Search results for: specificity

Authors: Sofiqul Islam, V. Murugan, Prema Kumari, Hari

Abstract:

Gentamicin is a broad spectrum water-soluble aminoglycoside antibiotics produced by the fermentation process of microorganism known as Micromonospora purpurea. It is widely used for the treatment of infection caused by both gram positive and gram negative bacteria. Gentamicin consists of a mixture of aminoglycoside components like C1, C1a, C2a, and C2. The molecular structure of Gentamicin and its related substances showed that it has lack of presence of chromophore group in the molecule due to which the detection of such components were quite critical and challenging. In this study, a simple Reversed Phase-High Performance Liquid Chromatographic (RP-HPLC) method using ultraviolet (UV) detector was developed and validated for quantification of the related substances present in Gentamicin drug substances. The method was achieved by using Thermo Scientific Hypersil Gold analytical column (150 x 4.6 mm, 5 µm particle size) with isocratic elution composed of methanol: water: glacial acetic acid: sodium hexane sulfonate in the ratio 70:25:5:3 % v/v/v/w as a mobile phase at a flow rate of 0.5 mL/min, column temperature was maintained at 30 °C and detection wavelength of 330 nm. The four components of Gentamicin namely Gentamicin C1, C1a, C2a, and C2 were well separated along with the related substance present in Gentamicin. The Limit of Quantification (LOQ) values were found to be at 0.0075 mg/mL. The accuracy of the method was quite satisfactory in which the % recovery was resulted between 95-105% for the related substances. The correlation coefficient (≥ 0.995) shows the linearity response against concentration over the range of Limit of Quantification (LOQ). Precision studies showed the % Relative Standard Deviation (RSD) values less than 5% for its related substance. The method was validated in accordance with the International Conference of Harmonization (ICH) guideline with various parameters like system suitability, specificity, precision, linearity, accuracy, limit of quantification, and robustness. This proposed method was easy and suitable for use for the quantification of related substances in routine analysis of Gentamicin formulations.

Keywords: reversed phase-high performance liquid chromatographic (RP-HPLC), high performance liquid chromatography, gentamicin, isocratic, ultraviolet

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Authors: Giancarlo La Marca, Engy Shokry, Fabio Villanelli

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Epilepsy is one of the most common neurological disorders, with an estimated prevalence of 50 million people worldwide. Twenty five percent of the epilepsy population is represented in children under the age of 15 years. For antiepileptic drugs (AED), there is a poor correlation between plasma concentration and dose especially in children. This was attributed to greater pharmacokinetic variability than adults. Hence, therapeutic drug monitoring (TDM) is recommended in controlling toxicity while drug exposure is maintained. Carbamazepine (CBZ) is a first-line AED and the drug of first choice in trigeminal neuralgia. CBZ is metabolised in the liver into carbamazepine-10,11-epoxide (CBZE), its major metabolite which is equipotent. This develops the need for an assay able to monitor the levels of both CBZ and CBZE. The aim of the present study was to develop and validate a LC-MS/MS method for simultaneous quantification of CBZ and CBZE in dried blood spots (DBS). DBS technique overcomes many logistical problems, ethical issues and technical challenges faced by classical plasma sampling. LC-MS/MS has been regarded as superior technique over immunoassays and HPLC/UV methods owing to its better specificity and sensitivity, lack of interference or matrix effects. Our method combines advantages of DBS technique and LC-MS/MS in clinical practice. The extraction process was done using methanol-water-formic acid (80:20:0.1, v/v/v). The chromatographic elution was achieved by using a linear gradient with a mobile phase consisting of acetonitrile-water-0.1% formic acid at a flow rate of 0.50 mL/min. The method was linear over the range 1-40 mg/L and 0.25-20 mg/L for CBZ and CBZE respectively. The limit of quantification was 1.00 mg/L and 0.25 mg/L for CBZ and CBZE, respectively. Intra-day and inter-day assay precisions were found to be less than 6.5% and 11.8%. An evaluation of DBS technique was performed, including effect of extraction solvent, spot homogeneity and stability in DBS. Results from a comparison with the plasma assay are also presented. The novelty of the present work lies in being the first to quantify CBZ and its metabolite from only one 3.2 mm DBS disc finger-prick sample (3.3-3.4 µl blood) by LC-MS/MS in a 10 min. chromatographic run.

Keywords: carbamazepine, carbamazepine-10, 11-epoxide, dried blood spots, LC-MS/MS, therapeutic drug monitoring

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Authors: Ching-Yuan Chen, Lung-Kwang Pan

Abstract:

Objective: Back pain is a major health problem costing billions of health budgets annually in Taiwan. Thousands of back pain surgeries are performed annually with up to 40% of patients complaining of back pain at time of post-surgery causing failed back surgery syndrome (FBSS), although diagnosis in these patients may be complex. The aim of study is to assess the feasibility of using bone SPECT-CT imaging to localize the active lesions causing persistent, recurrent or new backache after spine surgery. Materials and Methods: Bone SPECT-CT imaging was performed after the intravenous injection of 20 mCi of 99mTc-MDP for all the patients with diagnosis of FBSS. Patients were evaluated using status of subjectively pain relief, functional improvement and degree of satisfaction by reviewing the medical records and questionnaires in a 2 more years’ follow-up. Results: We enrolled a total of 16 patients were surveyed in our hospital from Jan. 2015 to Dec. 2016. Four people on SPEC/CT imaging ensured significant lesions were undergone a revised surgery (surgical treatment group). The mean visual analogue scale (VAS) decreased 5.3 points and mean Oswestry disability index (ODI) improved 38 points in the surgical group. The remaining 12 on SPECT/CT imaging were diagnosed as no significant lesions then received drug treatment (medical treatment group). The mean VAS only decreased 2 .1 point and mean ODI improved 12.6 points in the medical treatment group. In the posttherapeutic evaluation, the pain of the surgical treatment group showed a satisfactory improvement. In the medical treatment group, 10 of the 12 were also satisfied with the symptom relief while the other 2 did not improve significantly. Conclusions: Findings on SPECT-CT imaging appears to be easily explained the patients' pain. We recommended that SPECT/CT imaging was a feasible and useful clinical tool to improve diagnostic confidence or specificity when evaluating patients with FBSS.

Keywords: failed back surgery syndrome, oswestry disability index, SPECT-CT imaging, 99mTc-MDP, visual analogue scale

Procedia PDF Downloads 173

Authors: Godwin Dennison, C. E. Boulind, O. Gould, B. de Lacy Costello, J. Allison, P. White, P. Ewings, A. Wicaksono, N. J. Curtis, A. Pullyblank, D. Jayne, J. A. Covington, N. Ratcliffe, N. K. Francis

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Background: Colorectal symptoms are common but only infrequently represent serious pathology, including colorectal cancer (CRC). A large number of invasive tests are presently performed for reassurance. We investigated the feasibility of urinary volatile organic compound (VOC) testing as a potential triage tool in patients fast-tracked for assessment for possible CRC. Methods: A prospective, multi-centre, observational feasibility study was performed across three sites. Patients referred on NHS fast-track pathways for potential CRC provided a urine sample which underwent Gas Chromatography Mass Spectrometry (GC-MS), Field Asymmetric Ion Mobility Spectrometry (FAIMS) and Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) analysis. Patients underwent colonoscopy and/or CT colonography and were grouped as either CRC, adenomatous polyp(s), or controls to explore the diagnostic accuracy of VOC output data supported by an artificial neural network (ANN) model. Results: 558 patients participated with 23 (4.1%) CRC diagnosed. 59% of colonoscopies and 86% of CT colonographies showed no abnormalities. Urinary VOC testing was feasible, acceptable to patients, and applicable within the clinical fast track pathway. GC-MS showed the highest clinical utility for CRC and polyp detection vs. controls (sensitivity=0.878, specificity=0.882, AUROC=0.884). Conclusion: Urinary VOC testing and analysis are feasible within NHS fast-track CRC pathways. Clinically meaningful differences between patients with cancer, polyps, or no pathology were identified therefore suggesting VOC analysis may have future utility as a triage tool. Acknowledgment: Funding: NIHR Research for Patient Benefit grant (ref: PB-PG-0416-20022).

Keywords: colorectal cancer, volatile organic compound, gas chromatography mass spectrometry, field asymmetric ion mobility spectrometry, selected ion flow tube mass spectrometry

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Authors: L. Ebralidze, A. Tsertsvadze, D. Berashvili, A. Bakuridze

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Current cancer therapy strategies are based on surgery, radiotherapy and chemotherapy. The problems associated with chemotherapy are one of the biggest challenges for clinical medicine. These include: low specificity, broad spectrum of side effects, toxicity and development of cellular resistance. Therefore, anti-cance drugs need to be develop urgently. Particularly, in order to increase efficiency of anti-cancer drugs and reduce their side effects, scientists work on formulation of nano-drugs. The objective of this study was to develop composition and technology of vincristine nanoparticles using high-molecular carbohydrates of plant origin. Plant polysacharides, particularly, soy bean seed polysaccharides, flaxseed polysaccharides, citrus pectin, gum arabic, sodium alginate were used as objects. Based on biopharmaceutical research, vincristine containing nanoparticle formulations were prepared. High-energy emulsification and solvent evaporation methods were used for preparation of nanosystems. Polysorbat 80, polysorbat 60, sodium dodecyl sulfate, glycerol, polyvinyl alcohol were used in formulation as emulsifying agent and stabilizer of the system. The ratio of API and polysacharides, also the type of the stabilizing and emulsifying agents are very effective on the particle size of the final product. The influence of preparation technology, type and concentration of stabilizing agents on the properties of nanoparticles were evaluated. For the next stage of research, nanosystems were characterized. Physiochemical characterization of nanoparticles: their size, shape, distribution was performed using Atomic force microscope and Scanning electron microscope. The present study explored the possibility of production of NPs using plant polysaccharides. Optimal ratio of active pharmaceutical ingredient and plant polysacharids, the best stabilizer and emulsifying agent was determined. The average range of nanoparticles size and shape was visualized by SEM.

Keywords: nanoparticles, target delivery, natural high molecule carbohydrates, surfactants

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Authors: Rana Tabassum, Ravi Kant, Banshi D. Gupta

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Malic acid is an extensively distributed organic acid in numerous horticultural products in minute amounts which significantly contributes towards taste determination by balancing sugar and acid fractions. An enhanced concentration of malic acid is utilized as an indicator of fruit maturity. In addition, malic acid is also a crucial constituent of several cosmetics and pharmaceutical products. An efficient detection and quantification protocol for malic acid is thus highly demanded. In this study, we report a novel detection scheme for malic acid by synergistically collaborating fiber optic surface plasmon resonance (FOSPR) and distinctive features of nanomaterials favorable for sensing applications. The design blueprint involves the deposition of an assembly of malate dehydrogenase enzyme entrapped in ZnO nanowires forming the sensing route over silver coated central unclad core region of an optical fiber. The formation and subsequent decomposition of the enzyme-analyte complex on exposure of the sensing layer to malic acid solutions of diverse concentration results in modification of the dielectric function of the sensing layer which is manifested in terms of shift in resonance wavelength. Optimization of experimental variables such as enzyme concentration entrapped in ZnO nanowires, dip time of probe for deposition of sensing layer and working pH range of the sensing probe have been accomplished through SPR measurements. The optimized sensing probe displays high sensitivity, broad working range and a minimum limit of detection value and has been successfully tested for malic acid determination in real samples of fruit juices. The current work presents a novel perspective towards malic acid determination as the unique and cooperative combination of FOSPR and nanomaterials provides myriad advantages such as enhanced sensitivity, specificity, compactness together with the possibility of online monitoring and remote sensing.

Keywords: surface plasmon resonance, optical fiber, sensor, malic acid

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Authors: Teklay Gebrecherkos

Abstract:

Background: Serological testing for SARS-CoV-2 plays an important role in epidemiological studies, in aiding the diagnosis of COVID-19 and assess vaccine responses. Little is known about the dynamics of SARS-CoV-2 serology in African settings. Here, we aimed to characterize the longitudinal antibody response profile to SARS-CoV-2 in Ethiopia. Methods: In this prospective study, a total of 102 PCR-confirmed COVID-19 patients were enrolled. We obtained 802 plasma samples collected serially. SARS-CoV-2 antibodies were determined using four lateral flow immune assays (LFIAs) and an electrochemiluminescent immunoassay. We determined longitudinal antibody response to SARS-CoV-2 as well as seroconversion dynamics. Results: Serological positivity rate ranged between 12%-91%, depending on timing after symptom onset. There was no difference in the positivity rate between severe and non-severe COVID-19 cases. The specificity ranged between 90%-97%. Agreement between different assays ranged between 84%-92%. The estimated positive predictive value (PPV) for IgM or IgG in a scenario with seroprevalence at 5% varies from 33% to 58%. Nonetheless, when the population seroprevalence increases to 25% and 50%, there is a corresponding increase in the estimated PPVs. The estimated negative-predictive value (NPV) in a low seroprevalence scenario (5%) is high (>99%). However, the estimated NPV in a high seroprevalence scenario (50%) for IgM or IgG is reduced significantly from 80% to 85%. Overall, 28/102 (27.5%) seroconverted by one or more assays tested within a median time of 11 (IQR: 9–15) days post symptom onset. The median seroconversion time among symptomatic cases tended to be shorter when compared to asymptomatic patients [9 (IQR: 6–11) vs. 15 (IQR: 13–21) days; p = 0.002]. Overall, seroconversion reached 100% 5.5 weeks after the onset of symptoms. Notably, of the remaining 74 COVID-19 patients included in the cohort, 64 (62.8%) were positive for antibodies at the time of enrollment, and 10 (9.8%) patients failed to mount a detectable antibody response by any of the assays tested during follow-up. Conclusions: Longitudinal assessment of antibody response in African COVID-19 patients revealed heterogeneous responses. This underscores the need for a comprehensive evaluation of serum assays before implementation. Factors associated with failure to seroconvert need further research.

Keywords: COVID-19, antibody, rapid diagnostic tests, ethiopia

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Authors: Michal Krecichwost, Zauzanna Miodonska, Pawel Badura

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The diagnosis of sigmatism is mostly based on the observation of articulatory organs. It is, however, not always possible to precisely observe the vocal apparatus, in particular in the oral cavity of the patient. Speech processing can allow to objectify the therapy and simplify the verification of its progress. In the described study the methodology for classification of incorrectly pronounced phoneme [s] is proposed. The recordings come from adults. They were registered with the speech recorder at the sampling rate of 44.1 kHz and the resolution of 16 bit. The database of pathological and normative speech has been collected for the study including reference assessments provided by the speech therapy experts. Ten adult subjects were asked to simulate a certain type of stigmatism under the speech therapy expert supervision. In the recordings, the analyzed phone [s] was surrounded by vowels, viz: ASA, ESE, ISI, SPA, USU, YSY. Thirteen MFCC (mel-frequency cepstral coefficients) and RMS (root mean square) values are calculated within each frame being a part of the analyzed phoneme. Additionally, 3 fricative formants along with corresponding amplitudes are determined for the entire segment. In order to aggregate the information within the segment, the average value of each MFCC coefficient is calculated. All features of other types are aggregated by means of their 75th percentile. The proposed method of features aggregation reduces the size of the feature vector used in the classification. Binary SVM (support vector machine) classifier is employed at the phoneme recognition stage. The first group consists of pathological phones, while the other of the normative ones. The proposed feature vector yields classification sensitivity and specificity measures above 90% level in case of individual logo phones. The employment of a fricative formants-based information improves the sole-MFCC classification results average of 5 percentage points. The study shows that the employment of specific parameters for the selected phones improves the efficiency of pathology detection referred to the traditional methods of speech signal parameterization.

Keywords: computer-aided pronunciation evaluation, sibilants, sigmatism diagnosis, speech processing

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Authors: Uraib Sharaha, Guy Beck, Joseph Kapelushnik, Adam H. Agbaria, Itshak Lapidot, Shaul Mordechai, Ahmad Salman, Mahmoud Huleihel

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Infectious diseases cause a significant burden on the public health and the economic stability of societies all over the world for several centuries. A reliable detection of the causative agent of infection is not possible based on clinical features, since some of these infections have similar symptoms, including fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Moreover, physicians usually encounter difficulties in distinguishing between viral and bacterial infections based on symptoms. Therefore, there is an ongoing need for sensitive, specific, and rapid methods for identification of the etiology of the infection. This intricate issue perplex doctors and researchers since it has serious repercussions. In this study, we evaluated the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. Fourier transform infrared (FTIR) spectroscopy is considered a successful diagnostic method in the biological and medical fields. Many studies confirmed the great potential of the combination of FTIR spectroscopy and machine learning as a powerful diagnostic tool in medicine since it is a very sensitive method, which can detect and monitor the molecular and biochemical changes in biological samples. We believed that this method would play a major role in improving the health situation, raising the level of health in the community, and reducing the economic burdens in the health sector resulting from the indiscriminate use of antibiotics. We collected peripheral blood samples from young 364 patients, of which 93 were controls, 126 had bacterial infections, and 145 had viral infections, with ages lower than18 years old, limited to those who were diagnosed with fever-producing illness. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

Keywords: infectious diseases, (FTIR) spectroscopy, viral infections, bacterial infections.

Procedia PDF Downloads 138

Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Nusrat Praween, Krishna Thej Pammi Guru, Palash Kumar Basu

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Designing non-invasive biosensors for cancer diagnosis is essential for developing an affordable and specific tool to measure cancer-related exosome biomarkers. Exosomes, released by healthy as well as cancer cells, contain valuable information about the biomarkers of various diseases, including cancer. Despite the availability of various isolation techniques, ultracentrifugation is the standard technique that is being employed. Post isolation, exosomes are traditionally exposed to detergents for extracting their proteins, which can often lead to protein degradation. Further to this, it is very essential to develop a sensing platform for the quantification of clinically relevant proteins in a wider range to ensure practicality. In this study, exosomes were immobilized on the Au Screen Printed Electrode (SPE) using EDC/NHS chemistry to facilitate binding. After immobilizing the exosomes on the screen-printed electrode (SPE), we investigated the impact of the electric field by applying various voltages to induce exosome lysis and release their contents. The lysed solution was used for sensing TSG101, a crucial biomarker associated with various cancers, using both faradaic and non-faradaic electrochemical impedance spectroscopy (EIS) methods. The results of non-faradaic and faradaic EIS were comparable and showed good consistency, indicating that non-faradaic sensing can be a reliable alternative. Hence, the non-faradaic sensing technique was used for label-free quantification of the TSG101 biomarker. The results were validated using ELISA. Our electrochemical immunosensor demonstrated a consistent response of TSG101 from 125 pg/mL to 8000 pg/mL, with a detection limit of 0.125 pg/mL at room temperature. Additionally, since non-faradic sensing is label-free, the ease of usage and cost of the final sensor developed can be reduced. The proposed immunosensor is capable of detecting the TSG101 protein at low levels in healthy serum with good sensitivity and specificity, making it a promising platform for biomarker detection.

Keywords: biosensor, exosomes isolation on SPE, electric field lysis of exosome, EIS sensing of TSG101

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Ayah Al Yaari, Ayman Al Yaari, Montaha Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Developmental co-ordination disorder (DCD) (also known as dyspraxia) causes a child to speak less well than expected in social conversations. We propose that the smart speaking technology could help improve sound production mechanism at both phonetic and phonological levels, which leads to better articulation of an utterance. The participants are twelve privately beginner pupils aged between 6-12 years old and diagnosed with DCD (apraxia) divided into two groups: Experimental group (n=6) and control group (called apraxic control group) (n=6). A total of fifty typically developing and achieving (TD) pupils participated as control group 2 in both groups and were preassigned into two groups (27 pupils with the treatment group and 23 with the apraxic control group). Weekly quizzes were given to all participants each week for four continuous months and results were analyzed by psychoneurolinguists and a statistician. Although being taught by the same speech-language therapist (SLT), treatment group along with TD groups were taught a full-time speaking course with sociolinguistic themes covering both phonetic and phonological properties. The course lasted for a whole semester whereby smart speaking aids have become dominant while apraxic control group and its TD group were not. Compared with apraxic control group and its TD subgroup, results show obvious changes in speaking behavioral mechanism of the DCD experimental group and its TD subgroup. Improvement could be taken from the scores where the zero marks disappeared in the fourth week (end of the first month of treatment). Good marks (5 +/10) were seen starting from the eighth week and culminating with full marks in the week number 15 of treatment where some participants scored full mark. This study concludes to support the primacy of the smart educational technology for speaking purposes and also shows that such aids can expand the range of academic performance differential categories. Further research is required to evaluate the current demonizing of smart educational aids and weighting more reasonably the relationship specificity that speaking aids can offer to other language skills, as well as their limitations.

Keywords: smart educational technology, speaking aids, pupils with SCD, apraxia

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Authors: Nandita Ghosh, Shinjini Mitra, Ena Ray Banerjee

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Atopic dermatitis (AD) is a chronic disease of the skin, involving itchy, reddish, and scaly lesions. It mainly affects children and has a high prevalence in developing countries. The AD may occur due to environmental or genetic factors. There is no permanent cure for the AD. Currently, all therapeutic strategies involve methods to simply alleviate the symptoms, and include lotions and corticosteroids, which have adverse effects. Use of phytochemicals and natural products has not yet been exploited fully. The particle used in this study is derived from Cyamopsis tetragonoloba, an edible polysaccharide with a galactomannan component. The mannose component mainly increases its specificity towards cellular uptake by mannose receptors, highly expressed by the macrophage. The aim of this study was to determine the therapeutic effect of guar gum nanoparticles (GN) in vitro and in vivo in the AD. To assess the wound healing capacity of the guar gum nanoparticle (GN), we first treated adherent NIH3T3 cells, with a scratch injury, with GN. GN successfully healed the wound caused by the scratch. In the in vivo experiment, Balb/c mice ear were topically treated with oxazolone (oxa) to induce AD and then were topically treated with GN. The ear thickness was increased significantly till day 28 on the treatment of Oxa. The GN application showed a significant decrease in the thickness as assessed on day 28. The total cell count of skin cells showed fold increase when treated with oxa, was again decreased on topical application of GN on the affected skin. The eosinophil count, as assessed by Giemsa staining was also increased when treated with oxa, GN application led to a significant decrease. The IgE level was assessed in the serum samples which showed that GN helped in restoring the alleviated IgE level. The T helper cells and the macrophage population showed increased percentage when treated with oxa, the GN application. This was examined by flow cytometry. The H&E staining of the ear tissue showed epidermal thickness in the oxa treated mice, GN application showed reduced cellular filtration followed by epidermal thickness. Thus our assays showed that GN was successful in alleviating the disease caused by Oxa when administered topically.

Keywords: allergen, inflammation, nanodrug, wound

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Authors: Vaibhav D. Bhatt, Anju P. Kunjadia, D. S. Nauriyal, Bhumika J. Joshi, Chaitanya G. Joshi

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Metagenomic analysis of milk samples collected from local cattle breed, kankrej (Bos indicus), Gir (Bos indicus) and Crossbred (Bos indicus X Bos taurus) cattle harbouring subclinical mastitis was carried out by next-generation sequencing (NGS) 454 GS-FLX technology. Around 56 different species including members of Enterobacteriales, Pseudomonadales, Bacillales and Lactobacillales with varying abundance were detected in infected milk. The interesting presence of bacteriophages against Staphylococcus aureus, Escherichia coli, Enterobacter and Yersinia species were observed, especially Enterobacteria and E. coli phages (0∙32%) in Kankrej, Enterobacteria and Staphylococcus phages (1∙05%) in Gir and Staphylococcus phages (2∙32%) in crossbred cattle. NGS findings suggest that phages may be involved in imparting natural resistance of the cattle against pathogens. Further infected milk samples were subjected for bacterial isolation. Fourteen different isolates were identified, and DNA was extracted. Genes (Tet-K, Msr-A, and Mec-A) providing antibiotic resistance to the bacteria were screened by Polymerase Chain Reaction and results were validated with traditional antibiotic assay. Total 3 bacteriophages were isolated from nearby environment of the cattle farm. The efficacy of phages was checked against multi-drug resistant bacteria, identified by PCR. In-vivo study was carried out for phage therapy in mammary glands of female rats “Wister albino”. Mammary glands were infused with MDR isolates for 3 consecutive days. Recovery was observed in infected rats after intramammary infusion of sterile phage suspension. From day 4th onwards, level of C-reactive protein was significant increases up to day 12th . However, significant reduction was observed between days 12th to 18th post treatment. Bacteriophages have significant potential as antibacterial agents and their ability to replicate exponentially within their hosts and their specificity, make them ideal candidates for more sustainable mastitis control.

Keywords: bacteriophages, c-reactive protein, mastitis, metagenomic analysis

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Authors: Dimiter M. Dimitrov, Abdullah Sadaawi

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The National Assessment for Schools (NAFS) in Saudi Arabia consists of standardized tests in Mathematics, Reading, and Science for school grade levels 3, 6, and 9. One main goal is to classify students into four categories of NAFS performance (minimal, basic, proficient, and advanced) by schools and the entire national sample. The NAFS scoring and equating is performed on a bounded scale (D-scale: ranging from 0 to 1) in the framework of the recently developed “D-scoring method of measurement.” The specificity of the NAFS measurement framework and data complexity presented both challenges and opportunities to (a) the estimation of score reliability for schools, (b) setting cut-scores for the classification of students into categories of performance, and (c) generating plausible values for distributions of student performance on the D-scale. The estimation of score reliability at the school level was performed in the framework of generalizability theory (GT), with students “nested” within schools and test items “nested” within test forms. The GT design was executed via a multilevel modeling syntax code in R. Cut-scores (on the D-scale) for the classification of students into performance categories was derived via a recently developed method of standard setting, referred to as “Response Vector for Mastery” (RVM) method. For each school, the classification of students into categories of NAFS performance was based on distributions of plausible values for the students’ scores on NAFS tests by grade level (3, 6, and 9) and subject (Mathematics, Reading, and Science). Plausible values (on the D-scale) for each individual student were generated via random selection from a statistical logit-normal distribution with parameters derived from the student’s D-score and its conditional standard error, SE(D). All procedures related to D-scoring, equating, generating plausible values, and classification of students into performance levels were executed via a computer program in R developed for the purpose of NAFS data analysis.

Keywords: large-scale assessment, reliability, generalizability theory, plausible values

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Authors: Mohammed Zahid Akter

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In the studies of language change, mental factors including analogy, reanalysis, and frequency have received considerable attention as possible catalysts for language change. In comparison, relatively little is known regarding which functional domains or construction types are more amenable to these mental factors than others. In this regard, this paper will show with data from South Central (Kuki-Chin) Tibeto-Burman languages how language change interacts with certain functional domains or construction types. These construction types include transitivity, person marking, and polarity distinctions. Thus, it will be shown that transitive clauses are more prone to change than intransitive and ditransitive clauses, clauses with 1st person argument marking are more prone to change than clauses with 2nd and 3rd person argument marking, non-copular clauses are more prone to change than copular clauses, affirmative clauses are more prone to change than negative clauses, and standard negatives are more prone to change than negative imperatives. The following schematic structure can summarize these findings: transitive>intransitive, ditransitive; 1st person>2nd person, 3rd person; non-copular>copular; and affirmative>negative; and standard negative>negative imperatives. In the interest of space, here only one of these findings is illustrated: affirmative>negative. In Hyow (South Central, Bangladesh), the innovative and preverbal 1st person subject k(V)- occurs in an affirmative construction, and the archaic and postverbal 1st person subject -ŋ occurs in a negative construction. Similarly, in Purum (South Central, Northeast India), the innovative and preverbal 1st person subject k(V)- occurs in an affirmative construction, and the archaic and postverbal 1st person subject *-ŋ occurs in a negative construction. Like 1st person subject, we also see that in Anal (South Central, Northeast India), the innovative and preverbal 2nd person subject V- occurs in an affirmative construction, and the archaic and postverbal 2nd person subject -t(V) in a negative construction. To conclude, data from South Central Tibeto-Burman languages suggest that language change interacts with functional domains as some construction types are more susceptible to change than others.

Keywords: functional domains, Kuki-Chin, language change, south-central, Tibeto-Burman

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Authors: Reena K., Mamatha H. G., Somshekarayya, P. Kumar

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Objectives: The annual proficiency testing of intermediate reference laboratories is conducted by the National Reference Laboratory (NRL) to assess the efficiency of the laboratories to correctly identify Mycobacterium tuberculosis and to determine its drug susceptibility pattern. The proficiency testing results from 2013 to 2017 were analyzed to determine laboratories that were consistent in reporting quality results and those that had difficulty in doing so. Methods: A panel of twenty cultures were sent out to each of these laboratories. The laboratories were expected to grow the cultures in their own laboratories, set up drug susceptibly testing by all the methods they were certified for and report the results within the stipulated time period. The turnaround time for reporting results, specificity, sensitivity positive and negative predictive values and efficiency of the laboratory in identifying the cultures were analyzed. Results: Most of the laboratories had reported their results within the stipulated time period. However, there was enormous delay in reporting results from few of the laboratories. This was mainly due to improper functioning of the biosafety level III laboratory. Only 40% of the laboratories had 100% efficiency in solid culture using Lowenstein Jensen medium. This was expected as a solid culture, and drug susceptibility testing is not used for diagnosing drug resistance. Rapid molecular methods such as Line probe assay and Genexpert are used to determine drug resistance. Automated liquid culture system such as the Mycobacterial growth indicator tube is used to determine prognosis of the patient while on treatment. It was observed that 90% of the laboratories had achieved 100% in the liquid culture method. Almost all laboratories had achieved 100% efficiency in the line probe assay method which is the method of choice for determining drug-resistant tuberculosis. Conclusion: Since the liquid culture and line probe assay technologies are routinely used for the detection of drug-resistant tuberculosis the laboratories exhibited higher level of efficiency as compared to solid culture and drug susceptibility testing which are rarely used. The infrastructure of the laboratory should be maintained properly so that samples can be processed safely and results could be declared on time.

Keywords: annual proficiency testing, drug susceptibility testing, intermediate reference laboratory, national reference laboratory

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Authors: Guna Raj Dhungana, Roshan Nepal, Apshara Parajuli, , Archana Maharjan, Shyam K. Mishra, Pramod Aryal, Rajani Malla

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Introduction: Klebsiella pneumoniae is a well-known opportunistic human pathogen, primarily causing healthcare-associated infections. The global emergence of carbapenemase-producing K. pneumoniaeis a major public health burden, which is often extensively multidrug resistant.Thus, because of the difficulty to treat these ‘superbug’ and menace and some term as ‘apocalypse’ of post antibiotics era, an alternative approach to controlling this pathogen is prudent and one of the approaches is phage mediated control and/or treatment. Objective: In this study, we aimed to isolate novel bacteriophage against carbapenemase-producing K. pneumoniaeand characterize for potential use inphage therapy. Material and Methods: Twenty lytic phages were isolated from river water using double layer agar assay and purified. Biological features, physiochemical characters, burst size, host specificity and activity spectrum of phages were determined. One most potent phage: Phage TU_Kle10O was selected and characterized by electron microscopy. Whole genome sequences of the phage were analyzed for presence/absence of virulent factors, and other lysin genes. Results: Novel phage TU_Kle10O showed multiple host range within own genus and did not induce any BIM up to 5th generation of host’s life cycle. Electron microscopy confirmed that the phage was tailed and belonged to Caudovirales family. Next generation sequencing revealed its genome to be 166.2 Kb. bioinformatical analysis further confirmed that the phage genome ‘did not’ contain any ‘bacterial genes’ within phage genome, which ruled out the concern for transfer of virulent genes. Specific 'lysin’ enzyme was identified phages which could be used as 'antibiotics'. Conclusion: Extensively multidrug resistant bacteria like carbapenemase-producing K. pneumoniaecould be treated efficiently by phages.Absence of ‘virulent’ genes of bacterial origin and presence of lysin proteins within phage genome makes phages an excellent candidate for therapeutics.

Keywords: bacteriophage, Klebsiella pneumoniae, MDR, phage therapy, carbapenemase,

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Authors: Aileen Editha

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The legal recognition of property rights over human genes is a divisive topic to which there is no resolution. As a frequently discussed topic, scholars and practitioners often highlight the inadequacies of a proprietary regime. However, little has been said in regard to the nature of human genetic materials (HGMs). This paper proposes approaching the issue of property over HGMs from an alternative perspective that looks at the personal and social value and valuation of HGMs. This paper will highlight how the unique and unresolved status of HGMs is incompatible with the main tenets of property and, consequently, contributes to legal ambiguity and uncertainty in the regulation of property rights over human genes. HGMs are perceived as part of nature and a free-for-all while also being within an individual’s private sphere. Additionally, it is also considered to occupy a unique “not-private-nor-public” status. This limbo-like position clashes with property’s fundamental characteristic that relies heavily on a clear public/private dichotomy. Moreover, as property is intrinsically linked to the legal recognition of one’s personhood, this irresolution benefits some while disadvantages others. In particular, it demands the publicization of once-private genes for the “common good” but subsequently encourages privatization (through labor) of these now-public genes. This results in the gain of some (already privileged) individuals while enabling the disenfranchisement of members of minority groups, such as Indigenous communities. This paper will discuss real and intellectual property rights over human genes, such as the right to income or patent rights, in Canada and the US. This paper advocates for a sui generis approach to governing rights and interests over human genes that would not rely on having a strict public/private dichotomy. Not only would this improve legal certainty and clarity, but it would also alleviate—or, at the very least, minimize—the role that the current law plays in further entrenching existing systemic inequalities. Despite the specificity of this topic, this paper argues that there are broader lessons to be learned. This issue is an insightful case study on the interconnection of various principles in law, society, and property, and what must be done when discordance between one or more of those principles has detrimental societal outcomes. Ultimately, it must be remembered that property is an adaptable and malleable instrument that can be developed to ensure it contributes to equity and flourishing.

Keywords: property rights, human genetic materials, critical legal scholarship, systemic inequalities

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Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Nimet Yildirim Tirgil, Ahmed Busnaina, April Z. Gu

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Environmental waters are monitored worldwide to protect people from infectious diseases primarily caused by enteric pathogens. All long, Escherichia coli (E. coli) is a good indicator for potential enteric pathogens in waters. Thus, a rapid and simple detection method for E. coli is very important to predict the pathogen contamination. In this study, to the best of our knowledge, as the first time we developed a rapid, direct and reusable SWCNTs (single walled carbon nanotubes) based biosensor system for sensitive and selective E. coli detection in water samples. We use a novel and newly developed flexible biosensor device which was fabricated by high-rate nanoscale offset printing process using directed assembly and transfer of SWCNTs. By simple directed assembly and non-covalent functionalization, aptamer (biorecognition element that specifically distinguish the E. coli O157:H7 strain from other pathogens) based SWCNTs biosensor system was designed and was further evaluated for environmental applications with simple and cost-effective steps. The two gold electrode terminals and SWCNTs-bridge between them allow continuous resistance response monitoring for the E. coli detection. The detection procedure is based on competitive mode detection. A known concentration of aptamer and E. coli cells were mixed and after a certain time filtered. The rest of free aptamers injected to the system. With hybridization of the free aptamers and their SWCNTs surface immobilized probe DNA (complementary-DNA for E. coli aptamer), we can monitor the resistance difference which is proportional to the amount of the E. coli. Thus, we can detect the E. coli without injecting it directly onto the sensing surface, and we could protect the electrode surface from the aggregation of target bacteria or other pollutants that may come from real wastewater samples. After optimization experiments, the linear detection range was determined from 2 cfu/ml to 10⁵ cfu/ml with higher than 0.98 R² value. The system was regenerated successfully with 5 % SDS solution over 100 times without any significant deterioration of the sensor performance. The developed system had high specificity towards E. coli (less than 20 % signal with other pathogens), and it could be applied to real water samples with 86 to 101 % recovery and 3 to 18 % cv values (n=3).

Keywords: aptamer, E. coli, environmental detection, nanobiosensor, SWCTs

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Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

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Authors: Pavel Damborsky, Martina Zamorova, Jaroslav Katrlik

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Prostate cancer is annually the most common newly diagnosed cancer among men. An extensive number of evidence suggests that traditional serum Prostate-specific antigen (PSA) assay still suffers from a lack of sufficient specificity and sensitivity resulting in vast over-diagnosis and overtreatment. Thus, the early-stage detection of prostate cancer (PCa) plays undisputedly a critical role for successful treatment and improved quality of life. Over the last decade, particular altered glycans have been described that are associated with a range of chronic diseases, including cancer and inflammation. These glycans differences enable a distinction to be made between physiological and pathological state and suggest a valuable biosensing tool for diagnosis and follow-up purposes. Aberrant glycosylation is one of the major characteristics of disease progression. Consequently, the aim of this study was to develop a more reliable tool for early-stage PCa diagnosis employing lectins as glyco-recognition elements. Biosensor and biochip technology putting to use lectin-based glyco-profiling is one of the most promising strategies aimed at providing fast and efficient analysis of glycoproteins. The proof-of-concept experiments based on sandwich assay employing anti-PSA antibody and an aptamer as a capture molecules followed by lectin glycoprofiling were performed. We present a lectin-based biosensing assay for glycoprofiling of serum biomarker PSA using different biosensor and biochip platforms such as label-free surface plasmon resonance (SPR) and microarray with fluorescent label. The results suggest significant differences in interaction of particular lectins with PSA. The antibody-based assay is frequently associated with the sensitivity, reproducibility, and cross-reactivity issues. Aptamers provide remarkable advantages over antibodies due to the nucleic acid origin, stability and no glycosylation. All these data are further step for construction of highly selective, sensitive and reliable sensors for early-stage diagnosis. The experimental set-up also holds promise for the development of comparable assays with other glycosylated disease biomarkers.

Keywords: biomarker, glycosylation, lectin, prostate cancer

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Authors: Ujjawal Kumar Bhagat, Kamaluddin, Rama Krishna Peddinti

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The Huisgen’s 1,3-dipolar [3+2] cycloaddition of organic azides and alkynes often give the mixtures of both the regioisomers 1,4- and 1,5- disubstituted 1,2,3-triazoles. Later, in presence of metal salts (click chemistry) such as copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) was used for the synthesis of 1,4-disubstituted 1,2,3-triazoles as a sole products regioselectively. Also, the ‘click reactions’ of Ruthenium-catalyzed azides-alkynes cycloaddition (RuAAC) is used for the synthesis of 1,5-disubstituted 1,2,3-triazoles as a single isomer. The synthesis of 1,4- and 1.5-disubstituted 1,2,3-triazoles has become the gold standard of ‘click chemistry’ due to its reliability, specificity, and biocompatibility. The 1,4- and 1,5-disubstituted 1,2,3-triazoles have emerged as one of the most powerful entities in the varieties of biological properties like antibacterial, antitubercular, antitumor, antifungal and antiprotozoal activities. Some of the 1,4,5-trisubstituted 1,2,3-triazoles exhibit Hsp90 inhibiting properties. The 1,4-disubstituted 1,2,3-triazoles also play a big role in the area of material sciences. The triazole-derived oligomeric, polymeric structures are the potential materials for the preparation of organic optoelectronics, silicon elastomers and unimolecular block copolymers. By the virtue of hydrogen bonding and dipole interactions, the 1,2,3-triazole moiety readily associates with the biological targets. Since, the 4-aryl-1H-1,2,3-triazoles are stable entities, they are chemically robust and very less reactive. In this regard, the addition of 4-aryl-1H-1,2,3-triazoles as nucleophiles to α,β-unsaturated carbonyls and nucleophilic substitution with the epoxides constitutes a powerful and challenging synthetic approach for the generation of disubstituted 1,2,3-triazoles. Herein, we have developed aza-Michael addition of 4-aryl-1H-1,2,3-triazoles to 2-cycloalken-1-ones in the presence of an organic base (DABCO) in acetonotrile solvent leading to the formation of disubstituted 1,2,3-triazoles. The reaction provides 1,4-disubstituted triazoles, 3-(4-aryl-1H-1,2,3-triazol-1-yl)cycloalkanones in major amount along with 1,5-disubstituted 1,2,3-triazoles, minor regioisomers with excellent combined chemical yields (upto99%). The nucleophilic behavior of 4-aryl-1H-1,2,3-triazoles was also tested in the ring opening of meso-epoxides in the presence of organic bases (DABCO/Et3N) in acetonotrile solvent furnishing the two regioisomers1,4- and 1,5-disubstituted 1,2,3-triazoles. Thus, the novelty of this methodology is synthesis of diversified disubstituted 1,2,3-triazoles under metal free condition.The results will be presented in detail.

Keywords: aza-Michael addition, cycloalkenones, epoxides, triazoles

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Authors: Recep Keşli, Hayriye Tokay, Cengiz Demir, İsmail Ceyhan

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Objective: In many countries, tuberculosis (TB) is still one of the most important diseases. Tuberculosis is among top 10 causes of death worldwide. The early diagnosis of active tuberculosis still depends on the presence of acid resistant bacilli (ARB) in stained smears. In this study, we aimed to investigate the diagnostic performances of Erlich Ziehl Neelsen (EZN), Kinyoun and two different fluorescent stains. Methods: The specimens were obtained from the patients who applied to Chest Diseases Departments of Ankara Atatürk Chest Diseases and Thoracic Surgery Training and Research Hospital, and Afyon Kocatepe University, ANS Research and Practice Hospital. The study was carried out in the Medical Microbiology Laboratory, School of Medicine, Afyon Kocatepe University. All the non-sterile specimens were homogenized and decontaminated according to the EUCAST instructions. Samples were inoculated onto the Löwenstein-Jensen agars (bio-Merieux Marcy l'Etoile, France) and then incubated at 37˚C, for 40 days. Four smears were prepared from each specimen. Slides were stained with commercial EZN (BD, Sparks, USA), Kinyoun (SALUBRIS Istanbul, Turkey), Auramine (SALUBRIS Istanbul, Turkey) and Rhodamine (SALUBRIS Istanbul, Turkey) kit. While EZN and Kinyoun stainings were examined by light microscope, Auramine and Rhodamine slides were examined by fluorescence microscopy. Results: A total of 158 respiratory system samples (sputum, broncho alveolar lavage fluid…etc) were enrolled into the study. A hundred and two of the samples that processed were found as culture positive. The sensitivity, specificity, positive predictive, and negative predictive values were detected as 100%, 67.5%, 73.5%, and 100% for EZN, 100%, 70.9%, 77.4%, and 100% for Kinyoun, 100%,77.8%, 84.3%, 100% for Auramine, and 100%, 80% , 86.3%, and 100% for Rhodamine respectively. Conclusions: According to our study auramine and rhodamine staining methods showed the best diagnostic performance among the four investigated staining methods. In conclusion, the fluorochrome staining method may be accepted as the most reliable, rapid and useful method for diagnosis of the mycobacterial infections truly.

Keywords: acid resistant bacilli (ARB), auramine, Ehrlich-Ziehl-Neelsen (EZN), Kinyoun, Rhodamine

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Authors: Jean Paul M. Milambo

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Purpose: Aromatase inhibitors (AIs) are indicated in the treatment of hormone-receptive breast cancer in postmenopausal women in various settings. Studies have shown cardiovascular events in some developed countries. To date the data is sparce for evidence-based recommendations in African clinical settings due to lack of cancer registries, capacity building and surveillance systems. Therefore, this study was conducted to assess the feasibility of HyBeacon® probe genotyping adjunctive to standard care for timely prediction and diagnosis of Aromatase inhibitors (AIs) associated adverse events in breast cancer survivors in Africa. Methods: Cross sectional study was conducted to assess the knowledge of POCT among six African countries using online survey and telephonically contacted. Incremental cost effectiveness ratio (ICER) was calculated, using diagnostic accuracy study. This was based on mathematical modeling. Results: One hundred twenty-six participants were considered for analysis (mean age = 61 years; SD = 7.11 years; 95%CI: 60-62 years). Comparison of genotyping from HyBeacon® probe technology to Sanger sequencing showed that sensitivity was reported at 99% (95% CI: 94.55% to 99.97%), specificity at 89.44% (95% CI: 87.25 to 91.38%), PPV at 51% (95%: 43.77 to 58.26%), and NPV at 99.88% (95% CI: 99.31 to 100.00%). Based on the mathematical model, the assumptions revealed that ICER was R7 044.55. Conclusion: POCT using HyBeacon® probe genotyping for AI-associated adverse events maybe cost effective in many African clinical settings. Integration of preventive measures for early detection and prevention guided by different subtype of breast cancer diagnosis with specific clinical, biomedical and genetic screenings may improve cancer survivorship. Feasibility of POCT was demonstrated but the implementation could be achieved by improving the integration of POCT within primary health cares, referral cancer hospitals with capacity building activities at different level of health systems. This finding is pertinent for a future envisioned implementation and global scale-up of POCT-based initiative as part of risk communication strategies with clear management pathways.

Keywords: breast cancer, diagnosis, point of care, South Africa, aromatase inhibitors

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Authors: L. Szymanski, Z. Kolacinski, Z. Kamiński, G. Raniszewski, J. Fraczyk, L. Pietrzak

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In the article the development and demonstration of method and the model device for hyperthermic selective destruction of cancer cells are presented. This method was based on the synthesis and functionalization of carbon nanotubes serving as ferromagnetic material nano containers. Methodology of the production carbon - ferromagnetic nanocontainers includes: the synthesis of carbon nanotubes, chemical and physical characterization, increasing the content of ferromagnetic material and biochemical functionalization involving the attachment of the key addresses. Biochemical functionalization of ferromagnetic nanocontainers is necessary in order to increase the binding selectively with receptors presented on the surface of tumour cells. Multi-step modification procedure was finally used to attach folic acid on the surface of ferromagnetic nanocontainers. Folic acid is ligand of folate receptors which is overexpresion in tumor cells. The presence of ligand should ensure the specificity of the interaction between ferromagnetic nanocontainers and tumor cells. The chemical functionalization contains several step: oxidation reaction, transformation of carboxyl groups into more reactive ester or amide groups, incorporation of spacer molecule (linker), attaching folic acid. Activation of carboxylic groups was prepared with triazine coupling reagent (preparation of superactive ester attached on the nanocontainers). The spacer molecules were designed and synthesized. In order to ensure biocompatibillity of linkers they were built from amino acids or peptides. Spacer molecules were synthesized using the SPPS method. Synthesis was performed on 2-Chlorotrityl resin. The linker important feature is its length. Due to that fact synthesis of peptide linkers containing from 2 to 4 -Ala- residues was carried out. Independent synthesis of the conjugate of foilic acid with 6-aminocaproic acid was made. Final step of synthesis was connecting conjugat with spacer molecules and attaching it on the ferromagnetic nanocontainer surface. This article contains also information about special CVD and microvave plasma system to produce nanotubes and ferromagnetic nanocontainers. The first tests in the device for hyperthermal RF generator will be presented. The frequency of RF generator was in the ranges from 10 to 14Mhz and from 265 to 621kHz.

Keywords: synthesis of carbon nanotubes, hyperthermia, ligands, carbon nanotubes

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