Implantable and transcutaneous photobiomodulation promote neuroregeneration and recovery of lost function after spinal cord injury

Spinal cord injury (SCI) is a cause of profound and irreversible damage, with no effective therapy to promote functional recovery. Photobiomodulation (PBM) may provide a viable therapeutic approach using red or near-infrared light to promote recovery after SCI by mitigating neuroinflammation and preventing neuronal apoptosis. Our current study aimed to optimize PBM dose regimens and develop and validate the efficacy of an invasive PBM delivery paradigm for SCI. Dose optimization studies were performed using a serum withdrawal model of injury in cultures of primary adult rat dorsal root ganglion neurons (DRGN). Implantable and transcutaneous PBM delivery protocols were developed and validated using cadaveric modeling. The efficacy of PBM in promoting recovery after SCI in vivo was studied in a dorsal column crush injury model of SCI in adult rats. Optimal neuroprotection in vitro was achieved between 4 and 22 mW/cm2. 11 mW/cm2 for 1 min per day (0.66 J/cm2) increased cell viability by 45% over 5 days (p <0.0001), increasing neurite outgrowth by 25% (p < 0.01). A method for invasive application of PBM was developed using a diffusion-tipped optogenetics fiber optic. Delivery methods for PBM were developed and validated for both invasive (iPBM) and noninvasive (transcutaneous) (tcPBM) application. iPBM and tcPBM (24 mW/cm2 at spinal cord, 1 min per day (1.44 J/cm2) up to 7 days) increased activation of regeneration-associated protein at 3 days after SCI, increasing GAP43+ axons in DRGN from 18.0% (control) to 41.4% ± 10.5 (iPBM) and 45.8% ± 3.4 (tcPBM) (p < 0.05). This corresponded to significant improvements at 6 weeks post-injury in functional locomotor and sensory function recovery (p < 0.01), axonal regeneration (p < 0.01), and reduced lesion size (p < 0.01). Our results demonstrated that PBM achieved a significant therapeutic benefit after SCI, either using iPBM or tcPBM application and can potentially be developed for clinical use in SCI patients

Global Optimization Algorithms in Multidisciplinary DesignOptimization

While Multidisciplinay Design Optimization (MDO) literature focuses mainly on the development of different formulations, through the manipulation of design variables, less attention is generally devoted to the combination of specific MDO formulations with existing nonlinear optimization algorithms. In this paper, the focus is on the application of a Global Optimization (GO) algorithm to an MDO problem. We first introduce and describe some MDO approaches from the literature. Then, we consider our MDO formulation where we deal with the GO box-constrained problem min_{a R We assume that the solution of the latter problem requires the use of a derivative-free methods since the derivatives of f(x) are unavailable and/or the function must be treated as a `black-box'. Within this framework we study some globally convergent modifications of the evolutionary Particle Swarm Optimization (PSO) algorithm, suitably adapted for box-constrained optimization. Finally, we report our numerical experience. Preliminary results are provided for a simple hydroelastic problem. Two different numerical tools are involved: a fluid dynamic solver, to simulate the ow around hydrofoils traveling in proximity of the air-water interface, and a simplified torsion-flexional wing model

Author Correction: Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Correction to: Nature Geneticshttps://doi.org/10.1038/s41588-023-01314-0, published online 13 March 2023. In the version of the article initially published, the sample sizes in the main text and Supplementary Tables 1 and 2 were incorrect. In the abstract, the last paragraph of the Introduction, the first paragraph of the Results, the top box in Figure 1a and the Supplementary Information, the total sample size has been corrected from 580,869 to 588,452 participants and the size of the European cohort from 468,062 to 475,645. Some of the effect sizes in Supplementary Table 14 (columns W, Z, AC, AF) had the wrong sign. There was also an error in Supplementary Table 3 where the sample size instead of the variant count was shown for EXCEED. The errors do not affect the conclusions of the study. Additionally, two acknowledgments for use of INTERVAL pQTL and Lung eQTL consortium data were omitted from the Supplementary Information. These errors have been corrected in the Supplementary Information and HTML and PDF versions of the article

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies