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Dive into the research topics where Lenka Halámková is active.

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Featured researches published by Lenka Halámková.


Energy and Environmental Science | 2013

From “cyborg” lobsters to a pacemaker powered by implantable biofuel cells

Kevin MacVittie; Jan Halámek; Lenka Halámková; Mark Southcott; William D. Jemison; Robert Lobel; Evgeny Katz

Enzyme-based biofuel cells implanted into living lobsters or designed as fluidic systems mimicking human blood circulation were used for powering electronic devices. Two lobsters with implanted biofuel cells connected in series were able to generate open circuit voltage (Voc) up to 1.2 V and an electrical watch, selected as a model electronic device, was activated by the power extracted from the “living battery”. The fluidic system composed of five cells filled with human serum solution connected in series generated Voc of ca. 3 V and was able to power a pacemaker. Sustainable operation of the pacemaker was achieved with the system closely mimicking human physiological conditions characteristic of normal and pathophysiological glucose concentrations with the fluidic rate typical for a blood circulation upon resting or performing physical exercises. While the “cyborg” lobsters demonstrate a model system with future possible military, homeland security and environmental monitoring applications, the system activating a pacemaker presents practicality for biomedical applications. The first demonstration of the pacemaker activated by the physiologically produced electrical energy shows promise for future electronic implantable medical devices powered by electricity harvested from the human body.


Energy and Environmental Science | 2012

Living battery - biofuel cells operating in vivo in clams.

Alon Szczupak; Jan Halámek; Lenka Halámková; Vera Bocharova; Lital Alfonta; Evgeny Katz

Biofuel cells implanted in living clams and producing sustainable electrical power in vivo were integrated in batteries. The “electrified” clams, being biotechnological living “devices”, were able to generate electrical power using physiologically produced glucose as the fuel. The activity of the living batteries was dependent on the environmental conditions which are affecting physiological processes in clams. The living batteries generated open circuitry voltage (Voc), short circuitry current (Isc) and maximum power (Pmax) of ca. 800 mV, 25 μA, 5.2 μW and ca. 360 mV, 300 μA, 37 μW for the serial and parallel connections of 3 “electrified” clams, respectively. A clam-battery was connected to a capacitor which was charged up to 240 mV providing accumulation of electrical energy up to 28.8 mJ. Discharging the capacitor on an electrical motor resulted in the motor rotation. The “electrified” clams integrated in batteries demonstrated the possibility of activating electrical/electronic devices using energy produced in vivo.


Analyst | 2012

Analysis of biomarkers characteristic of porcine liver injury—from biomolecular logic gates to an animal model

Lenka Halámková; Jan Halámek; Vera Bocharova; Steven Wolf; Kristine E. Mulier; Greg J. Beilman; Joseph Wang; Evgeny Katz

A biocatalytic cascade for the analysis of the simultaneous increase in the concentration of two biomarkers characteristic of liver injury (alanine transaminase, ALT, and lactate dehydrogenase, LDH) was tested on real samples acquired from an animal model (domestic pigs, Sus scrofa domesticus) suffering from traumatic liver injury. A two-step reaction biocatalyzed in the presence of both enzyme-biomarkers resulted in the oxidation of NADH followed by optical absorbance measurements. A simple qualitative, YES/NO, test allowed for distinction between animals with and without the presence of liver injury with the probability of 92%. These data represent the first demonstration of applying binary logic systems for the analysis of real biomedical samples.


Journal of Biophotonics | 2015

Raman spectroscopy of blood serum for Alzheimer's disease diagnostics: specificity relative to other types of dementia.

Elena Ryzhikova; Oleksandr Kazakov; Lenka Halámková; Dzintra Celmins; Paula Malone; Eric Molho; Earl A. Zimmerman; Igor K. Lednev

The key moment for efficiently and accurately diagnosing dementia occurs during the early stages. This is particularly true for Alzheimers disease (AD). In this proof-of-concept study, we applied near infrared (NIR) Raman microspectroscopy of blood serum together with advanced multivariate statistics for the selective identification of AD. We analyzed data from 20 AD patients, 18 patients with other neurodegenerative dementias (OD) and 10 healthy control (HC) subjects. NIR Raman microspectroscopy differentiated patients with more than 95% sensitivity and specificity. We demonstrated the high discriminative power of artificial neural network (ANN) classification models, thus revealing the high potential of this developed methodology for the differential diagnosis of AD. Raman spectroscopic, blood-based tests may aid clinical assessments for the effective and accurate differential diagnosis of AD, decrease the labor, time and cost of diagnosis, and be useful for screening patient populations for AD development and progression. Multivariate data analysis of blood serum Raman spectra allows for the differentiation between patients with Alzheimers disease, other types of dementia and healthy individuals.


Analyst | 2013

Biocatalytic analysis of biomarkers for forensic identification of ethnicity between Caucasian and African American groups

Friederike Kramer; Lenka Halámková; Arshak Poghossian; Michael J. Schöning; Evgeny Katz; Jan Halámek

A new biocatalytic assay analyzing the simultaneous presence of creatine kinase (CK) and lactate dehydrogenase (LDH) was developed aiming at the recognition of biofluids of different ethnic origins for forensic applications. Knowing the difference in the concentrations of CK and LDH in the blood of healthy adults of two ethnical groups, Caucasian (CA) and African American (AA), and taking into account the distribution pattern, we mimicked the samples of different ethnic origins with various CK-LDH concentrations. The analysis was performed using a multi-enzyme/multi-step biocatalytic cascade where the differences in both included enzymes resulted in an amplified difference in the final analytical response. The statistically established analytical results confirmed excellent probability to distinguish samples of different ethnic origins (CA vs. AA). The standard enzymatic assay routinely used in hospitals for the analysis of CK, performed for comparison, was not able to distinguish the difference in samples mimicking blood of different ethnic origins. The robustness of the proposed assay was successfully tested on dried/aged serum samples (up to 24 h) - in order to mimic real forensic situations. The results obtained on the model solutions were confirmed by the analysis of real serum samples collected from human subjects of different ethnic origins.


Analytical Chemistry | 2015

Forensic Identification of Gender from Fingerprints.

Crystal Huynh; Erica Brunelle; Lenka Halámková; Juliana Agudelo; Jan Halámek

In the past century, forensic investigators have universally accepted fingerprinting as a reliable identification method, which relies mainly on pictorial comparisons. Despite developments to software systems in order to increase the probability and speed of identification, there has been limited success in the efforts that have been made to move away from the disciplines absolute dependence on the existence of a prerecorded matching fingerprint. Here, we have revealed that an information-rich latent fingerprint has not been used to its full potential. In our approach, the content present in the sweat left behind-namely the amino acids-can be used to determine physical such as gender of the originator. As a result, we were able to focus on the biochemical content in the fingerprint using a biocatalytic assay, coupled with a specially designed extraction protocol, for determining gender rather than focusing solely on the physical image.


Analytical Chemistry | 2016

New Horizons for Ninhydrin: Colorimetric Determination of Gender from Fingerprints

Erica Brunelle; Crystal Huynh; Anh Minh Le; Lenka Halámková; Juliana Agudelo; Jan Halámek

In the past century, forensic investigators have universally accepted fingerprinting as a reliable identification method via pictorial comparison. One of the most traditional detection methods uses ninhydrin, a chemical that reacts with amino acids in the fingerprint content to produce the blue-purple color known as Ruhemanns purple. It has recently been demonstrated that the amino acid content in fingerprints can be used to differentiate between male and female fingerprints. Here, we present a modified approach to the traditional ninhydrin method. This new approach for using ninhydrin is combined with an optimized extraction protocol and the concept of determining gender from fingerprints. In doing so, we are able to focus on the biochemical material rather than exclusively the physical image.


Analytical Chemistry | 2016

Race Differentiation by Raman Spectroscopy of a Bloodstain for Forensic Purposes

Ewelina Mistek; Lenka Halámková; Kyle C. Doty; Claire K. Muro; Igor K. Lednev

Bearing in mind forensic purposes, a nondestructive and rapid method was developed for race differentiation of peripheral blood donors. Blood is an extremely valuable form of evidence in forensic investigations so proper analysis is critical. Because potentially miniscule amounts of blood traces can be found at a crime scene, having a method that is nondestructive, and provides a substantial amount of information about the sample, is ideal. In this study Raman spectroscopy was applied with advanced statistical analysis to discriminate between Caucasian (CA) and African American (AA) donors based on dried peripheral blood traces. Spectra were collected from 20 donors varying in gender and age. Support vector machines-discriminant analysis (SVM-DA) was used for differentiation of the two races. An outer loop subject-wise cross-validation (CV) method evaluated the performance of the SVM classifier for each individual donor from the training data set. The performance of SVM-DA, evaluated by the area under the curve (AUC) metric, showed 83% probability of correct classification for both races, and a specificity and sensitivity of 80%. This preliminary study shows promise for distinguishing between different races of human blood. The method has great potential for real crime scene investigation, providing rapid and reliable results, with no sample preparation, destruction, or consumption.


Talanta | 2012

Enzymatic analysis of α-ketoglutaramate—A biomarker for hyperammonemia

Lenka Halámková; Shay Mailloux; Jan Halámek; Arthur J. L. Cooper; Evgeny Katz

Two enzymatic assays were developed for the analysis of α-ketoglutaramate (KGM)-an important biomarker of hepatic encephalopathy and other hyperammonemic diseases. In both procedures, KGM is first converted to α-ketoglutarate (KTG) via a reaction catalyzed by ω-amidase (AMD). In the first procedure, KTG generated in the AMD reaction initiates a biocatalytic cascade in which the concerted action of alanine transaminase and lactate dehydrogenase results in the oxidation of NADH. In the second procedure, KTG generated from KGM is reductively aminated, with the concomitant oxidation of NADH, in a reaction catalyzed by L-glutamic dehydrogenase. In both assays, the decrease in optical absorbance (λ=340 nm) corresponding to NADH oxidation is used to quantify concentrations of KGM. The two analytical procedures were applied to 50% (v/v) human serum diluted with aqueous solutions containing the assay components and spiked with concentrations of KGM estimated to be present in normal human plasma and in plasma from hyperammonemic patients. Since KTG is the product of AMD-catalyzed hydrolysis of KGM, in a separate study, this compound was used as a surrogate for KGM. Statistical analyses of samples mimicking the concentration of KGM assumed to be present in normal and pathological concentration ranges were performed. Both enzymatic assays for KGM were confirmed to discriminate between the predicted normal and pathophysiological concentrations of the analyte. The present study is the first step toward the development of a clinically useful probe for KGM analysis in biological fluids.


Analytical Chemistry | 2016

Ages at a Crime Scene: Simultaneous Estimation of the Time since Deposition and Age of Its Originator

Juliana Agudelo; Lenka Halámková; Erica Brunelle; Roselyn Rodrigues; Crystal Huynh; Jan Halámek

Blood is a major contributor of evidence in investigations involving violent crimes because of the unique composition of proteins and low molecular weight compounds present in the circulatory system, which often serve as biomarkers in clinical diagnostics. It was recently shown that biomarkers present in blood can also identify characteristics of the originator, such as ethnicity and biological sex. A biocatalytic assay for on-site forensic investigations was developed to simultaneously identify the age range of the blood sample originator and the time since deposition (TSD) of the blood spot. For these two characteristics to be identified, the levels of alkaline phosphatase (ALP), a marker commonly used in clinical diagnostics corresponding to old and young originators, were monitored after deposition for up to 48 h to mimic a crime scene setting. ALP was chosen as the biomarker due to its age-dependent nature. The biocatalytic assay was used to determine the age range of the originator using human serum samples. By means of statistical tools for evaluation and the physiological levels of ALP in healthy people, the applicability of this assay in forensic science was shown for the simultaneous determination of the age of the originator and the TSD of the blood spot. The stability of ALP in serum allows for the differentiation between old and young originators up to 2 days after the sample was left under mimicked crime scene conditions.

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Jan Halámek

State University of New York System

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Erica Brunelle

State University of New York System

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Vera Bocharova

Oak Ridge National Laboratory

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Juliana Agudelo

State University of New York System

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Joseph Wang

University of California

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Kyle C. Doty

State University of New York System

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