Pandemic (H1N1) 2009 Cluster Analysis: A Preliminary Assessment

Pandemic (H1N1) 2009 virus has been causing major concerns around the world because of its epidemic potential, rapid dissemination, rate of mutations, and the number of fatalities. One way to gain an advantage over this virus is to use existing rapid bioinformatics tools to examine easily and inexpensively generated genetic sequencing data. We have used the protein sequences deposited with the National Center for Biotechnology Information (NCBI) for data mining to study the relationship among the Pandemic (H1N1) 2009 proteins. There are 11 proteins in the Pandemic (H1N1) 2009 virus, and analysis of sequences from 65 different locations around the globe has resulted in two major clusters. These clusters illustrate the Pandemic H1N1 2009 virus is already experiencing significant genetic drift and that rapid worldwide travel is affecting the distribution of genetically distinct isolates

The Baltimore declaration toward the exploration of organoid intelligence

We, the participants of the First Organoid Intelligence Workshop - "Forming an OI Community" (22-24 February 2022), call on the international scientific community to explore the potential of human brain-based organoid cell cultures to advance our understanding of the brain and unleash new forms of biocomputing while recognizing and addressing the associated ethical implications. The term "organoid intelligence" (OI) has been coined to describe this research and development approach (1) in a manner consistent with the term "artificial intelligence" (AI) - used to describe the enablement of computers to perform tasks normally requiring human intelligence. OI has the potential for diverse and far-reaching applications that could benefit humankind and our planet, and which urge the strategic development of OI as a collaborative scientific discipline. OI holds promise to elucidate the physiology of human cognitive functions such as memory and learning. It presents game-changing opportunities in biological and hybrid computing that could overcome significant limitations in silicon-based computing. It offers the prospect of unparalleled advances in interfaces between brains and machines. Finally, OI could allow breakthroughs in modeling and treating dementias and other neurogenerative disorders that cause an immense and growing disease burden globally. Realizing the world-changing potential of OI will require scientific breakthroughs. We need advances in human stem cell technology and bioengineering to recreate brain architectures and to model their potential for pseudo-cognitive capabilities. We need interface breakthroughs to allow us to deliver input signals to organoids, measure output signals, and employ feedback mechanisms to model learning processes. We also need novel machine learning, big data, and AI technologies to allow us to understand brain organoids

Characterization of selected immobilized metal-ions using solid phase extraction sorbents

Solid phase extraction (SPE) has been developed as an alternative to liquid-liquid extraction (LLE) in the sample preparation process. The advantages of SPE over LLE are that it is a more useful, reliable tool for sample preparation, which offers greater selectivity. The selectivity of an SPE sorbent is vital for the isolation of analyte from a biological matrix containing a myriad of interferences. The use of conventional ion exchange SPE for such an extraction process might not be adequate due to the adverse effects of interfering ions. Metals immobilized on various modified silicas were investigated to determine if the addition of metals improved selectivity. The selectivity of these sorbents was studied by the extraction of analytes from high ionic strength matrices. Extraction selectivity was found to depend on different factors, including the type of bonded species, metal ions used and the analytes, counter ions, sample pH and elution solvent composition. Utilizing coordination complexation between analytes and immobilized metal ions, particularly when different phases are stacked, can increase selectivity for a particular analyte. Metals immobilized by ionic exchange sorbents were observed to retain analytes of tridentate chelation capability more than immobilized metals on bonded chelators. However, bonded chelators were observed to be advantageous because they more strongly retained metal ions, relative to ionic exchangers. The interactions of immobilized silver ions with unsaturated molecules utilizing SPE were investigated. Retention of silver ions was found dependent on the nature of bonded phase. The silver ions immobilized by coordination interactions showed weaker retention than silver immobilized by ionic interactions. Retention of alkenes by silver was found to have higher flow dependence, as compared to ionic exchange or ligand exchange processes. Retention of analytes was observed to depend on a variety of factors, including the type of bonded phase used for silver immobilization, the composition of the elution solvent, steric factors, the degree of unsaturation, the geometry and position of the double bonds of the analyte molecules. Extraction selectivity for geometrical isomers decreased when silver ions were immobilized by long chain cation exchangers versus those on conventional short chain cation exchangers

Study of the mechanical properties of two organic-inorganic hybrid systems : GPTMS/colloidal silica and GPTMS/TEOS

International audienceThis work investigates the mechanical properties of different scratch resistant coatings, namely, a mixture of 3-glycidoxypropyltrimethoxysilane (GPTMS) with either colloidal silica particles or tetraethoxysilane (TEOS). Coatings were prepared by the hydrolysis and the condensation of the precursor's alkoxide (sol-gel process) with thermally catalyzed polymerization of epoxy ring of GPTMS.Dip deposition techniques were used on silicon substrate. The nanoindentation technique was used to analyze the force required to indent the coating with a diamond tip. At low forces, this technique, based on indentation depth, predicts the hardness and the elastic modulus of the coating, while at higher forces, cracks appear. Another analysis based on geometric approach, namely, the crack length, allows the determination of both coating and interface toughness

Design and controlled synthesis by dual polymerization of new organic-​inorganic hybrid material for photonic devices

International audienc

Synthesis and characterization of a photosensitive organic–inorganic, hybrid positive resin type material: application to the manufacture of microfluidic devices by laser writing

International audienc

Synthesis of new vinyl ether functionalized silica for UV-patterning

International audienc

Double-Blind Characterization of Non-Genome-Sequenced Bacteria by Mass Spectrometry-Based Proteomics▿

Due to the possibility of a biothreat attack on civilian or military installations, a need exists for technologies that can detect and accurately identify pathogens in a near-real-time approach. One technology potentially capable of meeting these needs is a high-throughput mass spectrometry (MS)-based proteomic approach. This approach utilizes the knowledge of amino acid sequences of peptides derived from the proteolysis of proteins as a basis for reliable bacterial identification. To evaluate this approach, the tryptic digest peptides generated from double-blind biological samples containing either a single bacterium or a mixture of bacteria were analyzed using liquid chromatography-tandem mass spectrometry. Bioinformatic tools that provide bacterial classification were used to evaluate the proteomic approach. Results showed that bacteria in all of the double-blind samples were accurately identified with no false-positive assignment. The MS proteomic approach showed strain-level discrimination for the various bacteria employed. The approach also characterized double-blind bacterial samples to the respective genus, species, and strain levels when the experimental organism was not in the database due to its genome not having been sequenced. One experimental sample did not have its genome sequenced, and the peptide experimental record was added to the virtual bacterial proteome database. A replicate analysis identified the sample to the peptide experimental record stored in the database. The MS proteomic approach proved capable of identifying and classifying organisms within a microbial mixture