Unbiased Screening of Novel Infrared Nonlinear Optical Materials with High Thermal Conductivity: Long-neglected Nitrides and Popular Chalcogenides.

Traditional infrared (IR) nonlinear optical (NLO) materials such as AgGaS2 are crucial to key devices for solid-state lasers, however, low laser damage thresholds intrinsically hinder their practical application. Here, a robust strategy is proposed for unbiased high-throughput screening of more than 140 000 materials to explore novel IR NLO materials with high thermal conductivity and wide band gap which are crucial to intrinsic laser damage threshold. Via our strategy, 106 compounds with desired band gaps, NLO coefficients and thermal conductivity are screened out, including 8 nitrides, 68 chalcogenides, in which Sr2 SnS4 is synthesized to verify the reliability of our process. Remarkably, thermal conductivity of nitrides is much higher than that of chalcogenides, e.g., 5×AgGaS2 (5.13 W/m K) for ZrZnN2 , indicating that nitrides could be a long-neglected system for IR NLO materials. This strategy provides a powerful tool for searching NLO compounds with high thermal conductivity.

Prediction of Fluorooxoborates with Colossal Second Harmonic Generation (SHG) Coefficients and Extremely Wide Band Gaps: Towards Modulating Properties by Tuning the BO3 /BO3 F Ratio in Layers.

Fluorooxoborates have inspired investigations of deep-ultraviolet (DUV) nonlinear optical (NLO) materials that can meet the multiple criteria. Herein, five stable structures with the composition of BaB2 O3 F2 (I-V) are discovered using the ab initio evolutionary algorithm. Among them, BaB2 O3 F2 -I has been synthesized experimentally and confirms the reliability of the method. All of the predicted structures possess extremely wide band gaps (8.1-9.0 eV). Moreover, four new structures exhibit giant second harmonic generation (SHG) coefficients (>3×KDP, d36 =0.39 pm V-1 ). A novel type of the [BOF] layer with BO3 :BO3 F ratio of [1:1] is found in BaB2 O3 F2 -II and BaB2 O3 F2 -III. While BaB2 O3 F2 -IV and BaB2 O3 F2 -V are solely composed of the BO3 F group and have colossal SHG coefficients (ca. 4×KDP). It gives the direct evidence that the BO3 F group could generate strong SHG effect. Most importantly, the influences of BO3 :BO3 F ratio and their number density on band gap, birefringence and SHG effects are investigated.

Comprehensive peripheral blood immunoprofiling reveals five immunotypes with immunotherapy response characteristics in patients with cancer.

The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient's immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types and gene expression profiles. An independent analysis of 17,800 open-source transcriptomes with the same approach corroborated these findings. Continuous immunotype-based signature scores were developed to correlate systemic immunity with patient responses to different cancer treatments, including immunotherapy, prognostically and predictively. Our approach and findings illustrate the potential utility of a simple blood test as a flexible tool for stratifying cancer patients into therapy response groups based on systemic immunoprofiling.

Target-Driven Design of Deep-UV Nonlinear Optical Materials via Interpretable Machine Learning.

The development of a data-driven science paradigm is greatly revolutionizing the process of materials discovery. Particularly, exploring novel nonlinear optical (NLO) materials with the birefringent phase-matching ability to deep-ultraviolet (UV) region is of vital significance for the field of laser technologies. Herein, a target-driven materials design framework combining high-throughput calculations (HTC), crystal structure prediction, and interpretable machine learning (ML) is proposed to accelerate the discovery of deep-UV NLO materials. Using a dataset generated from HTC, an ML regression model for predicting birefringence is developed for the first time, which exhibits a possibility of achieving fast and accurate prediction. Essentially, crystal structures are adopted as the only known input of this model to establish a close structure-property relationship mapping birefringence. Utilizing the ML-predicted birefringence which can affect the shortest phase-matching wavelength, a full list of potential chemical compositions based on an efficient screening strategy is identified. Further, eight structures with good stability are discovered to show potential applications in the deep-UV region, owing to their promising NLO-related properties. This study provides a new insight into the discovery of NLO materials and this design framework can identify desired materials with high performances in the broad chemical space at a low computational cost.

Developmental intestinal microbiome alterations in canine fading puppy syndrome: a prospective observational study.

Fading puppy syndrome (FPS) is a fatal condition in neonatal dogs. Intestinal microbial alterations, although never investigated, may be involved in its pathophysiology. The study examined the occurrence of FPS and its associations with dam, puppy, and husbandry characteristics, compared the intestinal microbial diversity of healthy puppies and those with FPS, and examined whether intestinal microbiomes are predictive of FPS. Day 1 and 8 post-partum (PP) rectal swabs were collected from healthy puppies and puppies which later developed FPS. Microbial compositional structure, including alpha and beta diversities and relative abundance of specific taxa were compared between groups, and microbial data was applied to a machine-learning model to assess the predictive performance of microbial indices of FPS or death. FPS occurred in 22/165 puppies (13%), with a 100% mortality rate. FPS was associated (P < 0.001) with decreased Day 1 PP puppy activity. Day 1 (P = 0.003) and 8 (P = 0.005) PP rectal beta diversities were different in puppies with FPS vs healthy ones. Increased Proteobacteria/Firmicutes ratio, increased relative abundance of Pasteurellaceae, and decreased relative abundance of Clostridia and Enterococcus were associated with FPS. A machine-learning model showed that Day 1 PP rectal microbiome composition accurately predicted FPS-related death. We found that specific rectal microbial phenotypes are associated with FPS, reflecting the significant role of microbiome alterations in this phenomenon. These findings may serve as useful microbial indices for early diagnosis of puppies at risk of FPS and may provide specific therapeutic targets.