Fuzzing and Vulnerabilities Search

Fuzzing for vulnerabilities can be very effective if we know the input data format. This work contains description of network message format recovery algorithm and the usage of restored data model in fuzzing and vulnerabilities search

Hydrogenation of CO 2 by a Bifunctional PC( sp 3 )P Iridium(III) Pincer Complex Equipped with Tertiary Amine as a Functional Group

International audienceAbstract Reversible hydrogen storage in the form of stable and mostly harmless chemical substances such as formic acid (FA) is a cornerstone of a fossil fuels‐free economy. In the past, we have reported a primary amine‐functionalized bifunctional iridium(III)‐PC( sp 3 )P pincer complex as a mild and chemoselective catalyst for the additive‐free decomposition of neat formic acid. In this manuscript, we report on the successful application of a redesigned complex bearing tertiary amine functionality as a catalyst for mild hydrogenation of CO 2 to formic acid. The catalyst demonstrates TON up to 6×10 4 and TOF up to 1.7×10 4 h −1 . In addition to the practical value of the catalyst, experimental and computational mechanistic studies provide the rationale for the design of improved next‐generation catalysts

Fluorescent labeling of tRNAs for dynamics experiments

Transfer RNAs (tRNAs) are substrates for complex enzymes, such as aminoacyl-tRNA synthetases and ribosomes, and play an essential role in translation of genetic information into protein sequences. Here we describe a general method for labeling tRNAs with fluorescent dyes, so that the activities and dynamics of the labeled tRNAs can be directly monitored by fluorescence during the ribosomal decoding process. This method makes use of the previously reported fluorescent labeling of natural tRNAs at dihydrouridine (D) positions, but extends the previous method to synthetic tRNAs by preparing tRNA transcripts and introducing D residues into transcripts with the yeast enzyme Dus1p dihydrouridine synthase. Using the unmodified transcript of Escherichia coli tRNAPro as an example, which has U17 and U17a in the D loop, we show that Dus1p catalyzes conversion of one of these Us (mostly U17a) to D, and that the modified tRNA can be labeled with the fluorophores proflavin and rhodamine 110, with overall labeling yields comparable to those obtained with the native yeast tRNAPhe. Further, the transcript of yeast tRNAPhe, modified by Dus1p and labeled with proflavin, translocates on the ribosome at a rate similar to that of the proflavin-labeled native yeast tRNAPhe. These results demonstrate that synthetic tRNA transcripts, which may be designed to contain mutations not found in nature, can be labeled and studied. Such labeled tRNAs should have broad utility in research that involves studies of tRNA maturation, aminoacylation, and tRNA–ribosome interactions

Direct crosslinking of the antitumor antibiotic sparsomycin, and its derivatives, to A2602 in the peptidyl transferase center of 23S-like rRNA within ribosome-tRNA complexes

The antitumor antibiotic sparsomycin is a universal and potent inhibitor of peptide bond formation and selectively acts on several human tumors. It binds to the ribosome strongly, at an unknown site, in the presence of an N-blocked donor tRNA substrate, which it stabilizes on the ribosome. Its site of action was investigated by inducing a crosslink between sparsomycin and bacterial, archaeal, and eukaryotic ribosomes complexed with P-site-bound tRNA, on irradiating with low energy ultraviolet light (at 365 nm). The crosslink was localized exclusively to the universally conserved nucleotide A2602 within the peptidyl transferase loop region of 23S-like rRNA by using a combination of a primer extension approach, RNase H fragment analysis, and crosslinking with radioactive [(125)I]phenol-alanine-sparsomycin. Crosslinking of several sparsomycin derivatives, modified near the sulfoxy group, implicated the modified uracil residue in the rRNA crosslink. The yield of the antibiotic crosslink was weak in the presence of deacylated tRNA and strong in the presence of an N-blocked P-site-bound tRNA, which, as was shown earlier, increases the accessibility of A2602 on the ribosome. We infer that both A2602 and its induced conformational switch are critically important both for the peptidyl transfer reaction and for antibiotic inhibition. This supposition is reinforced by the observation that other antibiotics that can prevent peptide bond formation in vitro inhibit, to different degrees, formation of the crosslink

Machine-Learning-based global particle-identification algorithms at the LHCb experiment

One of the most important aspects of data analysis at the LHC experiments is the particle identification (PID). In LHCb, several different sub-detectors provide PID information: two Ring Imaging Cherenkov (RICH) detectors, the hadronic and electromagnetic calorimeters, and the muon chambers. To improve charged particle identification, we have developed models based on deep learning and gradient boosting. The new approaches, tested on simulated samples, provide higher identification performances than the current solution for all charged particle types. It is also desirable to achieve a flat dependency of efficiencies from spectator variables such as particle momentum, in order to reduce systematic uncertainties in the physics results. For this purpose, models that improve the flatness property for efficiencies have also been developed. This paper presents this new approach and its performance