High-Energy Long-Lived Excited States in DNA Double Strands

International audienceDark DNA light: Dark excited states of alternating GC double strands emit fluorescence at 4000 cm-1 higher energy (see spectrum) and with four orders of magnitude longer lifetime compared to the bright * states. Such high-energy long-lived excited states are expected to play a key role in the DNA photoreactivity associated with the appearance of carcinogenic mutations

Fluorescence of Natural DNA: From the Femtosecond to the Nanosecond Time Scales

International audienceThe fluorescence of calf thymus DNA is studied by steady-state and time-resolved spectroscopy combining fluorescence upconversion and time-correlated single photon counting. The fluorescence spectrum is very similar to that of a stoichiometric mixture of monomeric chromophores, arising from bright ππ* states, and contrasts with the existing picture of exciplex emission in natural DNA. Yet, the DNA fluorescence decays span over five decades of time, with 98% of the photons being emitted at times longer than 10 ps. These findings, in association with recent studies on model duplexes, are explained by the involvement of dark states, possibly related to charge separation, serving as a reservoir for the repopulation of the bright ππ* states

Perbandingan Jenis Lumpur Berbahan Dasar Air dengan 2% Polyamine Polymer dan 7% Kcl Polymer

Perkembangan penelitian mengenai polyamine sangat pesat diberbagai belahan dunia dewasa ini. Salah satunya disebabkan karena pemakaian KCl memberikan efek negatif di lingkungan sekitarnya. Penelitian kali ini menyajikan perbandingan unjuk kerja antara Polyamine dan KCl berdasarkan observasi laboratorium. Parameter yang digunakan dalam pengujian ini meliputi swelling clay dan rheology (Gel Strength). Hasil dari penelitian ini menunjukkan bahwa unjuk kerja dari 2% Polyamine setara dengan 7% KCl polymer

Optical Properties of Guanine Nanowires: Experimental and Theoretical Study

International audienceLong nanowires formed by ca. 800 guanine tetrads (G4-wires) are studied in phosphate buffer containing sodium cations. Their room temperature optical properties are compared to those of the monomeric chromophore 2-deoxyguanine monophosphate (dGMP). When going from dGMP to G4-wires, both the absorption and the fluorescence spectra change. Moreover, the fluorescence quantum yield increases by a factor of 7.3 whereas the average fluorescence lifetime increases by more than 2 orders of magnitude, indicating emission associated with weakly allowed transitions. The behavior of G4-wires is interpreted in the light of a theoretical study performed in the frame of the exciton theory combining data from molecular dynamics and quantum chemistry. These calculations, carried out for a quadruplex composed of three tetrads, reveal the existence of various exciton states having different energies and oscillator strengths. The degree of delocalization of the quadruplex Franck−Condon excited states is larger than those found for longer duplexes following the same methodology. The slower excited-state relaxation in G4-wires compared to dGMP is explained by emission from exciton states, possibly limited on individual tetrads, whose coherence is reserved by the reduced mobility of guanines due to multiple Hoogsteen hydrogen bonds

Paradoxical interactions among estrogen receptors,

Abstract The phenomenon of mutual annihilation of action between 17b estradiol (E 2 ) and a selective estrogen receptor modulator (SERM), previously described in prepubertal rat diaphysis, epiphysis and uterus, has been investigated in ROS 17/2.8 rat osteoblastic cells and in transiently co-transfected cells in culture. In ROS 17/2.8 cells, the estrogen-induced marker enzyme creatine kinase B (CKB) was stimulated by raloxifene, tamoxifen and tamoxifen methiodide to a specific activity equal to or greater than that induced by 10 nM E 2 . However, when a fully inhibitory dose of any of these SERMS was given simultaneously with E 2 , no stimulation of CK activity resulted. Therefore, SERMS can be full agonists when acting alone, but complete antagonists to a super-physiological dose of estrogen. It is expected that excess tamoxifen would prevent the action of a SERM, but that the agonist activity of a SERM is abolished by 1000-fold less estrogen is a phenomenon without obvious explanation by classical pharmacology of competitive inhibition. To probe the mechanism of this interaction further, a ckb-CAT reporter plasmid, plus the human receptor expression plasmid, HEO, was transfected transiently into several cell types. In MCF-7 cells, a 1:10 ratio of E 2 to tamoxifen produced mutual annihilation, but the same ratio in ROS 17/2.8 or HeLa cells led to synergistic stimulation. In HeLa cells, co-transfected with the more efficient wild-type estrogen receptor plasmid, HEGO, synergy was demonstrated only at sub-saturation levels of HEGO. We speculate that, in the presence of estradiol and a SERM, not only active homodimers would be formed, but also hetero-dimers of estrogen-liganded and tamoxifen-liganded receptor monomers, depending on the molar ratio of their ligands and their relative affinities. The resulting hetero-dimer conformation would change the specific receptor surface for interactions with the growing number of co-activators and co-repressors, structural changes which could help to explain the mutual annihilation and synergy phenomena and their cell selectivity

(E)-3-(4-Fluoro­phen­yl)-1-[4-(methyl­sulfan­yl)phen­yl]prop-2-en-1-one

In the title mol­ecule, C16H13FOS, the dihedral angle between the two benzene rings is 8.68 (6)°. The H atoms of the central enone group are trans and one H atom is involved in a close intra­molecular C—H⋯O contact. The crystal structure is stabilized by weak C—H⋯π inter­actions

Simulation of gain-switched picosecond pulse generation from quantum well lasers

Circuit models for gain-switched quantum well laser diodes are developed and simulated using the circuit analysis program SPICE2. Effects of cavity length and number of wells on the output pulse shape are analysed. Picosecond pulses of 7 and 2 ps full-width at half-maximum (FWHM) are observed, corresponding to second and third quantized level transitions, respectively. A remarkable reduction in the output pulse width observed for the third quantized level transition, demonstrates the significance of higher sub-band transitions for ultrashort pulse generation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43336/1/11082_2004_Article_BF00331056.pd

Application of Artificial Intelligence with Natural Language Processing for qualitative research texts in the medical -patient relationship with mental illness through the use of mobile technologies

La Inteligencia Artificial (IA) sigue posicionándose en la sociedad como referencia del progreso tecnológico. Dentro de este campo, el Procesamiento de Lenguaje Natural (PLN) alcanza gran aceptación en disciplinas que trabajen con altos volúmenes de datos (Big Data). En este marco queremos ver qué aportan estos algoritmos, pero aplicado a la comunicación en el campo de la salud mental. Establecemos esta metodología con PLN partiendo de observaciones cualitativas previas en textos transcritos de grupos focales realizados a pacientes con enfermedad mental con el objetivo de entender si la aplicación de esta metodología aporta mejora al análisis de los datos como se ha demostrado en investigaciones previas, pero aplicado novedosamente al campo de la salud mental. Para ello se han ejecutado scripts basados en código Python y se han depurado los textos, clasificando las cadenas de palabras en entidades denominadas tokens y eliminando las palabras vacías. Posteriormente, se ha analizado la frecuencia de palabras y la conexión de frases, obteniendo un conjunto de estructuras donde aplicar técnicas de Machine Learning mediante Word2vec y generando vectores sobre los datos quedando representados con gráficas n-dimensionales en donde se configura un nuevo vocabulario con palabras agrupadas por cercanía. Aplicamos un método que sin el aprendizaje algorítmico se nos escapa en el análisis previo de una investigación cualitativa. Se identifican en el análisis los principales temas encontrados con el análisis cualitativo tradicional, mecanizando el proceso y facilitándolo. Se demuestra además que esta metodología es aplicable en la salud mental como en otros grupos de población.Artificial Intelligence (AI) continues to position itself in society as a benchmark for technological progress. Within this field, Natural Language Processing (NLP) reaches great acceptance in disciplines that work with high volumes of data (Big Data). In this framework we want to see what do these algorithms contribute with, but applied to communication in the field of mental health. We establish this methodology with NLP based on previous qualitative observations in transcribed texts of focus groups. These texts were obtained from focus groups carried out on patients with mental illnesses in order to understand whether the application of this methodology contributes to any improvement on the analysis of data, which has been shown in previous researches. However, this research has been applied in a novel way in the field of mental health. To do this, scripts based on Python code have been executed and the texts have been purified, classifyi ng the word strings into entities called tokens and eliminating stopwords. Subsequently, the frequency of words and the connection of sentences have been analyzed, obtaining a set of structures in which to apply Machine Learning techniques using word2vec and generating vectors on the data, which are represented with n -dimensional graphics where a new vocabulary based on proximity words is created. We are applying a method that without algorithmic learning we would be unable to obtain this type of information in the previous analysis of qualitative research.The main themes found with traditional qualitative analysis are identified in the analysis, mechanizing the process and facilitating it. It is also shown that this methodology is applicable in mental healt h as in other population groups