Manipulating the monolayer : responsive and reversible control of colloidal inorganic nanoparticle properties

Funding: EPSRC EP/K016342/1; Leverhulme Trust: RPG-2015-042For a wide range of nanomaterials, surface-bound molecules play a central role in defining properties, and are key to integration with other components – be they molecules, surfaces, or other nanoparticles. Predictable and general methods for manipulating the surface monolayer are therefore crucial to exploiting this new region of chemical space. This review highlights limitations of the few established methods for controlling nanoparticle-bound molecular functionality, then focuses on emerging new strategies. In particular, approaches that can achieve stimuli-responsive and reversible modification of surface-bound molecules in colloidal solution are examined, with an emphasis on using these methods to control nanoparticle properties such as solvent compatibility, catalytic activity and cytotoxicity. Finally, the outstanding challenges and future potential for precisely controlled nanoparticle bound monolayers are discussed.Publisher PDFPeer reviewe

Tiny Medicine: Nanomaterial-Based Biosensors

Tiny medicine refers to the development of small easy to use devices that can help in the early diagnosis and treatment of disease. Early diagnosis is the key to successfully treating many diseases. Nanomaterial-based biosensors utilize the unique properties of biological and physical nanomaterials to recognize a target molecule and effect transduction of an electronic signal. In general, the advantages of nanomaterial-based biosensors are fast response, small size, high sensitivity, and portability compared to existing large electrodes and sensors. Systems integration is the core technology that enables tiny medicine. Integration of nanomaterials, microfluidics, automatic samplers, and transduction devices on a single chip provides many advantages for point of care devices such as biosensors. Biosensors are also being used as new analytical tools to study medicine. Thus this paper reviews how nanomaterials can be used to build biosensors and how these biosensors can help now and in the future to detect disease and monitor therapies

Silicon Nanowire Sensors Enable Diagnosis of Patients via Exhaled Breath

Two of the biggest challenges in medicine today are the need to detect diseases in a noninvasive manner and to differentiate between patients using a single diagnostic tool. The current study targets these two challenges by developing a molecularly modified silicon nanowire field effect transistor (SiNW FET) and showing its use in the detection and classification of many disease breathprints (lung cancer, gastric cancer, asthma, and chronic obstructive pulmonary disease). The fabricated SiNW FETs are characterized and optimized based on a training set that correlate their sensitivity and selectivity toward volatile organic compounds (VOCs) linked with the various disease breathprints. The best sensors obtained in the training set are then examined under real-world clinical conditions, using breath samples from 374 subjects. Analysis of the clinical samples show that the optimized SiNW FETs can detect and discriminate between almost all binary comparisons of the diseases under examination with >80% accuracy. Overall, this approach has the potential to support detection of many diseases in a direct harmless way, which can reassure patients and prevent numerous unpleasant investigations

Design of protein-nanomaterial hybrids as tools for sensing, imaging and bioelectronics

217 p.El diseño de proteínas permite construir herramientas nanotecnológicas adaptadas para su uso en campos como la biomedicina o la industria. Las proteínas de repetición CTPR son una buena opción para desarrollar nano-herramientas dada su estructura modular y tolerancia a mutaciones, lo que permite combinar módulos funcionalizados sin comprometer la estabilidad de la proteína. Además, las proteínas CTPR pueden modificarse para desarrollar módulos que coordinan metales, lo que permite la unión de nanomateriales metálicos con propiedades interesantes como las nanopartículas de oro, o la síntesis de nanocristales metálicos in situ. En la presente tesis doctoral se propone un sistema modular de proteínas CTPR funcionalizadas con nanomateriales metálicos para su aplicación como herramientas nanotecnológicas en sensórica, imagen y bioelectrónica. Para ello, primero se establece un diseño de CTPR con residuos de coordinación de metales y se estudia en profundidad las propiedades fotoluminiscentes que emergen de nanocristales de oro coordinados a dichas CTPR. A continuación, se elaboran diseños de CTPR coordinando nanomateriales metálicos y se aplican como sensores de parámetros ambientales, como la temperatura o la presencia de iones metálicos; como sondas fluorescentes para detección correlativa de orgánulos celulares usando microscopía de fluorescencia y fluorescencia de rayos-X; y como bloques de construcción para elaborar biomateriales conductores

Artificial Intelligence and Machine Learning in Computational Nanotoxicology: Unlocking and Empowering Nanomedicine.

AbstractAdvances in nanomedicine, coupled with novel methods of creating advanced materials at the nanoscale, have opened new perspectives for the development of healthcare and medical products. Special attention must be paid toward safe design approaches for nanomaterial‐based products. Recently, artificial intelligence (AI) and machine learning (ML) gifted the computational tool for enhancing and improving the simulation and modeling process for nanotoxicology and nanotherapeutics. In particular, the correlation of in vitro generated pharmacokinetics and pharmacodynamics to in vivo application scenarios is an important step toward the development of safe nanomedicinal products. This review portrays how in vitro and in vivo datasets are used in in silico models to unlock and empower nanomedicine. Physiologically based pharmacokinetic (PBPK) modeling and absorption, distribution, metabolism, and excretion (ADME)‐based in silico methods along with dosimetry models as a focus area for nanomedicine are mainly described. The computational OMICS, colloidal particle determination, and algorithms to establish dosimetry for inhalation toxicology, and quantitative structure–activity relationships at nanoscale (nano‐QSAR) are revisited. The challenges and opportunities facing the blind spots in nanotoxicology in this computationally dominated era are highlighted as the future to accelerate nanomedicine clinical translation