Topological Constraints on the Dynamics of Vortex Formation in a Two-Dimensional Quantum Fluid.

We present experimental and theoretical results on formation of quantum vortices in a laser beam propagating in a nonlinear medium. Topological constrains richer than the mere conservation of vorticity impose an elaborate dynamical behavior to the formation and annihilation of vortex-antivortex pairs. We identify two such mechanisms, both described by the same fold-Hopf bifurcation. One of them is particularly efficient although it is not observed in the context of liquid helium films or stationary systems because it relies on the compressible nature of the fluid of light we consider and on the nonstationarity of its flow.

Photon thermalization and a condensation phase transition in an electrically pumped semiconductor microresonator.

We report on an experimental study of photon thermalization and condensation in a semiconductor microresonator in the weak-coupling regime. We measure the dispersion relation of light and the photon mass in a single-wavelength, broad-area resonator. The observed luminescence spectrum is compatible with a room-temperature, thermal-equilibrium distribution. A phase transition, identified by a saturation of the population at high energies and a superlinear increase of the occupation at low energy, takes place when the phase-space density is of order unity. We explain our observations by Bose-Einstein condensation of photons in equilibrium with a particle reservoir and discuss the relation with laser emission.

Endocrine disruption: the noise in available data adversely impacts the models' performance.

This paper is devoted to the analysis of available experimental data and preparation of predictive models for binding affinity of molecules with respect to two nuclear receptors involved in endocrine disruption (ED): the oestrogen (ER) and the androgen (AR) receptors. The ED-relevant data were retrieved from multiple sources, including the CERAPP, CoMPARA, and the Tox21 projects as well as ChEMBL and PubChem databases. Data analysis performed with the help of generative topographic mapping revealed the problem of low agreement between experimental values from different sources. Collected data were used to train both classification models for ER and AR binding activities and regression models for relative binding affinity (RBA) and median inhibition concentration (IC50). These models displayed relatively poor performance in classification (sensitivities ER = 0.34, AR = 0.49) and in regression (determination coefficient r 2 for the RBA and IC50 models in external validation varied from 0.44 to 0.76). Our analysis demonstrates that low models' performance resulted from misinterpreted experimental endpoints or wrongly reported values, thus confirming the observations reported in CERAPP and CoMPARA studies. Developed models and collected data sets included of 6215 (ER) and 3789 (AR) unique compounds, which are freely available.

Consensus QSAR models estimating acute toxicity to aquatic organisms from different trophic levels: algae, Daphnia and fish.

We report new consensus models estimating acute toxicity for algae, Daphnia and fish endpoints. We assembled a large collection of 3680 public unique compounds annotated by, at least, one experimental value for the given endpoint. Support Vector Machine models were internally and externally validated following the OECD principles. Reasonable predictive performances were achieved (RMSEext = 0.56-0.78) which are in line with those of state-of-the-art models. The known structural alerts are compared with analysis of the atomic contributions to these models obtained using the ISIDA/ColorAtom utility. A benchmarking against existing tools has been carried out on a set of compounds considered more representative and relevant for the chemical space of the current chemical industry. Our model scored one of the best accuracy and data coverage. Nevertheless, industrial data performances were noticeably lower than those on public data, indicating that existing models fail to meet the industrial needs. Thus, final models were updated with the inclusion of new industrial compounds, extending the applicability domain and relevance for application in an industrial context. Generated models and collected public data are made freely available.

Publicly available QSPR models for environmental media persistence.

The evaluation of persistency of chemicals in environmental media (water, soil, sediment) is included in European Regulations, in the context of the Persistence, Bioaccumulation and Toxicity (PBT) assessment. In silico predictions are valuable alternatives for compounds screening and prioritization. However, already existing prediction tools have limitations: narrow applicability domains due to their relatively small training sets, and lack of medium-specific models. A dataset of 1579 unique compounds has been collected, merging several persistence data sources annotated by, at least, one experimental dissipation half-life value for the given environmental medium. This dataset was used to train binary classification models discriminating persistent/non-persistent (P/nP) compounds based on REACH half-life thresholds on sediment, water and soil compartments. Models were built using ISIDA (In SIlico design and Data Analysis) fragment descriptors and support vector regression, random forest and naïve Bayesian machine-learning methods. All models scored satisfactory performances: sediment being the most performing one (BAext = 0.91), followed by water (BAext = 0.77) and soil (BAext = 0.76). The latter suffer from low detection of persistent ('P') compounds (Snext = 0.50), reflecting discrepancies in reported half-life measurements among the different data sources. Generated models and collected data are made publicly available.

Modelling of ready biodegradability based on combined public and industrial data sources.

The European Registration, Evaluation, Authorization and Restriction of Chemical Substances Regulation, requires marketed chemicals to be evaluated for Ready Biodegradability (RB), considering in silico prediction as valid alternative to experimental testing. However, currently available models may not be relevant to predict compounds of industrial interest, due to accuracy and applicability domain restriction issues. In this work, we present a new and extended RB dataset (2830 compounds), issued by the merging of several public data sources. It was used to train classification models, which were externally validated and benchmarked against already-existing tools on a set of 316 compounds coming from the industrial context. New models showed good performances in terms of predictive power (Balance Accuracy (BA) = 0.74-0.79) and data coverage (83-91%). The Generative Topographic Mapping approach identified several chemotypes and structural motifs unique to the industrial dataset, highlighting for which chemical classes currently available models may have less reliable predictions. Finally, public and industrial data were merged into global dataset containing 3146 compounds. This is the biggest dataset reported in the literature so far, covering some chemotypes absent in the public data. Thus, predictive model developed on the Global dataset has larger applicability domain than the existing ones.

Consensus models to predict oral rat acute toxicity and validation on a dataset coming from the industrial context.

We report predictive models of acute oral systemic toxicity representing a follow-up of our previous work in the framework of the NICEATM project. It includes the update of original models through the addition of new data and an external validation of the models using a dataset relevant for the chemical industry context. A regression model for LD50 and multi-class classification model for toxicity classes according to the Global Harmonized System categories were prepared. ISIDA descriptors were used to encode molecular structures. Machine learning algorithms included support vector machine (SVM), random forest (RF) and naïve Bayesian. Selected individual models were combined in consensus. The different datasets were compared using the generative topographic mapping approach. It appeared that the NICEATM datasets were lacking some relevant chemotypes for chemical industry. The new models trained on enlarged data sets have applicability domains (AD) sufficiently large to accommodate industrial compounds. The fraction of compounds inside the models' AD increased from 58% (NICEATM model) to 94% (new model). The increase of training sets improved models' prediction performance: RMSE values decreased from 0.56 to 0.47 and balanced accuracies increased from 0.69 to 0.71 for NICEATM and new models, respectively.

QSPR models for bioconcentration factor (BCF): are they able to predict data of industrial interest?

The bioconcentration factor (BCF), a key parameter required by the REACH regulation, estimates the tendency for a xenobiotic to concentrate inside living organisms. In silico methods can be valid alternatives to costly data measurements. However, in the industrial context, these theoretical approaches may fail to predict BCF with reasonable accuracy. We analyzed whether models built on public data only have adequate performances when challenged to predict industrial compounds. A new set of 1129 compounds has been collected by merging publicly available datasets. Generative Topographic Mapping was employed to compare this chemical space with a set of new compounds issued from the industry. Some new chemotypes absent in the training set (such as siloxanes) have been detected. A new BCF model has been built using ISIDA (In SIlico design and Data Analysis) fragment descriptors, support vector regression and random forest machine-learning methods. It has been externally validated on: (i) collected data from the literature and (ii) industrial data. The latter also served as benchmark for the freely available tools VEGA, EPISuite, TEST, OPERA. New model performs (RMSE of 0.58 log BCF units) comparably to existing ones but benefits of an extended applicability, covering the industrial set chemical space (78% data coverage).

Characterization of two DNA polymerases from the hyperthermophilic euryarchaeon Pyrococcus abyssi.

The complete genome sequence of the hyperthermophilic archaeon Pyrococcus abyssi revealed the presence of a family B DNA polymerase (Pol I) and a family D DNA polymerase (Pol II). To extend our knowledge about euryarchaeal DNA polymerases, we cloned the genes encoding these two enzymes and expressed them in Escherichia coli. The DNA polymerases (Pol I and Pol II) were purified to homogeneity and characterized. Pol I had a molecular mass of approximately 90 kDa, as estimated by SDS/PAGE. The optimum pH and Mg(2+) concentration of Pol I were 8.5-9.0 and 3 mm, respectively. Pol II is composed of two subunits that are encoded by two genes arranged in tandem on the P. abyssi genome. We cloned these genes and purified the Pol II DNA polymerase from an E. coli strain coexpressing the cloned genes. The optimum pH and Mg(2+) concentration of Pol II were 6.5 and 15-20 mm, respectively. Both P. abyssi Pol I and Pol II have associated 3'-->5' exonuclease activity although the exonuclease motifs usually found in DNA polymerases are absent in the archaeal family D DNA polymerase sequences. Sequence analysis has revealed that the small subunit of family D DNA polymerase and the Mre11 nucleases belong to the calcineurin-like phosphoesterase superfamily and that residues involved in catalysis and metal coordination in the Mre11 nuclease three-dimensional structure are strictly conserved in both families. One hypothesis is that the phosphoesterase domain of the small subunit is responsible for the 3'-->5' exonuclease activity of family D DNA polymerase. These results increase our understanding of euryarchaeal DNA polymerases and are of importance to push forward the complete understanding of the DNA replication in P. abyssi.

[Retroperitoneal mucinous cystadenoma]. / Le cystadénome mucineux rétropéritonéal.

The authors report an unusual case of retroperitoneal mucinous cystadenoma in contact with the isthmus of a horseshoe kidney and associated with congenital absence of the left ovary. The retroperitoneal site is very unusual, as only about twenty cases have been reported in this site. The pathogenesis of these tumours remains unclear and the authors discuss the various hypotheses proposed to date.

[Skin gangrene of the external genitalia. Report of 44 cases]. / Gangrène cutanée des organes génitaux externes. A propos de 44 cas.

STUDY AIM: The aim of this study is to report 44 cases of male external genitalia cutaneous gangrene which have been observed at the Principal Hospital of Dakar (Senegal) during a 4-year period. PATIENTS AND METHODS: The patients all belonged to a black and poor population (mean age: 60 years). Diabetes was present in 11% of the patients. In ten patients, no aetiology was found. The other 34 cases were secondary mainly to urogenital pathology (50%). In 50% of the cases, the lesions were localised on the external genitalia, in the other 50%, the lesions had spread to the hypogastrium and/or the perineum. Medical treatment included intensive care and triple antibiotic therapy, penicillin, gentamycin and metronidazole. A hyperbaric oxygen therapy was associated in 25% of the cases. The surgical treatment in the acute period included incising, debridement, paring, draining, urinary derivation (n = 36), and colostomy (n = 5). Thirteen patients had the benefit of sequential and prospective bacteriological tests. RESULTS: Spontaneous healing was obtained in 48% of the patients within 2 to 3 months. Secondary reconstructive surgery consisted mainly in cutaneous grafts. Global mortality rate was 34%, mortality rate was 30% in the secondary gangrenes, 40% in the primitive gangrenes. Mean hospitalisation duration was 6 weeks. Main sequelae were cheiloïd scars. CONCLUSIONS: The authors try to clarify the nosological imprecisions of this pathology by distinguishing between the secondary types and the primitive types corresponding to Fournier's gangrene, which still inspires many questions concerning its etio-pathogenesis. The surgical treatment must eradicate all necrosis by suited iterative procedures, associated with local care. Hyperbaric oxygen therapy was not efficient in this series. This pathology, although rare, needs to be better known, because only an early and efficient surgical and medical treatment will be able to decrease the exceptional gravity of the prognosis.