Spectral Reconstruction from RGB Imagery: A Potential Option for Infinite Spectral Data?

Spectral imaging has revolutionisedvarious fields by capturing detailed spatial and spectral information. However, its high cost and complexity limit the acquisition of a large amount of data to generalise processes and methods, thus limiting widespread adoption. To overcome this issue, a body of the literature investigates how to reconstruct spectral information from RGB images, with recent methods reaching a fairly low error of reconstruction, as demonstrated in the recent literature. This article explores the modification of information in the case of RGB-to-spectral reconstruction beyond reconstruction metrics, with a focus on assessing the accuracy of the reconstruction process and its ability to replicate full spectral information. In addition to this, we conduct a colorimetric relighting analysis based on the reconstructed spectra. We investigate the information representation by principal component analysis and demonstrate that, while the reconstruction error of the state-of-the-art reconstruction method is low, the nature of the reconstructed information is different. While it appears that the use in colour imaging comes with very good performance to handle illumination, the distribution of information difference between the measured and estimated spectra suggests that caution should be exercised before generalising the use of this approach.

Relationship between reflectance and degree of polarization in the VNIR-SWIR: A case study on art paintings with polarimetric reflectance imaging spectroscopy.

We study the relationship between reflectance and the degree of linear polarization of radiation that bounces off the surface of an unvarnished oil painting. We design a VNIR-SWIR (400 nm to 2500 nm) polarimetric reflectance imaging spectroscopy setup that deploys unpolarized light and allows us to estimate the Stokes vector at the pixel level. We observe a strong negative correlation between the S0 component of the Stokes vector (which can be used to represent the reflectance) and the degree of linear polarization in the visible interval (average -0.81), while the correlation is weaker and varying in the infrared range (average -0.50 in the NIR range between 780 and 1500 nm, and average -0.87 in the SWIR range between 1500 and 2500 nm). By tackling the problem with multi-resolution image analysis, we observe a dependence of the correlation on the local complexity of the surface. Indeed, we observe a general trend that strengthens the negative correlation for the effect of artificial flattening provoked by low image resolutions.

Governance hurdles for expansion of low trophic mariculture production in Sweden.

The study examines the governance of low trophic species mariculture (LTM) using Sweden as a case study. LTM, involving species such as seaweeds and mollusks, offers ecosystem services and nutritious foods. Despite its potential to contribute to blue growth and Sustainable Development Goals, LTM development in the EU and OECD countries has stagnated. A framework for mapping governance elements (institutions, structures, and processes) and analyzing governance objective (effective, equitable, responsive, and robust) was combined with surveys addressed to the private entrepreneurs in the sector. Analysis reveals ineffective institutions due to lack of updated legislation and guidance, resulting in ambiguous interpretations. Governance structures include multiple decision-making bodies without a clear coordination agency. Licensing processes were lengthy and costly for the private entrepreneurs, and the outcomes were uncertain. To support Sweden's blue bioeconomy, LTM governance requires policy integration, clearer direction, coordinated decision-making, and mechanisms for conflict resolution and learning.

VEGF-C prophylaxis favors lymphatic drainage and modulates neuroinflammation in a stroke model.

Meningeal lymphatic vessels (MLVs) promote tissue clearance and immune surveillance in the central nervous system (CNS). Vascular endothelial growth factor-C (VEGF-C) regulates MLV development and maintenance and has therapeutic potential for treating neurological disorders. Herein, we investigated the effects of VEGF-C overexpression on brain fluid drainage and ischemic stroke outcomes in mice. Intracerebrospinal administration of an adeno-associated virus expressing mouse full-length VEGF-C (AAV-mVEGF-C) increased CSF drainage to the deep cervical lymph nodes (dCLNs) by enhancing lymphatic growth and upregulated neuroprotective signaling pathways identified by single nuclei RNA sequencing of brain cells. In a mouse model of ischemic stroke, AAV-mVEGF-C pretreatment reduced stroke injury and ameliorated motor performances in the subacute stage, associated with mitigated microglia-mediated inflammation and increased BDNF signaling in brain cells. Neuroprotective effects of VEGF-C were lost upon cauterization of the dCLN afferent lymphatics and not mimicked by acute post-stroke VEGF-C injection. We conclude that VEGF-C prophylaxis promotes multiple vascular, immune, and neural responses that culminate in a protection against neurological damage in acute ischemic stroke.

Complementary and Inducible creERT2 Mouse Models for Functional Evaluation of Endothelial Cell Subtypes in the Bone Marrow.

In the adult bone marrow (BM), endothelial cells (ECs) are an integral component of the hematopoietic stem cell (HSC)-supportive niche, which modulates HSC activity by producing secreted and membrane-bound paracrine signals. Within the BM, distinct vascular arteriole, transitional, and sinusoidal EC subtypes display unique paracrine expression profiles and create anatomically-discrete microenvironments. However, the relative contributions of vascular endothelial subtypes in supporting hematopoiesis is unclear. Moreover, constitutive expression and off-target activity of currently available endothelial-specific and endothelial-subtype-specific murine cre lines potentially confound data analysis and interpretation. To address this, we describe two tamoxifen-inducible cre-expressing lines, Vegfr3-creERT2 and Cx40-creERT2, that efficiently label sinusoidal/transitional and arteriole endothelium respectively in adult marrow, without off-target activity in hematopoietic or perivascular cells. Utilizing an established mouse model in which cre-dependent recombination constitutively-activates MAPK signaling within adult endothelium, we identify arteriole ECs as the driver of MAPK-mediated hematopoietic dysfunction. These results define complementary tamoxifen-inducible creERT2-expressing mouse lines that label functionally-discrete and non-overlapping sinusoidal/transitional and arteriole EC populations in the adult BM, providing a robust toolset to investigate the differential contributions of vascular subtypes in maintaining hematopoietic homeostasis.

Improving RGB illuminant estimation exploiting spectral average radiance.

We introduce a method that enhances RGB color constancy accuracy by combining neural network and k-means clustering techniques. Our approach stands out from previous works because we combine multispectral and color information together to estimate illuminants. Furthermore, we investigate the combination of the illuminant estimation in the RGB color and in the spectral domains, as a strategy to provide a refined estimation in the RGB color domain. Our investigation can be divided into three main points: (1) identify the spatial resolution for sampling the input image in terms of RGB color and spectral information that brings the highest performance; (2) determine whether it is more effective to predict the illuminant in the spectral or in the RGB color domain, and finally, (3) assuming that the illuminant is in fact predicted in the spectral domain, investigate if it is better to have a loss function defined in the RGB color or spectral domain. Experimental results are carried out on NUS: a standard dataset of multispectral radiance images with an annotated spectral global illuminant. Among the several considered options, the best results are obtained with a model trained to predict the illuminant in the spectral domain using an RGB color loss function. In terms of comparison with the state of the art, this solution improves the recovery angular error metric by 66% compared to the best tested spectral method, and by 41% compared to the best tested RGB method.

Raw Spectral Filter Array Imaging for Scene Recognition.

Scene recognition is the task of identifying the environment shown in an image. Spectral filter array cameras allow for fast capture of multispectral images. Scene recognition in multispectral images is usually performed after demosaicing the raw image. Along with adding latency, this makes the classification algorithm limited by the artifacts produced by the demosaicing process. This work explores scene recognition performed on raw spectral filter array images using convolutional neural networks. For this purpose, a new raw image dataset is collected for scene recognition with a spectral filter array camera. The classification is performed using a model constructed based on the pretrained Places-CNN. This model utilizes all nine channels of spectral information in the images. A label mapping scheme is also applied to classify the new dataset. Experiments are conducted with different pre-processing steps applied on the raw images and the results are compared. Higher-resolution images are found to perform better even if they contain mosaic patterns.

Compartmentalized ocular lymphatic system mediates eye-brain immunity.

The eye, an anatomical extension of the central nervous system (CNS), exhibits many molecular and cellular parallels to the brain. Emerging research demonstrates that changes in the brain are often reflected in the eye, particularly in the retina1. Still, the possibility of an immunological nexus between the posterior eye and the rest of the CNS tissues remains unexplored. Here, studying immune responses to herpes simplex virus in the brain, we observed that intravitreal immunization protects mice against intracranial viral challenge. This protection extended to bacteria and even tumours, allowing therapeutic immune responses against glioblastoma through intravitreal immunization. We further show that the anterior and posterior compartments of the eye have distinct lymphatic drainage systems, with the latter draining to the deep cervical lymph nodes through lymphatic vasculature in the optic nerve sheath. This posterior lymphatic drainage, like that of meningeal lymphatics, could be modulated by the lymphatic stimulator VEGFC. Conversely, we show that inhibition of lymphatic signalling on the optic nerve could overcome a major limitation in gene therapy by diminishing the immune response to adeno-associated virus and ensuring continued efficacy after multiple doses. These results reveal a shared lymphatic circuit able to mount a unified immune response between the posterior eye and the brain, highlighting an understudied immunological feature of the eye and opening up the potential for new therapeutic strategies in ocular and CNS diseases.

Filtered Lebedev quadrature method for robust and efficient beam shape coefficient estimation in acoustic tweezers calibration.

Acoustic tweezers offer a contactless, three-dimensional, and selective approach to trapping objects by harnessing the acoustic radiation force. Precise control of this technique requires accurate calibration of the force, which depends on the object's properties and the spherical harmonics expansion of the incident field through the beam shape coefficients. Previous studies showed that these coefficients can be determined using either the Lebedev quadrature or the angular spectrum methods. However, the former is highly susceptible to noise, while the latter demands extensive implementation time due to the number of required measurement points. A filtered method with a reduced number of points is introduced to address these limitations. Initially, we emphasize the implicit filtering in the angular spectrum method, allowing relative noise insensitivity. Subsequently, we present its unfiltered version, enabling force estimation of a standing field. Finally, we develop a filtered method based on the Lebedev quadrature, requiring fewer points, and apply it to focused vortex beams. Numerical evaluation of the radiation force demonstrates the method's resilience to noise and a reduced need for points compared to previous methods. The filtered Lebedev method paves the way for characterizing high-frequency acoustic tweezers, where measurement constraints necessitate rapid and robust beam shape coefficient estimation techniques.

Intrathecal delivery of nanoparticle PARP inhibitor to the cerebrospinal fluid for the treatment of metastatic medulloblastoma.

The morbidity associated with pediatric medulloblastoma, in particular in patients who develop leptomeningeal metastases, remains high in the absence of effective therapies. Administration of substances directly into the cerebrospinal fluid (CSF) is one approach to circumvent the blood-brain barrier and focus delivery of drugs to the site of tumor. However, high rates of CSF turnover prevent adequate drug accumulation and lead to rapid systemic clearance and toxicity. Here, we show that PLA-HPG nanoparticles, made with a single-emulsion, solvent evaporation process, can encapsulate talazoparib, a PARP inhibitor (BMN-673). These degradable polymer nanoparticles improve the therapeutic index when delivered intrathecally and lead to sustained drug retention in the tumor as measured with PET imaging and fluorescence microscopy. We demonstrate that administration of these particles into the CSF, alone or in combination with systemically administered temozolomide, is a highly effective therapy for tumor regression and prevention of leptomeningeal spread in xenograft mouse models of medulloblastoma. These results provide a rationale for harnessing nanoparticles for the delivery of drugs limited by brain penetration and therapeutic index and demonstrate important advantages in tolerability and efficacy for encapsulated drugs delivered locoregionally.

Life Cycle Assessment of a large commercial kelp farm in Shandong, China.

The environmental benefits of seaweed cultivation have gained a lot of attention, both in policy strategies and by private companies. Sustainability evaluations of seaweed farming have however focused on a very small part of global production of seaweed - on European cultivations at research and pilot-scales although Asia stands for 99 % of global production with China alone producing 60 %. In this study, we use Life Cycle Assessment (LCA) to evaluate the environmental performance of a 400-hectare Chinese kelp farm with a yearly harvest of 60,000 tons. Primary data from the farm was used to assess impacts up until harvest for the functional unit of 1 ton of fresh-weight kelp. Included in the LCA were impact on climate change, acidification terrestrial and marine eutrophication, and use of land water and energy. In addition, we calculated nutrient uptake. Further, we extracted inventory data of four published LCA studies of farmed kelp and recalculated environmental impacts, applying the same background data and method choices with the aim to compare the effects of scale and cultivation system. The results of the hotspot analysis showed that the plastic ropes and buoys dominated impacts on climate change, freshwater and marine eutrophication, and energy consumption. Consequently, the most effective improvement action was recycling after use. The yearly harvest of the Chinese farm was 1000-4000 times larger than previously evaluated farms compared. Results suggest that streamlined and mature production in the large-scale Chinese kelp farm led to lower electricity and fuel consumption compared to small-scale production, thus placing the Chinese farm with a climate impact of 57.5 kg CO2 eq. per ton fresh-weight kelp on the lower end when comparing the carbon footprint. There was a large variation in carbon footprints, which implies that the kelp cultivation sector has considerable room for optimization.

Elucidating the nature of the proton radioactivity and branching ratio on the first proton emitter discovered 53mCo.

The observation of a weak proton-emission branch in the decay of the 3174-keV 53mCo isomeric state marked the discovery of proton radioactivity in atomic nuclei in 1970. Here we show, based on the partial half-lives and the decay energies of the possible proton-emission branches, that the exceptionally high angular momentum barriers, [Formula: see text] and [Formula: see text], play a key role in hindering the proton radioactivity from 53mCo, making them very challenging to observe and calculate. Indeed, experiments had to wait decades for significant advances in accelerator facilities and multi-faceted state-of-the-art decay stations to gain full access to all observables. Combining data taken with the TASISpec decay station at the Accelerator Laboratory of the University of Jyväskylä, Finland, and the ACTAR TPC device on LISE3 at GANIL, France, we measured their branching ratios as bp1 = 1.3(1)% and bp2 = 0.025(4)%. These results were compared to cutting-edge shell-model and barrier penetration calculations. This description reproduces the order of magnitude of the branching ratios and partial half-lives, despite their very small spectroscopic factors.

Measuring the Optical Properties of Highly Diffuse Materials.

Measuring the optical properties of highly diffuse materials is a challenge as it could be related to the white colour or an oversaturation of pixels in the acquisition system. We used a spatially resolved method and adapted a nonlinear trust-region algorithm to the fit Farrell diffusion theory model. We established an inversion method to estimate two optical properties of a material through a single reflectance measurement: the absorption and the reduced scattering coefficient. We demonstrate the validity of our method by comparing results obtained on milk samples, with a good fitting and a retrieval of linear correlations with the fat content, given by R2 scores over 0.94 with low p-values. The values of absorption coefficients retrieved vary between 1 × 10-3 and 8 × 10-3 mm-1, whilst the values of the scattering coefficients obtained from our method are between 3 and 8 mm-1 depending on the percentage of fat in the milk sample, and under the assumption of the anisotropy factor g>0.8. We also measured and analyzed the results on white paint and paper, although the paper results were difficult to relate to indicators. Thus, the method designed works for highly diffuse isotropic materials.

VEGF-C promotes brain-derived fluid drainage, confers neuroprotection, and improves stroke outcomes.

Meningeal lymphatic vessels promote tissue clearance and immune surveillance in the central nervous system (CNS). Vascular endothelium growth factor-C (VEGF-C) is essential for meningeal lymphatic development and maintenance and has therapeutic potential for treating neurological disorders, including ischemic stroke. We have investigated the effects of VEGF-C overexpression on brain fluid drainage, single cell transcriptome in the brain, and stroke outcomes in adult mice. Intra-cerebrospinal fluid administration of an adeno-associated virus expressing VEGF-C (AAV-VEGF-C) increases the CNS lymphatic network. Post-contrast T1 mapping of the head and neck showed that deep cervical lymph node size and drainage of CNS-derived fluids were increased. Single nuclei RNA sequencing revealed a neuro-supportive role of VEGF-C via upregulation of calcium and brain-derived neurotrophic factor (BDNF) signaling pathways in brain cells. In a mouse model of ischemic stroke, AAV-VEGF-C pretreatment reduced stroke injury and ameliorated motor performances in the subacute stage. AAV-VEGF-C thus promotes CNS-derived fluid and solute drainage, confers neuroprotection, and reduces ischemic stroke damage. Short abstract: Intrathecal delivery of VEGF-C increases the lymphatic drainage of brain-derived fluids confers neuroprotection, and improves neurological outcomes after ischemic stroke.

Impact of Exposure and Illumination on Texture Classification Based on Raw Spectral Filter Array Images.

Spectral Filter Array cameras provide a fast and portable solution for spectral imaging. Texture classification from images captured with such a camera usually happens after a demosaicing process, which makes the classification performance rely on the quality of the demosaicing. This work investigates texture classification methods applied directly to the raw image. We trained a Convolutional Neural Network and compared its classification performance to the Local Binary Pattern method. The experiment is based on real SFA images of the objects of the HyTexiLa database and not on simulated data as are often used. We also investigate the role of integration time and illumination on the performance of the classification methods. The Convolutional Neural Network outperforms other texture classification methods even with a small amount of training data. Additionally, we demonstrated the model's ability to adapt and scale for different environmental conditions such as illumination and exposure compared to other methods. In order to explain these results, we analyze the extracted features of our method and show the ability of the model to recognize different shapes, patterns, and marks in different textures.

Three-dimensional imaging of vascular development in the mouse epididymis.

Long considered an accessory tubule of the male reproductive system, the epididymis is proving to be a key determinant of male fertility. In addition to its secretory role in ensuring functional maturation and survival of spermatozoa, the epididymis has a complex immune function. Indeed, it must manage both peripheral tolerance to sperm antigens foreign to the immune system and the protection of spermatozoa as well as the organ itself against pathogens ascending the epididymal tubule. Although our knowledge of the immunobiology of this organ is beginning to accumulate at the molecular and cellular levels, the organization of blood and lymphatic networks of this tissue, important players in the immune response, remains largely unknown. In the present report, we have taken advantage of a VEGFR3:YFP transgenic mouse model. Using high-resolution three-dimensional (3D) imaging and organ clearing coupled with multiplex immunodetections of lymphatic (LYVE1, PDPN, PROX1) and/or blood (PLVAP/Meca32) markers, we provide a simultaneous deep 3D view of the lymphatic and blood epididymal vasculature in the mature adult mouse as well as during postnatal development.

CCL21-CCR7 signaling promotes microglia/macrophage recruitment and chemotherapy resistance in glioblastoma.

Glioblastoma (GBM) is the most common and fatal primary tumor of the central nervous system (CNS) and current treatments have limited success. Chemokine signaling regulates both malignant cells and stromal cells of the tumor microenvironment (TME), constituting a potential therapeutic target against brain cancers. Here, we investigated the C-C chemokine receptor type 7 (CCR7) and the chemokine (C-C-motif) ligand 21 (CCL21) for their expression and function in human GBM and then assessed their therapeutic potential in preclinical mouse GBM models. In GBM patients, CCR7 expression positively associated with a poor survival. CCL21-CCR7 signaling was shown to regulate tumor cell migration and proliferation while also controlling tumor associated microglia/macrophage recruitment and VEGF-A production, thereby controlling vascular dysmorphia. Inhibition of CCL21-CCR7 signaling led to an increased sensitivity to temozolomide-induced tumor cell death. Collectively, our data indicate that drug targeting of CCL21-CCR7 signaling in tumor and TME cells is a therapeutic option against GBM.

Connexin 43-mediated neurovascular interactions regulate neurogenesis in the adult brain subventricular zone.

The subventricular zone (SVZ) is the largest neural stem cell (NSC) niche in the adult brain; herein, the blood-brain barrier is leaky, allowing direct interactions between NSCs and endothelial cells (ECs). Mechanisms by which direct NSC-EC interactions in the adult SVZ control NSC behavior are unclear. We found that Cx43 is highly expressed by SVZ NSCs and ECs, and its deletion in either leads to increased NSC proliferation and neuroblast generation, suggesting that Cx43-mediated NSC-EC interactions maintain NSC quiescence. This is further supported by single-cell RNA sequencing and in vitro studies showing that ECs control NSC proliferation by regulating expression of genes associated with NSC quiescence and/or activation in a Cx43-dependent manner. Cx43 mediates these effects in a channel-independent manner involving its cytoplasmic tail and ERK activation. Such insights inform adult NSC regulation and maintenance aimed at stem cell therapies for neurodegenerative disorders.