8 research outputs found
A new humanized antibody is effective against pathogenic fungi in vitro
Invasive fungal infections mainly affect patients undergoing transplantation, surgery, neoplastic disease, immunocompromised subjects and premature infants, and cause over 1.5 million deaths every year. The most common fungi isolated in invasive diseases are Candida spp., Cryptococcus spp., and Aspergillus spp. and even if four classes of antifungals are available (Azoles, Echinocandins, Polyenes and Pyrimidine analogues), the side effects of drugs and fungal acquired and innate resistance represent the major hurdles to be overcome. Monoclonal antibodies are powerful tools currently used as diagnostic and therapeutic agents in different clinical contexts but not yet developed for the treatment of invasive fungal infections. In this paper we report the development of the first humanized monoclonal antibody specific for β-1,3 glucans, a vital component of several pathogenic fungi. H5K1 has been tested on C. auris, one of the most urgent threats and resulted efficient both alone and in combination with Caspofungin and Amphotericin B showing an enhancement effect. Our results support further preclinical and clinical developments for the use of H5K1 in the treatment of patients in need
JANUS: an FPGA-based System for High Performance Scientific Computing
This paper describes JANUS, a modular massively parallel and reconfigurable
FPGA-based computing system. Each JANUS module has a computational core and a
host. The computational core is a 4x4 array of FPGA-based processing elements
with nearest-neighbor data links. Processors are also directly connected to an
I/O node attached to the JANUS host, a conventional PC. JANUS is tailored for,
but not limited to, the requirements of a class of hard scientific applications
characterized by regular code structure, unconventional data manipulation
instructions and not too large data-base size. We discuss the architecture of
this configurable machine, and focus on its use on Monte Carlo simulations of
statistical mechanics. On this class of application JANUS achieves impressive
performances: in some cases one JANUS processing element outperfoms high-end
PCs by a factor ~ 1000. We also discuss the role of JANUS on other classes of
scientific applications.Comment: 11 pages, 6 figures. Improved version, largely rewritten, submitted
to Computing in Science & Engineerin
Humanization of Antibodies using a Statistical Inference Approach
Antibody humanization is a key step in the preclinical phase of the development of therapeutic antibodies, originally developed and tested in non-human models (most typically, in mouse). The standard technique of Complementarity-Determining Regions (CDR) grafting into human Framework Regions of germline sequences has some important drawbacks, in that the resulting sequences often need further back-mutations to ensure functionality and/or stability. Here we propose a new method to characterize the statistical distribution of the sequences of the variable regions of human antibodies, that takes into account phenotypical correlations between pairs of residues, both within and between chains. We define a "humanness score" of a sequence, comparing its performance in distinguishing human from murine sequences, with that of some alternative scores in the literature. We also compare the score with the experimental immunogenicity of clinically used antibodies. Finally, we use the humanness score as an optimization function and perform a search in the sequence space, starting from different murine sequences and keeping the CDR regions unchanged. Our results show that our humanness score outperforms other methods in sequence classification, and the optimization protocol is able to generate humanized sequences that are recognized as human by standard homology modelling tools
A statics-dynamics equivalence through the fluctuation–dissipation ratio provides a window into the spin-glass phase from nonequilibrium measurements
Quantifying memory in spin glasses
10 pages, 8 figuresRejuvenation and memory, long considered the distinguishing features of spin glasses, have recently been proven to result from the growth of multiple length scales. This insight, enabled by simulations on the Janus~II supercomputer, has opened the door to a quantitative analysis. We combine numerical simulations with comparable experiments to introduce two coefficients that quantify memory. A third coefficient has been recently presented by Freedberg et al. We show that these coefficients are physically equivalent by studying their temperature and waiting-time dependence
Quantifying memory in spin glasses
10 pages, 8 figuresRejuvenation and memory, long considered the distinguishing features of spin glasses, have recently been proven to result from the growth of multiple length scales. This insight, enabled by simulations on the Janus~II supercomputer, has opened the door to a quantitative analysis. We combine numerical simulations with comparable experiments to introduce two coefficients that quantify memory. A third coefficient has been recently presented by Freedberg et al. We show that these coefficients are physically equivalent by studying their temperature and waiting-time dependence
Superposition principle and nonlinear response in spin glasses
International audienceThe extended principle of superposition has been a touchstone of spin-glass dynamics for almost 30 years. The Uppsala group has demonstrated its validity for the metallic spin glass, CuMn, for magnetic fields H up to 10 Oe at the reduced temperature Tr=T/Tg=0.95, where Tg is the spin-glass condensation temperature. For H>10 Oe, they observe a departure from linear response which they ascribe to the development of nonlinear dynamics. The thrust of this paper is to develop a microscopic origin for this behavior by focusing on the time development of the spin-glass correlation length, ξ(t,tw;H). Here, t is the time after H changes, and tw is the time from the quench for T>Tg to the working temperature T until H changes. We connect the growth of ξ(t,tw;H) to the barrier heights Δ(tw) that set the dynamics. The effect of H on the magnitude of Δ(tw) is responsible for affecting differently the two dynamical protocols associated with turning H off (TRM, or thermoremanent magnetization) or on (ZFC, or zero-field-cooled magnetization). This difference is a consequence of nonlinearity based on the effect of H on Δ(tw). Superposition is preserved if Δ(tw) is linear in the Hamming distance Hd (proportional to the difference between the self-overlap qEA and the overlap q[Δ(tw)]). However, superposition is violated if Δ(tw) increases faster than linear in Hd. We have previously shown, through experiment and simulation, that the barriers Δ(tw) do increase more rapidly than linearly with Hd through the observation that the growth of ξ(t,tw;H) slows down as ξ(t,tw;H) increases. In this paper, we display the difference between the zero-field-cooled ξZFC(t,tw;H) and the thermoremanent magnetization ξTRM(t,tw;H) correlation lengths as H increases, both experimentally and through numerical simulations, corresponding to the violation of the extended principle of superposition in line with the finding of the Uppsala Group