Seipin Deficiency as a Model of Severe Adipocyte Dysfunction: Lessons from Rodent Models and Teaching for Human Disease

Obesity prevalence is increasing worldwide, leading to cardiometabolic morbidities. Adipocyte dysfunction, impairing white adipose tissue (WAT) expandability and metabolic flexibility, is central in the development of obesity-related metabolic complications. Rare syndromes of lipodystrophy characterized by an extreme paucity of functional adipose tissue should be considered as primary adipocyte dysfunction diseases. Berardinelli-Seip congenital lipodystrophy (BSCL) is the most severe form with a near absence of WAT associated with cardiometabolic complications such as insulin resistance, liver steatosis, dyslipidemia, and cardiomyopathy. Twenty years ago, mutations in the BSCL2 gene have been identified as the cause of BSCL in human. BSCL2 encodes seipin, an endoplasmic reticulum (ER) anchored protein whose function was unknown back then. Studies of seipin knockout mice or rats demonstrated how seipin deficiency leads to severe lipodystrophy and to cardiometabolic complications. At the cellular levels, seipin is organized in multimers that are particularly enriched at ER/lipid droplet and ER/mitochondria contact sites. Seipin deficiency impairs both adipocyte differentiation and mature adipocyte maintenance. Experiments using adipose tissue transplantation in seipin knockout mice and tissue-specific deletion of seipin have provided a large body of evidence that liver steatosis, cardiomyopathy, and renal injury, classical diabetic complications, are all consequences of lipodystrophy. Rare adipocyte dysfunctions such as in BSCL are the key paradigm to unravel the pathways that control adipocyte homeostasis. The knowledge gathered through the study of these pathologies may bring new strategies to maintain and improve adipose tissue expandability.     

APOB CRISPR-Cas9 Engineering in Hypobetalipoproteinemia: A Promising Tool for Functional Studies of Novel Variants

Hypobetalipoproteinemia is characterized by LDL-cholesterol and apolipoprotein B (apoB) plasma levels below the fifth percentile for age and sex. Familial hypobetalipoproteinemia (FHBL) is mostly caused by premature termination codons in the APOB gene, a condition associated with fatty liver and steatohepatitis. Nevertheless, many families with a FHBL phenotype carry APOB missense variants of uncertain significance (VUS). We here aimed to develop a proof-of-principle experiment to assess the pathogenicity of VUS using the genome editing of human liver cells. We identified a novel heterozygous APOB-VUS (p.Leu351Arg), in a FHBL family. We generated APOB knock-out (KO) and APOB-p.Leu351Arg knock-in Huh7 cells using CRISPR-Cas9 technology and studied the APOB expression, synthesis and secretion by digital droplet PCR and ELISA quantification. The APOB expression was decreased by 70% in the heterozygous APOB-KO cells and almost abolished in the homozygous-KO cells, with a consistent decrease in apoB production and secretion. The APOB-p.Leu351Arg homozygous cells presented with a 40% decreased APOB expression and undetectable apoB levels in cellular extracts and supernatant. Thus, the p.Leu351Arg affected the apoB secretion, which led us to classify this new variant as likely pathogenic and to set up a hepatic follow-up in this family. Therefore, the functional assessment of APOB-missense variants, using gene-editing technologies, will lead to improvements in the molecular diagnosis of FHBL and the personalized follow-up of these patients.     

Effects of dietary supplements of zinc-methionine on milk production,udder health and zinc metabolism in dairy goats

Twenty-two Murciano-Granadina dairy goats were used to investigate the effects of organic Zn supplementation of a diet containing a high level of inorganic Zn. Goats were kept in pens, machine milked once a day throughout lactation and fed a diet based on a dehydrated mixture of whole-plant maize and alfalfa ad libitum, alfalfa pellets, barley grain and a concentrate mixture. Treatments were: (1) control, and (2) supplemented with 1 g/d Zn-Methionine (Zn-Met) included in the concentrate mixture. After parturition, goats were blocked in week 3 and dietary treatments were applied until week 23. From weeks 3-20, feed intake, milk yield, milk composition, milk somatic cell count (SCC), and udder health were measured. In week 21, all goats were injected intraperitoneally with 1 g/d DL-methionine for 5 d to establish the effects of methionine under the conditions of udder stress induced by hand milking on the second day. During weeks 22 and 23, diet digestibility, and N and Zn balance were determined. Dry matter intake, milk yield, and milk contents of total solids, fat, total and true protein, and casein did not differ between treatments, but whey protein and non-protein nitrogen contents were significantly lower for the Zn-Met group. Milk SCC tended to decrease as a result of Zn-Met supplementation but differences between treatments were not significant when halves with persistent infection were excluded. Hand milking increased SCC in both groups, but udders of supplemented goats showed a lower reaction. Apparent absorption of N significantly increased and Zn retention tended to increase in Zn-Met supplemented goats. We conclude that Zn-Met supplementation can enhance resistance to udder stress in dairy goats. Effects were attributed to the organic Zn and not to the methionine component. Zn retention and protein utilization were also improved by the Zn-Met supplement.     

Unsteady pressure measurements in a high-speed centrifugal compressor

This paper presents the unsteady data acquisition system used to measure the pressure field in high speed compressors. Details and electronic sketches are given for the conditioners developed in-house that have been used to amplify and to filter the pressure signal with the aim of acquiring data up to 150 kHz. A discussion of the experimental results carried out in a centrifugal compressor is proposed. Through different processing of the pressure signals and a comparison with URANS simulations, the excitation of the pressure transducers by the pressure waves generated by shock waves that occur between the impeller and the diffuser is highlighted. The levels of pressure fluctuations measured when entering into surge are also presented and reveal very repetitive behaviour of the flow instabilities.     

Influence of glass fiber content on the morphology and mechanical properties in injection molded polypropylene composites

Propropylene was reinforced with various concentrations of glass fiber (0, 10, 20, 28, and 35 percent by weight) and standard test samples were prepared by injection molding under identical conditions. The influence of fiber concentration on the morphology and mechanical properties was investigated using polarizing microscope, scanning electron microscope, Instron universal testing machine, etc. Tensile strength, tensile modulus, and flexural strength were found to increase with glass fiber content, while impact strength was reduced. These observed changes in mechanical properties were explained in terms of alterations in skin-core morphology, spherulite size, transcrystallinity, etc. The efficiency of reinforcement factor (K) was calculated for all the composites. It was found that K decreases with the increase of fiber concentration. This study attempts to correlate fiber concentration and polymer morphology with mechanical properties and the overall efficiency of reinforcement. This would help in optimizing the fiber content to prepare molded composites with desired mechanical properties.     

Thermodiffusion‐Assisted Pyroelectrics—Enabling Rapid and Stable Heat and Radiation Sensing

Sensors for monitoring temperature, heat flux, and thermal radiation are essential for applications such as electronic skin. While pyroelectric and thermoelectric effects are suitable candidates as functional elements in such devices, both concepts show individual drawbacks in terms of zero equilibrium signals for pyroelectric materials and small or slow response of thermoelectric materials. Here, these drawbacks are overcome by introducing the concept of thermodiffusion‐assisted pyroelectrics, which combines and enhances the performance of pyroelectric and ionic thermoelectric materials. The presented integrated concept provides both rapid initial response upon heating and stable synergistically enhanced signals upon prolonged exposure to heat stimuli. Likewise, incorporation of plasmonic metasurfaces enables the concept to provide both rapid and stable signals for radiation‐induced heating. The performance of the concept and its working mechanism can be explained by ion–electron interactions at the interface between the pyroelectric and ionic thermoelectric materials.     

Hierarchical Coherent Phonons in a Superatomic Semiconductor

The coupling of phonons to electrons and other phonons plays a defining role in material properties, such as charge and energy transport, light emission, and superconductivity. In atomic solids, phonons are delocalized over the 3D lattice, in contrast to molecular solids where localized vibrations dominate. Here, a hierarchical semiconductor that expands the phonon space by combining localized 0D modes with delocalized 2D and 3D modes is described. This material consists of superatomic building blocks (Re₆Se₈) covalently linked into 2D sheets that are stacked into a layered van der Waals lattice. Using transient reflectance spectroscopy, three types of coherent phonons are identified: localized 0D breathing modes of isolated superatom, 2D synchronized twisting of superatoms in layers, and 3D acoustic interlayer deformation. These phonons are coupled to the electronic degrees of freedom to varying extents. The presence of local phonon modes in an extended crystal opens the door to controlling material properties from hierarchical phonon engineering.     

Assessment of empirical algorithms for bathymetry extraction using Sentinel-2 data

Bathymetry estimated from optical satellite imagery has been increasingly implemented as an alternative to traditional bathymetric survey techniques. The availability of new sensors such as Sentinel-2 with improved spatial and temporal resolution, in comparison with previous optical sensors, offers innovative capabilities for bathymetry derivation. This study presents an assessment of the fit between satellite data and the underlying models in the most widely used empirical algorithms: the linear band model and the log-transformed band ratio model using Sentinel-2A data. Both models were tested in two study areas of the Irish coast with different morphological and environmental conditions. Results showed that the linear band model fitted better than the log-transformed band ratio model providing coefficient of determination values, R², between 0.83 and 0.88 (0 m–10 m) for the five images considered in the study. The closest fit was found in the depth range 2 m–6 m. Atmospheric correction, bottom type influence, and water column conditions proved to be key factors in the bathymetric derivation using these satellite datasets.     

Object-based fusion for urban tree species classification from hyperspectral,panchromatic and nDSM data

This study aims at identifying the best object-based fusion strategy that takes advantage of the complementarity of several heterogeneous airborne data sources for improving the classification of 15 tree species in an urban area (Toulouse, France). The airborne data sources are: hyperspectral Visible Near-Infrared (160 spectral bands, spatial resolution of 0.4 m) and Short-Wavelength Infrared (256 spectral bands, 1.6 m), panchromatic (14 cm), and a normalized Digital Surface Model (12.5 cm). Object-based feature and decision level fusion strategies are proposed and compared when applied to a reference site where the species are previously identified during ground truth collection. This allows the best fusion strategy to be selected with a view to introducing the method in an automatic process (tree crown delineation and species classification) on a test site, independent of the reference site used for learning. In particular, a decision level fusion is selected: based on the Support Vector Machine algorithm, Visible Near-Infrared and Short-Wavelength Infrared classifications use Minimum Noise Fraction components at the original spatial resolution, whereas panchromatic and normalized Digital Surface Model classifications use, respectively, Haralick’s and structural features computed at the object scale. After the computation of a decision profile for each source at the object level based on the classification algorithms’ membership probabilities, these decision profiles are combined and a decision rule is applied to predict the species. Focusing on the reference site, the Visible Near-Infrared exhibits the best performances with F-score values higher than 60% for 13 species out of 15. The Short-Wavelength Infrared is the most powerful for three species with F-score greater than 60% for seven common species with the Visible Near-Infrared. The panchromatic and normalized Digital Surface Model contribute marginally. The best fusion strategy (decision fusion) does not improve significantly the overall accuracy with 77% (kappa = 74%) against 75% (kappa = 72%) for the Visible Near-Infrared but in general, it improves the results for cases where complementarities have been observed. When applied to the test site and assessed for the two majority species (Tilia tomentosa and Platanus x hispanica), the selected approach gives consistent results with an overall accuracy of 63% against 55% for the Visible Near-Infrared.