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We report high efficiency continuous wave laser oscillations at 1063.6 nm from an ultrafast laser written Nd(3+):GdVO4 channel waveguide under the 808 nm optical excitation. A record 17 mm·s(-1) writing speed was used while the low propagation loss of the waveguide (~0.5 dB·cm(-1)) enabled laser performance with a threshold pump power as low as 52 mW and a near to quantum defect limited laser slope efficiency of 70%.

Buried channel waveguides have been fabricated in Nd:GGG crystals by using the femtosecond laser inscription. The waveguides are confined between two filaments with propagation losses of 2.0 dB/cm. Stable continuous wave laser oscillation at ~1061 nm has been demonstrated at room temperature. Under 808 nm optical excitation, a pump threshold of 29 mW and a slope efficiency of 25% have been obtained.

Advanced brain imaging analysis methods, including multivariate pattern analysis (MVPA), functional connectivity, and functional alignment, have become powerful tools in cognitive neuroscience over the past decade. These tools are implemented in custom code and separate packages, often requiring different software and language proficiencies. Although usable by expert researchers, novice users face a steep learning curve. These difficulties stem from the use of new programming languages (e.g., Python), learning how to apply machine-learning methods to high-dimensional fMRI data, and minimal documentation and training materials. Furthermore, most standard fMRI analysis packages (e.g., AFNI, FSL, SPM) focus on preprocessing and univariate analyses, leaving a gap in how to integrate with advanced tools. To address these needs, we developed BrainIAK (brainiak.org), an open-source Python software package that seamlessly integrates several cutting-edge, computationally efficient techniques with other Python packages (e.g., Nilearn, Scikit-learn) for file handling, visualization, and machine learning. To disseminate these powerful tools, we developed user-friendly tutorials (in Jupyter format; https://brainiak.org/tutorials/) for learning BrainIAK and advanced fMRI analysis in Python more generally. These materials cover techniques including: MVPA (pattern classification and representational similarity analysis); parallelized searchlight analysis; background connectivity; full correlation matrix analysis; inter-subject correlation; inter-subject functional connectivity; shared response modeling; event segmentation using hidden Markov models; and real-time fMRI. For longrunning jobs or large memory needs we provide detailed guidance on high-performance computing clusters. These notebooks were successfully tested at multiple sites, including as problem sets for courses at Yale and Princeton universities and at various workshops and hackathons. These materials are freely shared, with the hope that they become part of a pool of open-source software and educational materials for large-scale, reproducible fMRI analysis and accelerated discovery.

This study demonstrates the high efficiency of heparinized decellularized adipose tissue matrix loaded with bFGF in promoting adipose neotissue formation and neovascularization with long-term volume stability.

Introduction Abnormal glycolytic metabolism contributes to joint inflammation and destruction in rheumatoid arthritis (RA). We examine the expression and function of hexokinases in RA and evaluate the potential of their specific inhibitor for clinical treatment. Methods Detection of HKs was assessed in synovial tissue by immunohistology and Western blot. SiRNA and a specific hexokinases inhibitor, lonidamine (LND), were used to evaluate the role of hexokinase-I/II (HK-I/II). Pro-inflammatory and glycolysis factors, cell viability, and apoptosis were assessed by ELISA, RT-qPCR, MTS, and flow cytometry. The clinical effects of LND on type II collagen-induced arthritis (CIA) in DBA-/1 mouse model was evaluated by scoring their clinical responses, synovitis, and cartilage destructions, and ELISA was employed to analyze the concentrations of antibody in the serum of CIA model. Results HK-I/II expression and their activities increased in the synovium of RA compared with osteoarthritis (OA). Silencing HK-I/II (siHK-I/II) or LND treatment decreased the production of pro-inflammatory factors, such as IL-6, IL-8, CXCL9, CXCL10, and CXCL11, and cell viability, but induced cell apoptosis of RASFs. The expression of TNF-α and IL-1β of macrophage in response to LPS stimulation were depressed as well after treatment with siHK-I/II or LND. Furthermore, leucocyte infiltration co-cultured with RASFs was also suppressed after inhibiting the expression or activity of HK-I/II. These anti-inflammatory effects overlapped with their anti-glycolytic activities. Treatment with LND in mice with CIA decreased the production of antibodies against IgG1, IgG2a, and IgG2b and consequently attenuated joint inflammation and destruction. Conclusions HK-I/II contribute to shape the inflammatory phenotype of RASFs and macrophages. LND may be a potential drug in treating patients with RA. Electronic supplementary material The online version of this article (10.1186/s13075-019-1865-3) contains supplementary material, which is available to authorized users.

We report on the fabrication of a nonlinear cladding waveguide in BiB 3 O 6 crystal by using femtosecond laser inscription. The waveguide (with a nearly circular cross section of 150 m diameter) shows good guiding properties in two transverse polarizations. The guided-wave secondharmonic generation (SHG) at 532 nm green light has been realized under CW and pulsed wave pump at 1064 nm, based on the Type I birefringent phase matching configuration. The conversion efficiencies for CW and pulsed green laser SHG are 0.083 and 25%, respectively.

BiB3O6 crystals possess large piezoelectric coefficients and high-temperature stability of their piezoelectric properties, which is promising for piezoelectric sensor applications.