AI-based epidemic and pandemic early warning systems: A systematic scoping review.

Background: Timely detection of disease outbreaks is critical in public health. Artificial Intelligence (AI) can identify patterns in data that signal the onset of epidemics and pandemics. This scoping review examines the effectiveness of AI in epidemic and pandemic early warning systems (EWS). Objective: To assess the capability of AI-based systems in predicting epidemics and pandemics and to identify challenges and strategies for improvement. Methods: A systematic scoping review was conducted. The review included studies from the last 5 years, focusing on AI and machine learning applications in EWS. After screening 1087 articles, 33 were selected for thematic analysis. Results: The review found that AI-based EWS have been effectively implemented in various contexts, using a range of algorithms. Key challenges identified include data quality, model explainability, bias, data volume, velocity, variety, availability, and granularity. Strategies for mitigating AI bias and improving system adaptability were also discussed. Conclusion: AI has shown promise in enhancing the speed and accuracy of epidemic detection. However, challenges related to data quality, bias, and model transparency need to be addressed to improve the reliability and generalizability of AI-based EWS. Continuous monitoring and improvement, as well as incorporating social and environmental data, are essential for future development.

Evaluation of Machine Learning Algorithms for Pressure Injury Risk Assessment in a Hospital with Limited IT Resources.

Clinical decision support systems for Nursing Process (NP-CDSSs) help resolve a critical challenge in nursing decision-making through automating the Nursing Process. NP-CDSSs are more effective when they are linked to Electronic Medical Record (EMR) Data allowing for the computation of Risk Assessment Scores. Braden scale (BS) is a well-known scale used to identify the risk of Hospital-Acquired Pressure Injuries (HAPIs). While BS is widely used, its specificity for identifying high-risk patients is limited. This study develops and evaluates a Machine Learning (ML) model to predict the HAPI risk, leveraging EMR readily available data. Various ML algorithms demonstrated superior performance compared to BS (pooled model AUC/F1-score of 0.85/0.8 vs. AUC of 0.63 for BS). Integrating ML into NP-CDSSs holds promise for enhancing nursing assessments and automating risk analyses even in hospitals with limited IT resources, aiming for better patient safety.

Identifying the panorama of potential pandemic pathogens and their key characteristics: a systematic scoping review.

The globe has recently seen several terrifying pandemics and outbreaks, underlining the ongoing danger presented by infectious microorganisms. This literature review aims to explore the wide range of infections that have the potential to lead to pandemics in the present and the future and pave the way to the conception of epidemic early warning systems. A systematic review was carried out to identify and compile data on infectious agents known to cause pandemics and those that pose future concerns. One hundred and fifteen articles were included in the review. They provided insights on 25 pathogens that could start or contribute to creating pandemic situations. Diagnostic procedures, clinical symptoms, and infection transmission routes were analyzed for each of these pathogens. Each infectious agent's potential is discussed, shedding light on the crucial aspects that render them potential threats to the future. This literature review provides insights for policymakers, healthcare professionals, and researchers in their quest to identify potential pandemic pathogens, and in their efforts to enhance pandemic preparedness through building early warning systems for continuous epidemiological monitoring.

Developing a Comprehensive Search Strategy for the Systematic Review of Clinical Decision Support Systems for Nursing Practice.

The search strategy of a literature review is of utmost importance as it impacts the validity of its findings. In order to build the best query to guide the literature search on clinical decision support systems applied to nursing clinical practice, we developed an iterative process capitalizing on previous systematic reviews published on similar topics. Three reviews were analyzed relatively to their detection performance. Errors in the choice of keywords and terms used in title and abstract (missing MeSH terms, failure to use common terms), may make relevant articles invisible.

Automated Detection of Patient Harm: Implementation and Prospective Evaluation of a Real-Time Broad-Spectrum Surveillance Application in a Hospital With Limited Resources.

OBJECTIVES: This study aimed to prospectively validate an application that automates the detection of broad categories of hospital adverse events (AEs) extracted from a basic hospital information system, and to efficiently mobilize resources to reduce the level of acquired patient harm. METHODS: Data were collected from an internally designed software, extracting results from 14 triggers indicative of patient harm, querying clinical and administrative databases including all inpatient admissions (n = 8760) from October 2019 to June 2020. Representative samples of the triggered cases were clinically validated using chart review by a consensus expert panel. The positive predictive value (PPV) of each trigger was evaluated, and the detection sensitivity of the surveillance system was estimated relative to incidence ranges in the literature. RESULTS: The system identified 394 AEs among 946 triggered cases, associated with 291 patients, yielding an overall PPV of 42%. Variability was observed among the trigger PPVs and among the estimated detection sensitivities across the harm categories, the highest being for the healthcare-associated infections. The median length of stay of patients with an AE showed to be significantly higher than the median for the overall patient population. CONCLUSIONS: This application was able to identify AEs across a broad spectrum of harm categories, in a real-time manner, while reducing the use of resources required by other harm detection methods. Such a system could serve as a promising patient safety tool for AE surveillance, allowing for timely, targeted, and resource-efficient interventions, even for hospitals with limited resources.

The Use of Medical Imaging Request Forms as Trigger Tools to Detect Intra-Hospital Adverse Events: A Pilot Study.

Aim: To evaluate the contribution of medical imaging request forms as trigger tools to detect patient adverse event (AE) occurring during hospitalization. Material and Methods: This is a retrospective study in a single institution. Between January and June 2019, the hospital information system (HIS) was fetched for request forms of radiological examinations performed for inpatients >48 hours after the admission date. The investigated request forms were: Doppler ultrasound of the upper limbs, Doppler ultrasound of the lower limbs, and the repetition of three consecutive requests of chest radiographs within 24 hrs, to detect upper or lower limb venous thrombosis, or AEs related to the respiratory system, respectively. Patients' medical charts and radiological examinations were evaluated to document the presence or absence of an AE. The frequencies of AEs in the three groups of trigger tools were compared to corresponding control groups, matched according to age, sex and length of stay. Results: Among a total of 2798 hospital admissions during the study period, there were 74 files triggered by the three types of radiological request forms. There were 6/24 AE (25%) related to upper limb venous thrombosis, 4/33 (12.1%) AE related to lower limb venous thrombosis, and 6/17 (35.3%) AE related to the respiratory system. For all the trigger tools, the frequency of AE in the study groups was significantly higher than that in the control groups. Conclusion: Medical imaging requests could be used as potential trigger tools to detect adverse events related to hospital stay.

Early Prediction of All-Cause Clinical Deterioration in General Wards Patients: Development and Validation of a Biomarker-Based Machine Learning Model Derived From Rapid Response Team Activations.

OBJECTIVE: The aim of the study is to evaluate the performance of a biomarker-based machine learning (ML) model (not including vital signs) derived from reviewed rapid response team (RRT) activations in predicting all-cause deterioration in general wards patients. DESIGN: This is a retrospective single-institution study. All consecutive adult patients' cases on noncritical wards identified by RRT calls occurring at least 24 hours after patient admission, between April 2018 and June 2020, were included. The cases were reviewed and labeled for clinical deterioration by a multidisciplinary expert consensus panel. A supervised learning approach was adopted based on a set of biomarkers and demographic data available in the patient's electronic medical record (EMR). SETTING: The setting is a 250-bed tertiary university hospital with a basic EMR, with adult (>18 y) patients on general wards. PATIENTS: The study analyzed the cases of 514 patients for which the RRT was activated. Rapid response teams were extracted from the hospital telephone log data. Two hundred eighteen clinical deterioration cases were identified in these patients after expert chart review and complemented by 146 "nonevent" cases to build the training and validation data set. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The best performance was achieved with the random forests algorithm, with a maximal area under the receiver operating curve of 0.90 and F1 score of 0.85 obtained at prediction time T0-6h, slightly decreasing but still acceptable (area under the receiver operating curve, >0.8; F1 score, >0.75) at T0-42h. The system outperformed most classical track-and-trigger systems both in terms of prediction performance and prediction horizon. CONCLUSIONS: In hospitals with a basic EMR, a biomarker-based ML model could be used to predict clinical deterioration in general wards patients earlier than classical track-and-trigger systems, thus enabling appropriate clinical interventions for patient safety and improved outcomes.

Evaluation of a Broad-Spectrum Partially Automated Adverse Event Surveillance System: A Potential Tool for Patient Safety Improvement in Hospitals With Limited Resources.

OBJECTIVE: The aim of the study was to evaluate the sensitivity and resource efficiency of a partially automated adverse event (AE) surveillance system for routine patient safety efforts in hospitals with limited resources. METHODS: Twenty-eight automated triggers from the hospital information system's clinical and administrative databases identified cases that were then filtered by exclusion criteria per trigger and then reviewed by an interdisciplinary team. The system, developed and implemented using in-house resources, was applied for 45 days of surveillance, for all hospital inpatient admissions (N = 1107). Each trigger was evaluated for its positive predictive value (PPV). Furthermore, the sensitivity of the surveillance system (overall and by AE category) was estimated relative to incidence ranges in the literature. RESULTS: The surveillance system identified a total of 123 AEs among 283 reviewed medical records, yielding an overall PPV of 52%. The tool showed variable levels of sensitivity across and within AE categories when compared with the literature, with a relatively low overall sensitivity estimated between 21% and 44%. Adverse events were detected in 23 of the 36 AE categories defined by an established harm classification system. Furthermore, none of the detected AEs were voluntarily reported. CONCLUSIONS: The surveillance system showed variable sensitivity levels across a broad range of AE categories with an acceptable PPV, overcoming certain limitations associated with other harm detection methods. The number of cases captured was substantial, and none had been previously detected or voluntarily reported. For hospitals with limited resources, this methodology provides valuable safety information from which interventions for quality improvement can be formulated.

Comparison of Machine Learning Algorithms for Classifying Adverse-Event Related 30-Day Hospital Readmissions: Potential Implications for Patient Safety.

Studies in the last decade have focused on identifying patients at risk of readmission using predictive models, in an objective to decrease costs to the healthcare system. However, real-time models specifically identifying readmissions related to hospital adverse-events are still to be elaborated. A supervised learning approach was adopted using different machine learning algorithms based on features available directly from the hospital information system and on a validated dataset elaborated by a multidisciplinary expert consensus panel. Accuracy results upon testing were in line with comparable studies, and variable across algorithms, with the highest prediction given by Artificial Neuron Networks. Features importances relative to the prediction were identified, in order to provide better representation and interpretation of results. Such a model can pave the way to predictive models for readmissions related to patient harm, the establishment of a learning platform for clinical quality measurement and improvement, and in some cases for an improved clinical management of readmitted patients.

Cytotoxicity of cucurbitacin E from Citrullus colocynthis against multidrug-resistant cancer cells.

BACKGROUND: Cucurbitacin E (CuE) is an oxygenated tetracyclic triterpenoid isolated from the fruits of Citrullus colocynthis (L.) Schrad. PURPOSE: This study outlines CuE's cytotoxic activity against drug-resistant tumor cell lines. Three members of ABC transporters superfamily, P-glycoprotein (P-gp), breast cancer resistance protein (BCRP) and ABCB5 were investigated, whose overexpression in tumors is tightly linked to multidrug resistance. Further factors of drug resistance studied were the tumor suppressor TP53 and the epidermal growth factor receptor (EGFR). METHODS: Cytotoxicity assays (resazurin assays) were used to investigate the activity of Citrullus colocynthis and CuE towards multidrug resistant cancer cells. Molecular docking (In silico) has been carried out to explore the CuE's mode of binding to ABC transporters (P-gp, BCRP and ABCB5). The visualization of doxorubicin uptake was done by a Spinning Disc Confocal Microscope. The assessment of proteins expression was done by western blotting analysis. COMPARE and hierarchical cluster analyses were applied to identify, which genes correlate with sensitivity or resistance to cucurbitacins (CuA, CuB, CuE, CuD, CuI, and CuK). RESULTS: Multidrug-resistant cells overexpressing P-gp or BCRP were cross-resistant to CuE. By contrast, TP53 knock-out cells were sensitive to CuE. Remarkably, resistant cells transfected with oncogenic ΔEGFR or ABCB5 were hypersensitive (collateral sensitive) to CuE. In silico analyses demonstrated that CuE is a substrate for P-gp and BCRP. Immunoblot analyses highlighted that CuE targeted EGFR and silenced its downstream signaling cascades. The most striking result that emerged from the doxorubicin uptake by ABCB5 overexpressing cells is that CuE is an effective inhibitor for ABCB5 transporter when compared with verapamil. The COMPARE analyses of transcriptome-wide expression profiles of tumor cell lines of the NCI identified common genes involved in cell cycle regulation, cellular adhesion and intracellular communication for different cucurbitacins. CONCLUSION: CuE represents a potential therapeutic candidate for the treatment of certain types of refractory tumors. To best of our knowledge, this is the first time to identify CuE and verapamil as inhibitors for ABCB5 transporter.

Phytochemical and pharmacological properties of essential oils from Cedrus species.

Natural products frequently exert pharmacological activities. The present review gives an overview of the ethnobotany, phytochemistry and pharmacology of the Cedrus genus, e.g. cytotoxic, spasmolytic immunomodulatory, antiallergic, anti-inflammatory and analgesic activities. Cancer patients frequently seek remedies from traditional medicinal plants that are believed to exert less side effects than conventional therapy with synthetic drugs. A long-lasting goal of anti-cancer and anti-microbial therapy research is to find compounds with reduced side effects compared to currently approved drugs. In this respect, Cedrus species might be of interest. The essential oil isolated from Cedrus libani leaves may bear potential for drug development due to its high concentrations of germacrene D and ß-caryophyllene. The essential oils from Cedrus species also show bioactivity against bacteria and viruses. More preclinical analyses (e.g. in vivo experiments) as well as clinical trials are required to evaluate the potential of essential oils from Cedrus species for drug development.

Biopiracy of natural products and good bioprospecting practice.

BACKGROUND: Biopiracy mainly focuses on the use of biological resources and/or knowledge of indigenous tribes or communities without allowing them to share the revenues generated out of economic exploitation or other non-monetary incentives associated with the resource/knowledge. METHODS: Based on collaborations of scientists from five continents, we have created a communication platform to discuss not only scientific topics, but also more general issues with social relevance. This platform was termed 'PhytCancer -Phytotherapy to Fight Cancer' (www.phyt-cancer.uni-mainz.de). As a starting point, we have chosen the topic "biopiracy", since we feel this is of pragmatic significance for scientists working with medicinal plants. RESULTS: It was argued that the patenting of herbs or natural products by pharmaceutical corporations disregarded the ownership of the knowledge possessed by the indigenous communities on how these substances worked. Despite numerous court decisions in U.S.A. and Europe, several international treaties, (e.g. from United Nations, World Health Organization, World Trade Organization, the African Unity and others), sharing of a rational set of benefits amongst producers (mainly pharmaceutical companies) and indigenous communities is yet a distant reality. In this paper, we present an overview of the legal frameworks, discuss some exemplary cases of biopiracy and bioprospecting as excellent forms of utilization of natural resources. CONCLUSIONS: We suggest certain perspectives, by which we as scientists, may contribute towards prevention of biopiracy and also to foster the fair utilization of natural resources. We discuss ways, in which the interests of indigenous people especially from developing countries can be secured.

Berberis libanotica extract targets NF-κB/COX-2, PI3K/Akt and mitochondrial/caspase signalling to induce human erythroleukemia cell apoptosis.

The aim of this study was to describe and understand the relationship between cyclooxygenase-2 (COX-2) expression and apoptosis rate in erythroleukemia cells after apoptosis induction by Berberis libanotica (Bl) extract. To achieve this goal we used erythroleukemia cell lines expressing COX­2 (HEL cell line) or not (K562 cell line). Moreover, we made use of COX­2 cDNA to overexpress COX­2 in K562 cells. In light of the reported chemopreventive and chemosensitive effects of natural products on various tumor cells and animal models, we postulated that our Bl extract may mediate their effects through apoptosis induction with suppression of cell survival pathways. Our study is the first report on the specific examination of intrinsic apoptosis and Akt/NF-κB/COX­2 pathways in human erythroleukemia cells upon Bl extract exposure. Even if Bl extract induced apoptosis of three human erythroleukemia cell lines, a dominant effect of Bl extract treatment on K562 cells was observed resulting in activation of the late markers of apoptosis with caspase-3 activation, PARP cleavage and DNA fragmentation. Whereas, we showed that Bl extract reduced significantly expression of COX­2 by a dose-dependent manner in HEL and K562 (COX­2+) cells. Furthermore, in regard to our results, it is clear that the simultaneous inhibition of Akt and NF-κB signalling can significantly contribute to the anticancer effects of Bl extract in human erythroleukemia cells. We observed that the Bl extract is clearly more active than the berberine alone on the induction of DNA fragmentation in human erythro-leukemia cells.

Laurus nobilis L. Seed Extract Reveals Collateral Sensitivity in Multidrug-Resistant P-Glycoprotein-Expressing Tumor Cells.

The frequent failure of standard cancer chemotherapy requires the development of novel drugs capable of killing otherwise drug-resistant tumors. Here, we have investigated a chloroform extract of Laurus nobilis seeds. Fatty acids and 23 constituents of the volatile fraction were identified by gas chromotography/flame ionization detection (GC/FID) and gas chromatography/mass spectrometry (GC/MS), in good agreement with (1)H NMR (nuclear magnetic resonance) spectrum. Multidrug-resistant P-glycoprotein-expressing CEM/ADR5000 leukemia cells were hypersensitive (collaterally sensitive) toward this extract compared to drug-sensitive CCRF-CEM cells, whereas CEM/ADR5000 cells were 2586-fold resistant to doxorubicin as control drug. Collateral sensitivity was verified by measurement of apoptotic cells by flow cytometry. The log10IC50 values of 3 compounds in the extract (limonene, eucalyptol, oleic acid) did not correlate with mRNA expression of the P-glycoprotein-coding ABCB1/MDR1 gene and accumulation of the P-glycoprotein substrate rhodamine in the NCI panel of tumor cell lines. A microarray-based profile of 20 genes predicted resistance to doxorubicin and 7 other anticancer drugs involved in the multidrug resistance phenotype but not to limonene, eucalyptol and oleic acid. In conclusion, our results show that Laurus nobilis seed extract is suitable to kill multidrug-resistant P-glycoprotein expressing tumor cells.

Berberis aetnensis and B. libanotica: a comparative study on the chemical composition, inhibitory effect on key enzymes linked to Alzheimer's disease and antioxidant activity.

OBJECTIVES: This study involves for the first time the evaluation of Berberis aetnensis C. Presl. and Berberis libanotica Ehrenb. ex C.K. Schneid. roots for anticholinesterase and antioxidant properties, with the aim to search compounds possibly useful for the treatment of Alzheimer's disease (AD). METHODS: Samples were evaluated for their ability to inhibit acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). The antioxidant activity was assayed by 2,2-diphenyl-1-picrylhydrazyl radical and ß-carotene bleaching tests. Berberine and palmatine were isolated by flash chromatography and identified by spectrometric methods as main constituents. Non-polar compounds were analysed by gas chromatography and gas chromatography-mass spectrometry. KEY FINDINGS: Extracts, fractions and isolated compounds inhibited AChE and BChE to varying degrees. The methanol fractions exhibited the strongest AChE inhibitory activity with inhibitory concentration 50% (IC50 ) of 7.6 and 16.9 µg/ml for B. aetnensis and B. libanotica, respectively. The alkaloid fraction of B. aetnensis inhibited AChE (IC50 of 24.5 µg/ml) and possessed the highest antioxidant activity (IC50 value of 2.2 µg/ml in ß-carotene-bleaching test after 30 min of incubation). Berberine was more potent of palmatine against AChE (IC50 of 2.2 and 7.4 µg/ml, respectively). CONCLUSIONS: These findings raise the possibility of developing B. aetnensis and B. libanotica as a promising candidate for the treatment of AD.

Synthesis and antiproliferative activity of quinolone nucleosides against the human myelogenous leukemia k-562 cell line.

A set of 6-substituted quinolone nucleosides linked to aniline or phenol via N or O heteroatom-bridges presenting new compounds were synthesized by palladium-catalyzed Buchwald-Hartwig cross-coupling reactions. 6-Bromoquinolone nucleoside precursors, being protected by either benzoyl or TBDMS protecting groups on the ribose moiety, were subjected to different Buchwald-Hartwig conditions as the key step. Defined deprotection steps led, in good yields, to the final target compounds that carry, in position 3, either ester, acid, or amide functions. Thus, a series of novel quinolone nucleoside derivatives was obtained via a convergent synthesis route. Biological tests in human chronic myelogenous leukemia K562 cells exerted an efficient antiproliferative activity for two of them without induction of differentiation. These novel nucleosides deserve further experiments to determine their antiproliferative effects on other CML cell lines.

Antiproliferative and erythroid differentiation of piperazine and triphenyl derivatives against k-562 human chronic myelogenous leukemia.

Five piperazine derivatives (S)-4-benzyl-1-(4-bromo-3-methylphenyl)-2 methylpiperazine (A), (S)-1-benzyl-3-isobutylpiperazine-2,5-dione (B), (S)-1-benzyl-3 methylpiperazine-2,5-dione (C), (S)-1,3-dibenzylpiperazine-2,5-dione (D), (E)-1-(3-methyl 4-((E)-3-(2-methylpropylidene) piperazin-1-yl) phenyl)-2-(2 methylpropylidene) piperazine (E) and triphenyl derivative ammonium 2-((2,3',3''-trimethyl-[1,1':4',1''-terphenyl]-4 yl)oxy)acetate (F) were tested for inhibition of K-562 cell proliferation and for induction of erythroid differentiation. Among them, two piperazine and one triphenyl derivatives, compounds A, E, and F inhibited the proliferation of the K562 cell lines exhibiting inhibition concentration 50 (IC50) (IC50) of values 30.10±1.6, 4.60±0.4 and 25.70±1.10 µg ml(-1), respectively. If compound A and F were added to suboptimal concentrations of the established anticancer drugs cytosine arabinoside or mithramycin, pronounced synergic effects were observed.

Antiproliferative activities on renal, prostate and melanoma cancer cell lines of Sarcopoterium spinosum aerial parts and its major constituent tormentic acid.

The search for improved cytotoxic agents continues to be an important line in the discovery of modern anticancer drugs. Sarcopoterium spinosum (L.) Spach is mentioned in ethnobotanical surveys as a medicinal plant used for the treatment of cancer. The aim of this study is to investigate and to compare the aerial parts of S. spinosum collected in Italy and Lebanon for their chemical composition and their antiproliferative activity against ACHN, C32, A375, MCF-7, LNCaP and HeLa human cancer cell lines using SRB assay. The main constituent tormentic acid was isolated by MPLC and characterized by spectroscopic techniques (NMR, MS). Non polar compounds were analyzed by GC and GC-MS. S. spinosum showed an interesting antiproliferative activity against ACHN and C32 cell lines with IC(50) values of 2.4 and 2.7 µg/ml for S. spinosum from Italy and Lebanon, respectively. Remarkable results were obtained also against A375 and LNCaP cell lines. The cytotoxicity against ACHN cell line could be partially attributed to tormentic acid that demonstrated a higher cytotoxicity than the positive control vinblastine. Close association between the radical scavenging activity (evaluated by DPPH and ABTS assay) and cytotoxicity was also demonstrated. This investigation demonstrated the potential cytotoxic activity of S. spinosum taking into account also that none of the tested extracts, fractions and isolated compound affected the proliferation of normal cell line 142BR. Tormentic acid, the major constituent isolated from S. spinosum, play an important role in the cytotoxicity exhibited by the extract.

Phytochemical analysis and cytotoxicity towards multidrug-resistant leukemia cells of essential oils derived from Lebanese medicinal plants.

Juniperus excelsa fruit essential oil as well as J. oxycedrus, Cedrus libani, and Pinus pinea wood essential oils have been obtained with yields between 2.2 ± 0.3 % to 3.4 ± 0.5 % and analyzed by gas chromatography. Sesquiterpenes mainly characterized C. libani and J. oxycedrus essential oils, while in P. pinea and J. excelsa, monoterpenes were the most abundant compounds. In J. oxycedrus, cis-calamenene (7.8 %), cuparene (3.8 %), and cis-thujopsenal (2.0 %) have been detected for the first time. The cytotoxic activity of these essential oils against drug-sensitive CCRF-CEM and multidrug-resistant P-glycoprotein-expressing CEM/ADR5000 leukemia cells has been investigated (IC50 values: 29.46 to 61.54 µg/mL). Remarkably, multidrug-resistant CEM/ADR5000 cells did not reveal cross-resistance, indicating that these essential oils might be useful to treat otherwise drug-resistant and refractory tumors.

Antioxidant and antiproliferative activity of Laurus nobilis L. (Lauraceae) leaves and seeds essential oils against K562 human chronic myelogenous leukaemia cells.

The antioxidant and antiproliferative activities of the essential oils from Laurus nobilis leaves and seeds in relation to their composition were analysed. The most abundant components of the leaf essential oil were 1,8-cineole, 1-p-menthen-8-ethyl acetate, linalool and sabinene, while the seed oil was characterised by ß-ocimene, 1,8-cineole, α-pinene and ß-pinene as main constituents. Both seed and leaf essential oils exhibited a scavenging effect on the DPPH radical, with IC50 values of 66.1 and 53.5 µg mL⁻¹, respectively. The leaf essential oil showed the strongest antioxidant activity in the ß-carotene/linoleic acid system, with an IC50 value of 35.6 µg mL⁻¹ after 30 min of incubation. Both leaf and seed oils inhibited proliferation of the K562 tumour cell line with IC50 values of 95 and 75 µg mL⁻¹, respectively. The L. nobilis leaf oil showed a percentage of erythroide differentiation of 15% at a concentration of 10 µg mL⁻¹. A value of 12% was found for the seed essential oil at a concentration of 50 µg mL⁻¹. When the oils were added to a suboptimal concentration of the commercial drug, cytosine arabinoside, a clear synergic effect was observed.