Antireflection microstructures on ZnSe for mid- and far-IR fabricated by femtosecond laser ablation assisted with wet chemical etching.

Most infrared materials used in high-power systems, such as optical parametric generators, have high values of refractive indices, which result in high Fresnel losses. The performance of conventional antireflection coatings is limited when used in high-power and ultra-broadband systems. An alternative approach is to fabricate antireflection microstructures (ARMs) that allow for a broadband increase in transmittance without reducing the damage threshold of the material. In this work, ARMs were fabricated on the surface of ZnSe crystals using the femtosecond laser ablation assisted with wet chemical etching method. This allowed to produce high aspect ratio microstructures that increase the transmittance up to 98% in the mid- and far- infrared regions.

Depth of response and response kinetics of isatuximab plus carfilzomib and dexamethasone in relapsed multiple myeloma.

The IKEMA study (Randomized, Open Label, Multicenter Study Assessing the Clinical Benefit of Isatuximab Combined With Carfilzomib [Kyprolis®] and Dexamethasone Versus Carfilzomib With Dexamethasone in Patients With Relapse and/or Refractory Multiple Myeloma Previously Treated With 1 to 3 Prior Lines; #NCT03275285) was a randomized, open-label, multicenter phase 3 study investigating isatuximab plus carfilzomib and dexamethasone (Isa-Kd) vs Kd in patients with relapsed multiple myeloma. This subanalysis analyzed the depth of response of Isa-Kd vs Kd. The primary end point was progression-free survival (PFS); secondary end points included overall response rate, very good partial response or better (≥VGPR) rate, complete response (CR) rate, and minimal residual disease (MRD) negativity rate (assessed in patients with ≥VGPR by next-generation sequencing at a 10-5 sensitivity level). At a median follow-up of 20.7 months, deeper responses were observed in the Isa-Kd arm vs the Kd arm, with ≥VGPR 72.6% vs 56.1% and CR of 39.7% vs 27.6%, respectively. MRD negativity occurred in 53 (29.6%) of 179 patients in the Isa-Kd arm vs 16 (13.0%) of 123 patients in the Kd arm, with 20.1% (Isa-Kd, 36 of 179 patients) vs 10.6% (Kd, 13 of 123 patients) reaching MRD-negative CR status. Achieving MRD negativity resulted in better PFS in both arms. A positive PFS treatment effect was seen with Isa-Kd in both MRD-negative patients (hazard ratio, 0.578; 95% CI, 0.052-6.405) and MRD-positive patients (hazard ratio, 0.670; 95% CI, 0.452-0.993). Exploratory analysis indicates that both current CR and MRD-negative CR rates are underestimated due to M-protein interference (potential adjusted CR rate, 45.8%; potential adjusted MRD-negative CR rate, 24.0%). In conclusion, there was a clinically meaningful improvement in depth of response with Isa-Kd. The CR rate in Isa-Kd was 39.7%. Mass spectrometry suggests that the potential adjusted CR rate could reach an unprecedented 45.8% of patients treated with Isa-Kd.

Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder-decoder models.

Like other experimental techniques, X-ray photon correlation spectroscopy is subject to various kinds of noise. Random and correlated fluctuations and heterogeneities can be present in a two-time correlation function and obscure the information about the intrinsic dynamics of a sample. Simultaneously addressing the disparate origins of noise in the experimental data is challenging. We propose a computational approach for improving the signal-to-noise ratio in two-time correlation functions that is based on convolutional neural network encoder-decoder (CNN-ED) models. Such models extract features from an image via convolutional layers, project them to a low dimensional space and then reconstruct a clean image from this reduced representation via transposed convolutional layers. Not only are ED models a general tool for random noise removal, but their application to low signal-to-noise data can enhance the data's quantitative usage since they are able to learn the functional form of the signal. We demonstrate that the CNN-ED models trained on real-world experimental data help to effectively extract equilibrium dynamics' parameters from two-time correlation functions, containing statistical noise and dynamic heterogeneities. Strategies for optimizing the models' performance and their applicability limits are discussed.

Nonequilibrium electron and lattice dynamics of strongly correlated Bi2Sr2CaCu2O8+δ single crystals.

The interplay between the electronic and lattice degrees of freedom in nonequilibrium states of strongly correlated systems has been debated for decades. Although progress has been made in establishing a hierarchy of electronic interactions with the use of time-resolved techniques, the role of the phonons often remains in dispute, a situation highlighting the need for tools that directly probe the lattice. We present the first combined megaelectron volt ultrafast electron diffraction and time- and angle-resolved photoemission spectroscopy study of optimally doped Bi2Sr2CaCu2O8+δ. Quantitative analysis of the lattice and electron subsystems' dynamics provides a unified picture of nonequilibrium electron-phonon interactions in the cuprates beyond the N-temperature model. The work provides new insights on the specific phonon branches involved in the nonequilibrium heat dissipation from the high-energy Cu-O bond stretching "hot" phonons to the lowest-energy acoustic phonons with correlated atomic motion along the <110> crystal directions and their characteristic time scales. It reveals a highly nonthermal phonon population during the first several picoseconds after the photoexcitation. The approach, taking advantage of the distinct nature of electrons and photons as probes, is applicable for studying energy relaxation in other strongly correlated electron systems.

Efficient cell surface display of Lip2 lipase using C-domains of glycosylphosphatidylinositol-anchored cell wall proteins of Yarrowia lipolytica.

The cell surface display of enzymes is of great interest because of its simplified purification stage and the possibility for recycling in industrial processes. In this study, we have focused on the cell wall immobilization of Yarrowia lipolytica Lip2 protein--an enzyme that has a wide technological application. By genome analysis of Y. lipolytica in addition to already characterized Ylcwp1, we identified five putative open reading frames encoding glycosylphosphatidylinositol-anchored proteins. Lip2 translation fusion with the carboxyl termini of these proteins revealed that all proteins were capable of immobilizing lipase in active form on the cell surface. The highest level of cell-bound lipase activity was achieved using C-domains encoded by YlCWP1, YlCWP3 (YALI0D27214g) and YlCWP6 (YALI0F18282g) comprising 16,173 ± 1,800, 18,785 ± 1,130 and 17,700 ± 2,101 U/g dry cells, respectively. To the best of our knowledge, these results significantly exceed the highest cell-bound lipase activity previously reported for engineered Saccharomyces cerevisiae and Pichia pastoris strains. Furthermore, the lyophilized biomass retained the activity and was robust to collecting/resuspending procedures. Nevertheless, in most cases, a substantial amount of lipase activity was also found in the growth medium. Further work will be necessary to better understand the nature of this phenomenon.