Abnormality Detection inside Blood Vessels with Mobile Nanomachines

Motivated by the numerous healthcare applications of molecular communication within Internet of Bio-Nano Things (IoBNT), this work addresses the problem of abnormality detection in a blood vessel using multiple biological embedded computing devices called cooperative biological nanomachines (CNs), and a common receiver called the fusion center (FC). Due to blood flow inside a vessel, each CN and the FC are assumed to be mobile. In this work, each of the CNs perform abnormality detection with certain probabilities of detection and false alarm by counting the number of molecules received from a source, e.g., infected tissue. These CNs subsequently report their local decisions to a FC over a diffusion-advection blood flow channel using different types of molecules in the presence of inter-symbol interference, multi-source interference, and counting errors. Due to limited computational capability at the FC, OR and AND logic based fusion rules are employed to make the final decision after obtaining each local decision based on the optimal likelihood ratio test. For the aforementioned system, probabilities of detection and false alarm at the FC are derived for OR and AND fusion rules. Finally, simulation results are presented to validate the derived analytical results, which provide important insights.Comment: Submitted to IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Letters for possible publicatio

Abnormality detection using molecular communications based nano-scale sensor networks

Abnormality detection is one of the most highly anticipated application areas of Molecular Communication (MC) based nanonetworks. .is task entails sensing, detection, and reporting of abnormal changes in a fluid medium that may characterize a disease or disorder using a network of collaborating nanoscale sensors. Such distributed detection (DD) problems are of paramount interest in applications of nanonetworks. For the first time in literature, we proposed to employ sequential probability ratio test (SPRT) to decision fusion (DF). .e proposed approach yields considerable gains in the average number of samples required for the decision resulting in significant improvement in decision delay, which is one of the main challenges encountered in a molecular communications based sensor network. Existing strategies for such distributed collaborative detection problems require a complete statistical characterization of the underlying communication channel between the sensors and the fusion centre (FC), with the assumption of perfectly-known or accurately estimated channel parameters. .is assumption is usually impractical both due to mathematical intractability of the analytical channel models for MC except in a few ideal cases, and the slow and dispersive signal propagation characteristics that make the channel estimation a difficult task even in these ideal cases. .is work, for the first time in the literature, proposes to employ a machine learning (ML) approach to this task and shows that this approach provides the robustness and flexibility required for practical implementation. We focus on detection based on deep learning, specifically on a feed-forward neural network and a recurrent neural network structure that learn the underlying model from data. .is study shows that the proposed DF strategy can perform well without any knowledge of the communication channel

Channel modeling for diffusive molecular communication - a tutorial review

Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide channel models for timevarying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate simulation-driven and experiment-driven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems

Channel Modeling for Diffusive Molecular Communication - A Tutorial Review

Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide channel models for time-varying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate simulation-driven and experimentally-driven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems.Comment: 40 pages; 23 figures, 2 tables; this paper is submitted to the Proceedings of IEE

Excellentia Eminentia Effectio

"In these pages you will learn about the fascinating research endeavors that each of our faculty members is undertaking. We have divided their research into the broad categories of health, sustainability, information, and systems. While we recognize the imperfect nature of categorizing research that, by its very nature may be interdisciplinary or transdisciplinary, we nonetheless believe it will be helpful as a way to see the depth and breadth of our research endeavors within each grouping. As you read the profiles on these pages, I know you will begin to appreciate that, taken as a whole, the research spectrum at Columbia Engineering is exceptional and that, as our professors go about their work, they are at the cusp of making breakthroughs that will have a major impact on the way we live our lives today and tomorrow.

Macro-Scale Molecular Communications

The use of electromagnetic (EM) waves to transmit information has allowed our society to collaborate and share information on a scale that was unimaginable just a few decades ago. But as with any technology, there are areas where EM-based communications do not function well. For example, underwater and underground communications where EM waves experience high attenuation. This limitation has generated interest in an alternative mode of information transmission, molecular communications. In this thesis, after giving a survey of micro- and macro-scale molecular communications, the two most important aspects of molecular communications are identified: macroscale molecular communications and the experimental analysis of molecular communications. Molecular communication has been dominated so far by interest in the nano-scale, where the application focus is on drug-delivery and DNA communications, etc. Studies in the macro-scale are relatively rare compared to nano- and micro-scale research. This thesis looks closely at macro-scale molecular communication and attempts to improve our understanding of this novel communication paradigm. To achieve this, a mathematical model was developed, based on the advective-diffusion equation (ADE). The model was compared with experimental results, and showed a strong correlation. In addition, a model was developed to simulate molecular communication in both 1D and 3D environments. To generate the modulated chemicals and transmit them in the environment, an inhouse- built odour generator was used, and to detect the chemicals in the environment a mass spectrometer (MS) with a quadrupole mass analyser (QMA) was employed. Mass spectrometers have the ability to distinguish multiple chemicals in the environment concurrently, making them ideal detectors for use in molecular communications. Based on the experimental setup, various aspects of the communication paradigm are investigated in the three main sections. The first section focuses on the fundamental parameters that govern the propagation of molecules in a flow. The second section delves into the communication properties of this new form of information transfer. The final section studies aspects of simultaneous multiple-chemical transmission. Based on this multiple-chemical transmission, modulation methods are developed that exploit this new approach for use in molecular communications

Nanotechnology and supramolecular chemistry in controlled release and molecular recognition proceses for biomedical applications"

Tesis por compendioLa presente tesis doctoral, titulada "Nanotecnología y química supramolecular en procesos de liberación controlada y reconocimiento molecular para aplicaciones biomédicas", se centra en dos temas importantes: el reconocimiento molecular y los procesos de liberación controlada. Esta tesis doctoral está estructurada en cuatro capítulos. El primer capítulo introduce el concepto de materiales híbridos orgánicos-inorgánicos funcionalizados con puertas moleculares y sus aplicaciones biomédicas como nanomateriales para dirigir y controlar la liberación controlada de fármacos. Además se introduce una breve descripción sobre sensors colorimétricos basados en la base de la quimica supramolecular, particularmente en los procesos de reconocimiento molecular. En particular, el capítulo 2 describe la preparacion de cinco nanodispositivos que responden a enzimas. Estos materiales híbridos se componen de dos unidades principales: un soporte mesoporoso basado en sílice inorgánica, capaz de encapsular moléculas orgánicas y un compuesto orgánico anclado en la superficie externa del soporte mesoporoso inorgánico que actúa como puerta molecular. Todos los sistemas propuestos utilizan puertas moleculares peptídicas que responden a temperatura o enzimas como estímulo. La segunda parte de esta tesis doctoral se centra en el diseño y desarrollo de un nuevo compuesto químico capaz de detectar monóxido de carbono in vivo. En resumen, para todos los resultados antes mencionados podemos decir que esta tesis doctoral constituye una contribución científica original al desarrollo de la química supramolecular. Sus resultados derivados de los estudios presentados dejan rutas abiertas para continuar el estudio y el desarrollo de nuevos materiales híbridos y sensors químicos más eficientes para aplicaciones biomédicas y terapeuticas.This PhD thesis entitled "Nanotechnology and supramolecular chemistry in controlled release and molecular recognition processes for biomedical applications", is focused on two important subjects: molecular recognition and controlled delivery processes. This PhD thesis is structured in four chapters. The first chapter introduces the concept of organic-inorganic hybrid materials containing switchable "gate-like" ensembles and their biomedical applications as nanomaterials for targeting and control drug delivery. Furthermore, is introduced a short review about chromo-fluorogenic chemosensors based on basic principles of supramolecular chemistry, particulary in molecular recognition processes. In particular, in chapter 2 is focus on the development of enzymatic-driven nanodevices. These hybrid materials are composed of two main units: an inorganic silica based mesoporous scaffold, able to store organic molecules and an organic compound anchored on the external surface of the inorganic mesoporous support than acts as molecular gate. All the systems proposed use peptidic gates that respond to temperature or enzimatic stimulis. The second part of this PhD thesis is focused on the design and development of a new chemical compound capable of detecting carbon monoxide in vivo. In summary, for all the results above mentioned we can say that this PhD thesis constitutes an original scientific contribution to the development of supramolecular chemistry. Its results derived from the studies presented leaves open routes to continue the study and development of new hybrid materials and more efficient chemical sensors with biomedical and therapeutic applications.La present tesi doctoral, titulada "Nanotecnologia i química supramolecular en processos d'alliberament controlat i reconeixement molecular per a aplicacions biomèdiques", es centra en dos temes importants de la química: el reconeixement molecular i els processos d'alliberament controlat. Aquesta tesi doctoral està estructurada en quatre capítols. El primer capítol introdueix el concepte de materials híbrids orgànics-inorgànics funcionalitzats amb portes moleculars i les seves aplicacions biomèdiques com nanomaterials per dirigir i controlar l'alliberament controlat de fàrmacs. A més s'introdueix una breu descripció sobre sensors colorimètrics fonamentats en la base de la química supramolecular, particularment en els processos de reconeixement molecular. En particular, el capítol 2 descriu la preparació de cinc nanodispositius que responen a enzims. Aquests materials híbrids es componen de dues unitats principals: un suport mesoporos basat en sílice inorgànica, capaç d'encapsular molècules orgàniques i un compost orgànic ancorat a la superfície externa del suport mesoporós inorgànic que actua com a porta molecular. La segona part d'aquesta tesi doctoral es centra en el disseny i desenvolupaent d'un nou compost químic capaç de detectar monòxid de carboni in vivo. En resum, per a tots els resultats abans mencionats podem dir que esta tesi doctoral constituïx una contribució científica original al desenvolupament de la química supramolecular. Els seus resultats derivats dels estudis presentats deixen rutes obertes per a continuar l'estudi i el desenvolupament de nous materials hibrids i sensors químics més eficients per a aplicacions biomèdiques i terapeutiques.De La Torre Paredes, C. (2017). Nanotechnology and supramolecular chemistry in controlled release and molecular recognition proceses for biomedical applications" [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/94043TESISCompendi

System biology of alcoholism: Understanding of the consequences of the metabolism in brain cells

The addictive drug ethanol represents a serious universal health and social problem. Alcohol abuse and dependency have been increasing in many countries worldwide. Chronic use of alcohol leads to metabolic abnormalities and damage to the brain, which can result in severe cognitive dysfunction and addiction. Areas of the brain such as prefrontal cortex (PFC), the white matter, the hippocampus (HP), the cerebellum and the striatum are particularly vulnerable to the effects of alcohol. The striatum (ST), a region of brain closely associated with addiction mechanisms, is commonly divided into two regions, dorsal (DS) and ventral striatum (VS); the DS comprising caudate nucleus (CN) and putamen (P) while the VS is constituted mainly by nucleus accumbens (NAc). Neuroimaging analysis indicates that microstructural degradation is occurring in alcohol-affected brains and the abnormalities may be correlated with altered locomotor activity, aggressive behavior, changes in reward/aversion-related learning, deficient motor coordination, disturbances in procedural learning and memory. The NAc is strongly implicated in drug addiction but current evidence suggests that DS has also a significant role in this process. One of the aims of the project is to carry out comparative study of the sub-regions of human alcoholic striatum using two omics technologies (proteomics and metabolomics). There were no differences in the levels of dopamine (DA), 3,4-dihydrophenylacetic acid (DOPAC), serotonin (5HT), homovanillic acid (HVA), 5-hydroxyindoleacetic acid (HIAA), histamine, L-glutamate (Glu), -aminobutyric acid (GABA), tyrosine (Tyr) and tryptophan (Tryp) between the DS (CN and P) and VS (NAc) in control brains. Choline (Ch) and acetylcholine (Ach) were higher and, norepinephrine (NE) is lower, in the VS Overall. Alcohol-affected ST had lower levels of neurotransmitters except for Glu (30% higher in the alcoholic ventral striatum). Ratios of DOPAC/DA and HIAA/5HT were higher in alcohol-affected ST indicating an increase in the DA and 5HT turnover. Glutathione was significantly reduced in all three regions of alcohol-affected ST. The pattern of changes of 13 neurometabolites in alcoholic sub-regions relative to their respective control was similar. In order to investigate correlations between the alcohol-related changes in metabolites and and altered protein expressions, the author has selected a single sub-region of ST for a global proteomics study. By analysing CN tissues, 25 unique proteins were found to be differently expressed in alcohol-affected tissue 9 relative to control. From the identified proteins two were dopamine-related proteins and one a GABA-synthesizing enzyme glutamate decarboxylase (GAD) 65. Two proteins that are related to apoptosis and/or neuronal loss (BiD and amyloid-β A4 precursor protein-binding family B member 3) were increased. These results suggest that neurotransmitter metabolism and systems possibly related to neuroprotective mechanisms in both the DS (CN and P) and the VS (NAc) are significantly influenced by long-term heavy alcohol intake associated with alcoholism. Amongst the mechanisms mediating the effects of alcohol oxidative stress may have produce a particularly significant impact and could make a strong contribution to the microstructural damage. It has been known that alcohol can have a particularly damaging effect on the PFC and the HP regions of the fetus/developing/adolescent brain. The change imparted at those stages of development could be irreversible resulting in lasting deficits in a range of personality traits and impacting decision making, memory and learning. The HP is a significant place of neurogenesis and a source of neural stem cell (NSC). These can differentiate into neurons, astrocytes and oligodendrocytes and constitute building blocks of the developing central nervous system. They can also contribute to brain repair at later stages of development and, possibly, even in adulthood. On current evidence, alcohol reduces neurogenesis but little or no tangible information is available on the actual biochemistry and/or the fate of NSC. In the present experiments, the NSC obtained from rat embryos were exposed to various concentrations of ethanol (25 to 100 mM) for up to 96 hours. The cell numbers were found to be reduced in the presence of ethanol but only at the higher concentrations (50 and 100 mM). There were no apparent dramatic changes in the morphology of the cells but the numbers of neuron-like (MAP2-positive) cells were reduced by ethanol in a dose-dependent manner. In proteome analysis of alcoholic cells, a total of 28 proteins were altered in 50 mM ethanol relative to ethanol-free control. Of these proteins some were constituents of cytoskeleton, others were involved in transcription/translation, energy metabolism, signal transduction and oxidative stress. Two of the proteins identified as altered were nucleophosmin (NPM) and dead-end protein homolog 1 (DND1). These were further studied by immunological techniques in cultured neurons and astrocytes. NPM decreased and DND1 increased in both alcohol affected neurons and astrocytes cells