate alternative therapeutic approaches to augment the existing medications. Pomegranate, the fruit of Punica granatum Linn. (Punicaceae), widely recognized for potency against a broad spectrum of bacterial pathogens, deserves further investigation in this respect.

OBJECTIVE

This study determines the therapeutic potential of pomegranate juice, extracts of non-edible peel prepared with methanol/water, and its four polyphenolic constituents, namely caffeic acid, ellagic acid, epigallocatechin-3-gallate (EGCG) and quercetin, against drug-resistant clinical isolates.

MATERIALS AND METHODS

Phenotypic characterisation of Mycobacterium tuberculosis, extended-spectrum β-lactamase (ESBL) and KPC-type carbapenemase producing Klebsiella pneumoniae was performed by biochemical and molecular methods. Resistance profiles of M. tuberculosis and K. pneumoniae were determined using LJ proportion and Kirby-Bauer methods, respectively. Pomegranate fruit extracts, and the compounds, were evaluated at a dose range of 1024-0.5 µg/mL, and 512-0.25 µg/mL, respectively, to determine minimum inhibitory (MIC) and bactericidal concentrations (MBC) against the drug-resistant isolates by the broth micro-dilution method.

RESULTS

The peel extracts exhibited greater antimycobacterial activity (MIC 64-1024 μg/mL) than the potable juice (MIC 256 - > 1024 μg/mL). EGCG and quercetin exhibited higher antitubercular (MIC 32-256 μg/mL) and antibacterial (MIC 64-56 μg/mL) potencies than caffeic acid and ellagic acid (MIC 64-512 μg/mL).

DISCUSSION AND CONCLUSION

The pomegranate fruit peel and pure constituents were active against a broad panel of M. tuberculosis and β-lactamase producing K. pneumoniae isolates. EGCG and quercetin need further investigation for prospective application against respiratory infections.