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Abstract This article explores the possible presence of a pentacle valence bond structure in C 5 cyclic molecules. At this end, we have used quantum chemistry tools to elucidate the possible arrangement and the nature of chemical bonds within linear, cyclic, and three‐dimensional structures only formed by five carbon atoms. While the linear structure is clearly the most stable one, local minima were obtained for both bi‐ and three‐dimensional structures. Using the localization‐delocalization matrices approach, we characterize both the minimum linear structure and the cyclic ones. Interestingly, the linear structure is a combination of ionic and covalent bonds, albeit the four distances are almost identical, when using Density Functional Theory. For cyclic C 5 , the pentacle bonding arrangement emerges as a significant Lewis structure, indicative of an unusual formal configuration characterized by five intersecting C−C bonds. Our calculations show that this pentacle arrangement in cyclic C 5 scheme is also present in the more known cyclo‐pentadienyl molecule.

Considering the challenges related to hydrogen storage and transportation which hinder its widespread adoption, ammonia has emerged as a carbon-free carrier for hydrogen due to several advantages such as simple inexpensive storage. But, due to some limitations related to net ammonia combustion, the suggestion is to store hydrogen in the form of ammonia and convert it into hydrogen-rich fuel before utilization in different applications like engines and turbines. Therefore, in this article, a comprehensive thermodynamic analysis of hydrogen-rich fuel production via ammonia decomposition is conducted utilizing Aspen Plus V.12, to assess the impact of operating parameters on key criteria such as conversion rate (CR) and enthalpy of reaction, to establish the maximum level of efficiency of the process. The results show that at a specific temperature, the CR of ammonia decreases as the pressure rises so that the CR of more than 50% occurred at temperatures of 427 and 513 K for pressures of 1 and 10 bar, respectively. Moreover, the adiabatic flame temperature of hydrogen-rich fuel is investigated so that increasing the molar percentage of hydrogen from 0 to 50 leads to an increase in the maximum adiabatic flame temperature from 2,079 to 2,216 K.

Summary: Antibody-oligonucleotide conjugates (AOCs) are a fast-expanding modality for targeted delivery of therapeutic oligonucleotides to tissues. Here, we present a protocol to generate, purify, and analyze AOCs from off-the-shelf antibodies. We describe steps to conjugate single/double-stranded oligonucleotides bearing amine handles to linkers and, then, to antibodies using well-established chemistry. In addition, we provide details regarding the purification techniques and analytical methods suitable for AOC. This protocol can be applied for several purposes where AOC is a modality of interest.For complete details on the use and execution of this protocol, please refer to Rady et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Gallium-68-labeled FAPI-46 has recently been proposed as a novel positron emission tomography imaging probe to diagnose and monitor a wide variety of cancers. Promising results from several ongoing clinical trials have led to a soaring demand for this radiotracer. Typical [68Ga]Ga-FAPI-46 labeling protocols do not cope with multiple generator elutions, leaving radiopharmacies unable to scale-up the production and meet the demand. Here, we propose a robust and efficient automated radiosynthesis of [68Ga]Ga-FAPI-46 on the Trasis miniAllinOne synthesizer, featuring a prepurification step which allows multiple generator elutions and ensures compatibility with a wide range of gallium-68 generators. Our approach was to optimize the prepurification step by first testing five different cationic cartridge chemistries. Only the strong cationic exchange (SCX) cartridges tested had sufficient affinities for quantitative trapping of >99.9%, while the weak cationics did not exceed 50%. Packaging, rinsing, or flowing of the selected SCX cartridges was not noticeable, but improvements in fluidics managed to save time. Based on our previous development experience of [68Ga]Ga-FAPI-46, radiolabeling optimization was also carried out at different temperatures during 10 min. At temperatures above 100°C, radiochemical yield (RCY) > 80% was achieved without significantly increasing the chemical impurities (88%). A comparison with radiosyntheses carried out without prepurification steps was also conclusive in terms of RCY, radiochemical yield, and chemical purity. Finally, high-activity tests using elutions from three generators were also successful for these parameters. [68Ga]Ga-FAPI-46 was consistently obtained in good radiochemical yields (>89%, n = 3), and the final product quality was compliant with internal specifications based on European Pharmacopoeia. This process is suitable for GMP production and allows scaling-up of routine productions, higher throughput, and, ultimately, better patient care.

Many new methods for single atom skeletal editing of heterocycles have been developed in the past few years with obvious applications to discovery chemistry. In this perspective, we assess the recent advances in this field and the potential application to lead exploration campaigns.

The development of catalytic systems that selectively convert O2 to water is required to progress fuel cell technology. As an alternative to platinum catalysts, derivatives of iron and cobalt porphyrin molecular catalysts provide one benchmark for catalyst design. However, the inclusion of these catalysts into homogeneous platforms remains a difficulty. Co-porphyrins have been studied as heterogeneous O2 reduction catalysts; however, they have not been explored much in homogeneous systems. Moreover, they suffer from poor selectivity for the desired four-electron reduction of O2 to H2O. Herein, we present two cobalt-based β-fluorinated porphyrin complexes (CoTPF8(OH)2 and CoTPF8(OH)4) and demonstrate applicability as effective catalysts for the oxygen reduction reaction. Using rotating ring-disk electrochemistry, the catalysts, CoTPF8(OH)2 and CoTPF8(OH)4, showed maximum Faradaic efficiency for H2O of 92 % and 97 %, respectively. DFT calculations suggest that the formation of a phlorin intermediate could occur before O2 reduction and that a stronger H2O2 binding in the cobalt-based β-fluorinated porphyrin species compared to the unsubstituted parent compound, CoTP(OH)2, was responsible for the observed experimental selectivity for H2O. These results reveal that the β-fluorinated porphyrin catalyst serves as a novel platform for investigating molecular electrocatalytic reactions.

Abstract The topology of amorphous materials can be affected by mechanical forces during compression or milling, which can induce material densification. Here, we show that densified amorphous silica (SiO2) fabricated by cold compression of siliceous zeolite (SZ) is permanently densified, unlike densified glassy SiO2 (GS) fabricated by cold compression although the X-ray diffraction data and density of the former are identical to those of the latter. Moreover, the topology of the densified amorphous SiO2 fabricated from SZ retains that of crystalline SZ, whereas the densified GS relaxes to pristine GS after thermal annealing. These results indicate that it is possible to design new functional amorphous materials by tuning the topology of the initial zeolitic crystalline phases.

Recent developments in metallic additive manufacturing (AM) processes for the production of high-performance industrial pieces have been hampered by the limited availability of reliably processable or printable alloys. To date, most of the alloys used in AM are commercial grades that have been previously optimized for different manufacturing techniques. This study aims to design new alloys specifically tailored for AM processes, to minimize defects in the final products and to optimize their properties. A computational approach is proposed to design novel and optimized austenitic alloy compositions. This method integrates a suite of predictive tools, including machine learning, calculation of phase diagrams (CALPHAD) and physical models, all piloted by a multi-objective genetic algorithm. Within this framework, several material-dependent criteria are examined and their impact on properties and on the occurrence of defects is identified. To validate our approach, experimental tests are performed on a selected alloy composition: powder is produced by gas atomization and samples are fabricated by laser powder bed fusion. The microstructure and mechanical properties of the alloys are evaluated and its printability is compared with a commercial 316L stainless steel taken as a reference. The optimized alloy performs similarly to 316L in terms of coefficient of thermal expansion, hardness and elongation, but has a 17% lower yield strength and ultimate tensile strength (UTS), indicating that further optimization is required.

Different types of macrophages (Mφ) are involved in atherogenesis, including inflammatory Mφ and foamy Mφ (FM). Our previous study demonstrated that two-photon excited fluorescence (TPEF) imaging of NADH and FAD autofluorescence (AF) could distinguish experimental models that mimic the different atherosclerotic Mφ types. The present study assessed whether optical differences correlated with phenotypic and functional differences, potentially guiding diagnostic and therapeutic strategies. Phenotypic differences were investigated using three-dimensional principal component analysis and multi-color flow cytometry. Functional analyses focused on cytokine production, metabolic profiles, and cellular oxidative stress, in LDL dose-dependent assays, to understand the origin of AF in the FAD spectrum and assess FM ability to transition toward an immunoregulatory phenotype and function. Phenotypic studies revealed that FM models generated with acetylated LDL (Mac) were closer to immunoregulatory Mφ, while those generated with oxidized LDL (Mox) more closely resembled inflammatory Mφ. The metabolic analysis confirmed that inflammatory Mφ primarily used glycolysis, while immunoregulatory Mφ mainly depended on mitochondrial respiration. FM models employed both pathways; however, FM models generated with high doses of modified LDL showed reduced mitochondrial respiration, particularly Mox FM. Thus, the high AF in the FAD spectrum in Mox was not linked to increased mitochondrial respiration, but correlated with the dose of oxidized LDL, leading to increased production of reactive oxygen species (ROS) and lysosomal ceroid accumulation. High FAD-like AF, ROS, and ceroid accumulation were reduced by incubation with α-tocopherol. The cytokine profiles supported the phenotypic analysis, indicating that Mox FM exhibited greater inflammatory activity than Mac FM, although both could be redirected toward immunoregulatory functions, albeit to different degrees. In conclusion, in the context of immunoregulatory therapies for atherosclerosis, it is crucial to consider FM, given their prevalence in plaques and our results, as potential targets, regardless of their inflammatory status, alongside non-foamy inflammatory Mφ.

This paper introduces an evolutionary algorithm for objective functions defined over clouds of points of varying sizes. Such design variables are modeled as uniform discrete measures with finite support and the crossover and mutation operators of the algorithm are defined using the Wasserstein barycenter. We prove that the Wasserstein-based crossover has a contracting property in the sense that the support of the generated measure is included in the closed convex hull of the union of the two parents’ supports. We introduce boundary mutations to counteract this contraction. Variants of evolutionary operators based on Wasserstein barycenters are studied. We compare the resulting algorithm to a more classical, sequence-based, evolutionary algorithm on a family of test functions that include a wind-farm layout problem. The results show that Wasserstein-based evolutionary operators better capture the underlying geometrical structures of the considered test functions and outperform a reference evolutionary algorithm in the vast majority of the cases. The tests indicate that the mutation operators play a major part in the performances of the algorithms.

Abstract To reduce the costs of proton exchange membrane fuel cells, the amount of Pt necessary to drive efficient oxygen reduction reaction (ORR) should be minimized. Particle nanostructuring, (nano‐)alloying, and metal‐doping can yield higher activities per Pt mass through tailoring catalysts owning a high number of active sites and precise electronic properties. In this work, the atom‐precise [NBnMe3]2[Co8Pt4C2(CO)24] (Co8Pt4) cluster is encapsulated and activated in a zeolitic imidazolate framework (ZIF)‐8, which unlocks the access to defined, bare Pt−Co nanoclusters, Co8±xPt4±yNC@ZIF‐8, for the fabrication of highly active ORR catalysts. Upon controlled C‐interfacing and ZIF‐8‐digestion, Co‐doped Pt NPs (Pt27Co1) with a homogenous and narrow size distribution of (1.1±0.4) nm are produced on Vulcan® carbon. Restructuring of the Pt27Co1/C catalyst throughout the ORR measurement was monitored via high‐angle annular dark field‐scanning transmission electron microscopy and X‐ray photoelectron spectroscopy. The measured ORR mass activity of (0.42±0.07) A mgPt−1 and the specific activity of (0.67±0.06) mA cmECSA−2 compare favourably with the catalyst obtained by direct C‐interfacing the pristine Co8Pt4 cluster and with state‐of‐the‐art Pt/C reference catalysts. Our results demonstrate the potential of ZIF‐8‐mediated Pt−Co NP synthesis toward devising ORR catalysts with high Pt‐mass activity.

Insect biomass, rich in chitin and chitosan, is a sustainable and abundant resource with substantial promise for advancing green energy storage solutions. In this study, we explored cricket flour as a biomass candidate for carbon electrodes in electrochemical capacitors, aiming at creating a material with a high nitrogen content upon carbonization. The optimized material boasted a specific surface area exceeding 3300 m2/g, with most pores falling within the 0.5–2 nm diameter range. In a symmetrical Swagelok-type cell, this material delivered exceptional performance, yielding capacitances of 273.5 F/g, 200.2 F/g, and 161.6 F/g at 1 A/g in 6 M KOH, 1 M H2SO4, and 9.2 M NaClO4 electrolytes, respectively. Furthermore, it showcased a capacity retention of 89.6 % and 87.9 % over 5000 cycles in 1 M H2SO4 and 6 M KOH, respectively. The cricket-based electrochemical capacitor exhibited robust cycling stability, suggesting its suitability for prolonged use. The resulting device demonstrated remarkably high specific capacitance, positioning it as a promising candidate for energy storage applications.

Progress in laser-driven proton acceleration requires increasing the proton maximum energy and laser-to-proton conversion efficiency while reducing the divergence of the proton beam. However, achieving all these qualities simultaneously has proven challenging experimentally, with the increase in beam energy often coming at the cost of beam quality. Numerical simulations suggest that coupling multi-PW laser pulses with ultrathin foils could offer a route for such simultaneous improvement. Yet, experimental investigations have been limited by the scarcity of such lasers and the need for very stringent temporal contrast conditions to prevent premature target expansion before the pulse maximum. Here, combining the newly commissioned Apollon laser facility that delivers high-power ultrashort (∼24fs) pulses with a double plasma mirror scheme to enhance its temporal contrast, we demonstrate the generation of up to 35 MeV protons with only 5 J of laser energy. This approach also achieves improved laser-to-proton energy conversion efficiency, reduced beam divergence, and optimized spatial beam profile. Therefore, despite the laser energy losses induced by the plasma mirror, the proton beams produced by this method are enhanced on all accounts compared to those obtained under standard conditions. Particle-in-cell simulations reveal that this improvement mainly results from a better space–time synchronization of the maximum of the accelerating charge-separation field with the proton bunch.

Duchenne and Becker muscular dystrophies, caused by pathogenic variants in DMD, are the most common inherited neuromuscular conditions in childhood. These diseases follow an X-linked recessive inheritance pattern, and mainly males are affected. The most prevalent pathogenic variants in the DMD gene are copy number variants (CNVs), and most patients achieve their genetic diagnosis through Multiplex Ligation-dependent Probe Amplification (MLPA) or exome sequencing. Here, we investigated a female patient presenting with muscular dystrophy who remained genetically undiagnosed after MLPA and exome sequencing. RNA sequencing (RNAseq) from the patient’s muscle biopsy identified an 85% reduction in DMD expression compared to 116 muscle samples included in the cohort. A de novo balanced translocation between chromosome 17 and the X chromosome (t(X;17)(p21.1;q23.2)) disrupting the DMD and BCAS3 genes was identified through trio whole genome sequencing (WGS). The combined analysis of RNAseq and WGS played a crucial role in the detection and characterisation of the disease-causing variant in this patient, who had been undiagnosed for over two decades. This case illustrates the diagnostic odyssey of female DMD patients with complex structural variants that are not detected by current panel or exome sequencing analysis.

Previous research has predominantly focused on the biomechanical effects of anterior–posterior foot motion during running, with comparatively less attention given to medial–lateral foot motion and its impact on lower limb biomechanical characteristics. We recruited 18 healthy runners who wore five different types of running shoes: regular shoes (NS), those with a 6 mm and 9 mm medial–lateral height difference in the forefoot (M6, M9), and those with a 6 mm and 9 mm lateral–medial height difference (L6, L9). Biomechanical parameters of lower limb joints during the stance phase of running, including range of motion, peak angular velocity, peak moment, power, and work, were analyzed. We used paired-sample t-tests and one-dimensional statistical parametric mapping (SPM1D) to compare joint biomechanics between shoes with varying height differences and NS. Under the L6 condition, notable differences occurred in the hip and knee flexion–extension moments during landing and push-off, accompanied by a significant increase in ankle dorsiflexion work and a significant decrease in inversion–eversion work. In contrast, the M9 condition resulted in decreased hip flexion–extension peak moment, power, and work in the sagittal plane. These findings indicate that varying forefoot medial–lateral height differences in running shoes significantly impact lower limb joint dynamics during the stance phase, particularly the L6 condition, potentially reducing knee injury risk and aiding gait improvement for overpronators. The findings offer valuable insights for sports injury prevention and athletic footwear design. However, further research is needed to understand the underlying mechanisms and practical implications for sports injury prevention and performance enhancement.

Selenium is an essential trace element in our diet, crucial for the composition of human selenoproteins, which include 25 genes such as glutathione peroxidases and thioredoxin reductases. The regulation of the selenoproteome primarily hinges on the bioavailability of selenium, either from dietary sources or cell culture media. This selenium-dependent control follows a specific hierarchy, with “housekeeping” selenoproteins maintaining constant expression while “stress-regulated” counterparts respond to selenium level fluctuations. This study investigates the variability in fetal bovine serum (FBS) selenium concentrations among commercial batches and its effects on the expression of specific stress-related cellular selenoproteins. Despite the limitations of our study, which exclusively used HEK293 cells and focused on a subset of selenoproteins, our findings highlight the substantial impact of serum selenium levels on selenoprotein expression, particularly for GPX1 and GPX4. The luciferase reporter assay emerged as a sensitive and precise method for evaluating selenium levels in cell culture environments. While not exhaustive, this analysis provides valuable insights into selenium-mediated selenoprotein regulation, emphasizing the importance of serum composition in cellular responses and offering guidance for researchers in the selenoprotein field.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutations in the receptor-binding domain (RBD) of the spike protein induced the emergence of variants with increased contagion and can hinder vaccine efficiency. Hence, it is crucial to better understand the binding mechanisms of variant RBDs to human ACE2 and develop efficient methods to characterize this interaction. In this work, we present an approach that uses machine learning to analyze the molecular dynamics simulations of RBD variant trajectories bound to ACE2. Along with the binding free energy calculation, this method was used to characterize the major differences in ACE2-binding capacity of three SARS-CoV-2 RBD variants—namely the original Wuhan strain, Omicron BA.1, and the more recent Omicron BA.5 sublineages. Our analyses assessed the differences in binding free energy and shed light on how it affects the infectious rates of different variants. Furthermore, this approach successfully characterized key binding interactions and could be deployed as an efficient tool to predict different binding inhibitors to pave the way for new preventive and therapeutic strategies.

Abstract Fragment-based drug discovery is an established methodology for finding hit molecules that can be elaborated into lead compounds. However it is currently challenging to predict whether fragment hits that do not bind to an orthosteric site could be elaborated into allosteric modulators, as in these cases binding does not necessarily translate into a functional effect. We propose a workflow using Markov State Models (MSMs) with steered molecular dynamics (sMD) to assess the allosteric potential of known binders. sMD simulations are employed to sample protein conformational space inaccessible to routine equilibrium MD timescales. Protein conformations sampled by sMD provide starting points for seeded MD simulations, which are combined into MSMs. The methodology is demonstrated on a dataset of protein tyrosine phosphatase 1B ligands. Experimentally confirmed allosteric inhibitors are correctly classified as inhibitors, whereas the deconstructed analogues show reduced inhibitory activity. Analysis of the MSMs provide insights into preferred protein-ligand arrangements that correlate with functional outcomes. The present methodology may find applications for progressing fragments towards lead molecules in FBDD campaigns.

Abstract Engineered nanoparticles have emerged as new types of materials for a wide range of applications from therapeutics to energy. Still, fabricating nanomaterials presenting complex inner morphologies and shapes in a simple manner remains a great challenge. Herein, we report the template‐free one‐pot continuous gradient nanoprecipitation of different types of non‐compatible polymers to spontaneously form nanostructured particles. The continuous addition of antisolvent induces precipitation and (re)organization of polymer chains at the forming particle interface, ultimately and naturally developing complex inner morphologies and shapes while particle grows. This low‐energy‐cost bottom‐up assembly approach applies to various functional polymers, possibly embedded with metal nanoparticles, for continuous growth into well‐organized nanoparticles. UV crosslinking of the particles and core removal allows both confirming the building process and leading to hollow or multivoid nanomaterials.

Low-density dispersive liquid-liquid microextraction with a subsequent esterification step was proposed in this study for the determination of linoleic acid and stearic acid in sheep blood serum samples. The method developed aimed to quickly and efficiently extract and esterify both fatty acids with subsequent analysis by gas chromatography/flame ionization detection. The extraction method was optimized with Scheffé’s polynomial model for three-component mixtures. The method was validated according to the parameters established by Eurachem Guide (2014). The optimal extraction conditions for LD-DLLME were 1400 µL of dispersion medium (MgCl2 0.017%), 400 µL of extractor solvent (toluene) and 1200 µL of dispersion solvent (methanol). The method performance showed adequate selectivity, sensitivity and precision to be applied to real samples, with an average recovery of 98.54% for linoleic acid and 103.83% for stearic acid. LD-DLLME was superior to the traditional method of analysis, which has been used until now for the determination of fatty acids in blood serum samples from ruminants. The analysis of real samples showed that the developed method is efficient for monitoring these substances in ruminants.

Abstract Nanomechanical resonators are built into phones, as filters or accelerometers, but they lack a knob to effectively tune the frequency at the nanoscale when it’s easy to tune on an octave the tone of a classical musical instrument like a guitar string. Moreover, the control of deformation in nanomaterials, as two-dimensional (2D) materials, to tailor their electronic properties, i.e., straintronic, opens up avenues for applications in force detection, bolometry or quantum emitters. An accurate control of the deformation within these materials is thus necessary to fully exploit their potential. The precise study of deformations in 2D materials involves measurements of vibration modes and nanomechanics. By using a suspended MoS2 membrane heated by the Joule effect, we induce a strong softening of the mechanical resonance frequency as a function of the electrothermal heating, over one octave. A simple electrical tension is used to modulate the thermal mechanical tuning. Its amplitude is very large, greater than 100% modulation for one volt, compared to other approaches on 2D or 1D materials and, moreover, a very wide frequency range is accessible. Finally, we have related a photo-induced softening of the membrane over very long times with the current measurements and a photothermal effect.

The pyoverdine siderophore is produced by Pseudomonas aeruginosa to access iron. Its synthesis involves the complex coordination of four nonribosomal peptide synthetases (NRPSs), which are responsible for assembling the pyoverdine peptide backbone. The precise cellular organization of these NRPSs and their mechanisms of interaction remain unclear. Here, we used a combination of several single-molecule microscopy techniques to elucidate the spatial arrangement of NRPSs within pyoverdine-producing cells. Our findings reveal that PvdL differs from the three other NRPSs in terms of localization and mobility patterns. PvdL is predominantly located in the inner membrane, while the others also explore the cytoplasmic compartment. Leveraging the power of multicolor single-molecule localization, we further reveal co-localization between PvdL and the other NRPSs, suggesting a pivotal role for PvdL in orchestrating the intricate biosynthetic pathway. Our observations strongly indicates that PvdL serves as a central orchestrator in the assembly of NRPSs involved in pyoverdine biosynthesis, assuming a critical regulatory function.

Dysregulation of cyclin-dependent kinase 8 (CDK8) activity has been associated with many diseases, including colorectal and breast cancer. As usual in the CDK family, the activity of CDK8 is controlled by a regulatory protein called cyclin C (CycC). But, while human CDK family members are generally activated in two steps, that is, the binding of the cyclin to CDK and the phosphorylation of a residue in the CDK activation loop, CDK8 does not require the phosphorylation step to be active. Another peculiarity of CDK8 is its ability to be associated with CycC while adopting an inactive form. These specificities raise the question of the role of CycC in the complex CDK8–CycC, which appears to be more complex than the other members of the CDK family. Through molecular dynamics (MD) simulations and binding free energy calculations, we investigated the effect of CycC on the structure and dynamics of CDK8. In a second step, we particularly focused our investigation on the structural and molecular basis of the protein–protein interaction between the two partners by finely analyzing the energetic contribution of residues and simulating the transition between the active and the inactive form. We found that CycC has a stabilizing effect on CDK8, and we identified specific interaction hotspots within its interaction surface compared to other human CDK/Cyc pairs. Targeting these specific interaction hotspots could be a promising approach in terms of specificity to effectively disrupt the interaction between CDK8. The simulation of the conformational transition from the inactive to the active form of CDK8 suggests that the residue Glu99 of CycC is involved in the orientation of three conserved arginines of CDK8. Thus, this residue may assume the role of the missing phosphorylation step in the activation mechanism of CDK8. In a more general view, these results point to the importance of keeping the CycC in computational studies when studying the human CDK8 protein in both the active and the inactive form.

Sputtering of silicon in a He magnetron discharge (MS) has been reported as a bottom-up procedure to obtain He-charged silicon films (i.e., He nanobubbles encapsulated in a silicon matrix). The incorporation of heavier noble gases is demonstrated in this work with a synergistic effect, producing increased Ne and Ar incorporations when using He–Ne and He–Ar gas mixtures in the MS process. Microstructural and chemical characterizations are reported using ion beam analysis (IBA) and scanning and transmission electron microscopies (SEM and TEM). In addition to gas incorporation, He promotes the formation of larger nanobubbles. In the case of Ne, high-resolution X-ray photoelectron and absorption spectroscopies (XPS and XAS) are reported, with remarkable dependence of the Ne 1s photoemission and the Ne K-edge absorption on the nanobubble’s size and composition. The gas (He, Ne and Ar)-charged thin films are proposed as “solid” targets for the characterization of spectroscopic properties of noble gases in a confined state without the need for cryogenics or high-pressure anvils devices. Also, their use as targets for nuclear reaction studies is foreseen.

We present TimberTool (TTool v2.1.1), a software designed for woodworking tasks assisted by augmented reality (AR), emphasizing its essential function of the real-time localization of a tool head’s poses within camera frames. The localization process, a fundamental aspect of AR-assisted tool operations, enables informed integration with contextual tracking, facilitating the computation of meaningful feedback for guiding users during tasks on the target object. In the context of timber construction, where object pose tracking has been predominantly explored in additive processes, TTool addresses a noticeable gap by focusing on subtractive tasks with manual tools. The proposed methodology utilizes a machine learning (ML) classifier to detect tool heads, offering users the capability to input a global pose and utilizing an automatic pose refiner for final pose detection and model alignment. Notably, TTool boasts adaptability through a customizable platform tailored to specific tool sets, and its open accessibility encourages widespread utilization. To assess the effectiveness of TTool in AR-assisted woodworking, we conducted a preliminary experimental campaign using a set of tools commonly employed in timber carpentry. The findings suggest that TTool can effectively contribute to AR-assisted woodworking tasks by detecting the six-degrees-of-freedom (6DoF) pose of tool heads to a satisfactory level, with a millimetric positional error of 3.9 ± 1 mm with possible large room for improvement and 1.19 ± 0.6° for what concerns the angular accuracy.

The functionalization of bone substitutes with exosomes appears to be a promising technique to enhance bone tissue formation. This study investigates the potential of exosomes derived from bone marrow mesenchymal stromal cells (BMSCs) to improve bone healing and bone augmentation when incorporated into wide open-porous 3D-printed ceramic Gyroid scaffolds. We demonstrated the multipotent characteristics of BMSCs and characterized the extracted exosomes using nanoparticle tracking analysis and proteomic profiling. Through cell culture experimentation, we demonstrated that BMSC-derived exosomes possess the ability to attract cells and significantly facilitate their differentiation into the osteogenic lineage. Furthermore, we observed that scaffold architecture influences exosome release kinetics, with Gyroid scaffolds exhibiting slower release rates compared to Lattice scaffolds. Nevertheless, in vivo implantation did not show increased bone ingrowth in scaffolds loaded with exosomes, suggesting that the scaffold microarchitecture and material were already optimized for osteoconduction and bone augmentation. These findings highlight the lack of understanding about the optimal delivery of exosomes for osteoconduction and bone augmentation by advanced ceramic scaffolds.

Interaction with the environment appears necessary for the maturation of sensorimotor and cognitive functions in early life. In rats, a model of sensorimotor restriction (SMR) from postnatal day 1 (P1) to P28 has shown that low and atypical sensorimotor activities induced the perturbation of motor behavior due to muscle weakness and the functional disorganization of the primary somatosensory and motor cortices. In the present study, our objective was to understand how SMR affects the muscle–brain dialogue. We focused on irisin, a myokine secreted by skeletal muscles in response to exercise. FNDC5/irisin expression was determined in hindlimb muscles and brain structures by Western blotting, and irisin expression in blood and cerebrospinal fluid was determined using an ELISA assay at P8, P15, P21 and P28. Since irisin is known to regulate its expression, Brain-Derived Neurotrophic Factor (BDNF) levels were also measured in the same brain structures. We demonstrated that SMR increases FNDC5/irisin levels specifically in the soleus muscle (from P21) and also affects this protein expression in several brain structures (as early as P15). The BDNF level was increased in the hippocampus at P8. To conclude, SMR affects FNDC5/irisin levels in a postural muscle and in several brain regions and has limited effects on BDNF expression in the brain.

Graphics Processing Units (GPUs) are employed for their parallel processing capabilities, which are essential to train deep learning (DL) models with large datasets within a reasonable time. However, the diverse GPU architectures exhibit variability in training performance depending on DL models. Furthermore, factors such as the number of GPUs for distributed training and batch size significantly impact training efficiency. Addressing the variability in training performance and accounting for these influential factors are critical for optimising resource usage. This paper presents a scheduling policy for DL training tasks in a heterogeneous GPU cluster. It builds upon a model-similarity-based scheduling policy by implementing a round-based mechanism and job packing. The round-based mechanism allows the scheduler to adjust its scheduling decisions periodically, whereas job packing optimises GPU utilisation by fitting additional jobs into a GPU that trains a small model. Results show that implementing a round-based mechanism reduces the makespan by approximately 29%, compared to the scenario without it. Additionally, integrating job packing further decreases the makespan by 5%.

Background: The application of isotopes of metals in medical science (isotope metallomics) has shown significant growth in the last few years, specifically with respect to the study of metal cycles in the body and/or their use as diagnostic tools for diseases that affect metal homeostasis. Given the great potential for Ca stable isotopes to identify changes in Ca metabolism and bone metabolism, there have been major applications of Ca metallomics—and isotope metallomics. However, reliable and high precision Ca isotopic analysis is challenging considering the limited Ca amounts in some soft tissues compared to e.g., bones and the related interference effect during measurement. Furthermore, there is a lack of Ca isotopic data in widely available biological reference materials with various matrices. Method: The development of collision-cell multi-collection inductively-coupled-plasma mass-spectrometers (CC-MC-ICP-MS), such as the Nu Instrument Sapphire, has revolutionized Ca isotope analysis, improving the sensitivity by over a factor 10 compared to older generation instruments, and more readily overcoming isobaric interferences. In this study, we report the first set of high precision Ca isotopic data for several widely available biological reference materials, spanning both land and sea animals, as well as various bodily organs (muscle, kidney, liver). Result: Results indicate that animals are globally enriched in the lighter isotopes compared to their living environment, and that Ca isotopes are fractionated by more than 1.5 ‰ between organs (e.g., in bovine), further highlighting that Ca isotopes could be used to study Ca cycles within the body. Conclusion: These new data—and reference materials—could be used for future interlaboratory comparisons.

This work is focused on the application of Cu-containing zeolites as potential environmental sensors for monitoring carbon monoxide. A number of commercial zeolites with different structural properties (NaX, NaY, MOR, FER, BEA and ZSM-5) were modified using CuSO4, Cu(NO3)2 and Cu(OAc)2 solutions as copper sources to prepare Cu+-containing zeolites, since Cu+ forms stable complexes with CO at room temperature that can be monitored by infrared spectroscopy. Zeolite impregnation with Cu(NO3)2 resulted in the highest total Cu-loadings, while the Cu(OAc)2-treated samples had the highest Cu+/Cutotal ratio. Cu(NO3)2-impregnated MOR, which displayed the highest concentration of Cu+, was subjected to a number of tests to evaluate its performance as a potential CO sensor. The working temperature and concentration ranges of the sensor were determined to be from 20 to 300 °C and from 10 to 10,000 ppm, respectively. The stepwise CO desorption experiments indicated that the sensor can be regenerated at 400 °C if required. Additional analyses under realistic flow conditions demonstrated that for hydrophilic zeolites, the co-adsorption of water can compromise the sensor’s performance. Therefore, a hydrophobic Sn-BEA was utilised as a parent material for the preparation of an impregnated Cu-Sn-BEA zeolite, which exhibited superior resistance to interfering water while maintaining its sensing properties. Overall, the prepared Cu-modified zeolites showed promising potential as environmental CO sensors, displaying high sensitivity and selectivity under representative testing conditions.

Environmental monitoring of pollutants, such as NOx and COx, which can be facilitated by a range of gas sensors, is of considerable fundamental and practical importance. This work has been focused on the synthesis and evaluation of zeolite β with tin (Sn-BEA) and dealuminated β (DeAl-BEA) zeolites. The zeolite samples have been extensively investigated by IR, UV-VIS and NMR spectroscopy, XRD, TGA, and N2 adsorption-desorption. The prepared Sn-BEA sample is characterised by the submicron particle size, an almost defect-free structure, and high hydrophobicity. Sensors containing selective microporous layers based on Sn-BEA and DeAl-BEA zeolites have been prepared and extensively tested. Both the Sn-BEA and DeAl-BEA zeolites have been deposited in thin films and evaluated as gas sensors for CO, CO2, NO, and NO2 in the presence of water vapour at room temperature. The Sn-BEA zeolite-based sensor showed high selectivity towards NO2, while the DeAl-BEA is selective towards CO2 and NO2.

The development of an integrated theory of subsurface drainage based on hydrology and hydrogeology concepts is presented. The historical context, the main hypothesis derived from the Boussinesq equation and the validation of the model predictions are discussed. Theoretical developments of this equation demonstrate that a single parameter ($\sigma $)—a combination of soil and drainage system properties—is sufficient for predicting the dynamics of subsurface drain flow rates. We also demonstrate that these drain flow rates are a function of the level of water replenishment in the system (classically the water table elevation), of the recharge intensity of the aquifer and of a buffer function related to the swelling or deflation of the water table shape during recharge events. For values of $\sigma >1$, the buffer role of the water table is negligible. In that case approx. 13% of the water table recharge contributes to the flow rate, which is shown to explain the observed disconnection between water table elevations and peak flow rates at the outlet of classic agricultural drainage systems and to predict these peak flow rates accurately. A modelling approach based on this theory and validated experimentally (SIDRA model) allowed us to test the quality of the peak flow prediction. The SIDRA model also includes a surface runoff module and has been coupled to different modelling tools and used to analyse the impacts of subsurface drainage on water quality. The approach contributed towards the development of tools that helped to connect better the drainage systems to the hydrological functioning of watersheds.

Benzothioxanthene imide (BTI) has recently emerged as an interesting and promising block for organic electronics. In this contribution, we report on the impact of the N-annulation of the latter dye on the optoelectronic of π-extended molecular structures. To do so, the thiophene-diketopyrrolopyrrole was selected, as central π-conjugated core, and either end-capped with two BTIs or its N-annulated version, namely the TCI. While almost similar band gaps were measured for individual rylene imide dyes, significant differences were highlighted, and rationalized, on their π-extended counterparts.

Geophysical and geological data from the North Mozambique Channel acquired during the 2020–2021 SISMAORE oceanographic cruise reveal a corridor of recent volcanic and tectonic features 200 km wide and 600 km long within and north of Comoros Archipelago. Here we identify and describe two major submarine tectono-volcanic fields: the N’Droundé province oriented N160°E north of Grande-Comore Island, and the Mwezi province oriented N130°E north of Anjouan and Mayotte Islands. The presence of popping basaltic rocks sampled in the Mwezi province suggests post-Pleistocene volcanic activity. The geometry and distribution of recent structures observed on the seafloor are consistent with a current regional dextral transtensional context. Their orientations change progressively from west to east (${\sim }$N160°E, ${\sim }$N130°E, ${\sim }$EW). The volcanism in the western part appears to be influenced by the pre-existing structural fabric of the Mesozoic crust. The 200 km-wide and 600 km-long tectono-volcanic corridor underlines the incipient Somalia–Lwandle dextral lithospheric plate boundary between the East-African Rift System and Madagascar.

Groundwater flow depends on subsurface heterogeneity, which often calls for categorical fields to represent different geological facies. The knowledge about subsurface is however limited and often provided indirectly by state variables, such as hydraulic heads of contaminant concentrations. In such cases, solving a categorical inverse problem is an important step in subsurface modeling. In this work, we present and compare three recent inverse frameworks: Posterior Population Expansion (PoPEx), Ensemble Smoother with Multiple Data Assimilation (ESMDA), and DREAM-ZS (a Markov chain Monte Carlo sampler). PoPEx and ESDMA are used with Multiple-point statistics (MPS) as geostatistical engines, and DREAM-ZS is used with a Wasserstein generative adversarial network (WGAN). The three inversion methods are tested on a synthetic example of a pumping test in a fluvial channelized aquifer. Moreover, the inverse problem is solved three times with each method, each time using a different training image to check the performance of the methods with different geological priors. To assess the quality of the results, we propose a framework based on continuous ranked probability score (CRPS), which compares single true values with predictive distributions. All methods performed well when using the training image used to create the reference, but their performances were degraded with the alternative training images. PoPEx produced the least geological artifacts but presented a rather slow convergence. ESMDA showed initially a very fast convergence which reaches a plateau, contrary to the remaining methods. DREAM-ZS was overly confident in placing some incorrect geological features but outperformed the other methods in terms of convergence.

In nonribosomal peptide synthesis, condensation (C) domains are key catalytic domains that most commonly link carrier protein bound substrates to form peptides or depsipeptides. While adenylation domains have been well characterized due to their role in the selection of monomers and hence as gate keepers in nonribosomal peptide biosynthesis, C-domains have been the subject of debate as they do not have apparent “A-domain like” side chain selectivity for their acceptor substrates. To probe the selectivity and specificity of C-domains, here we report our biochemical and structural characterization of the C3-domain from the biosynthesis of the siderophore fusachelin. Our results show that this C-domain is not broadly flexible for monomers bearing significantly alternated side chains or backbones, which suggests there can be a need to consider C-domain specificity for acceptor substrates when undertaking NRPS engineering.

Carbon nanostructures formed through physical synthesis come in a variety of sizes and shapes. With the end goal of rationalizing synthetic pathways of carbon nanostructures as a function of tunable parameters in the synthesis, we investigate how the initial density and quench rate influence the morphology of carbon nanostructures obtained from the cooling of a gas of atomic carbon by molecular dynamics simulations. For the structural analysis, we combine classical order parameters with a data-driven approach based on local density descriptors and kernel similarity measurements. Aided by this complementary set of tools, we describe in detail the formation of carbon nanostructures from the gas phase. Their formation proceeds through the nucleation of small liquid carbon nanoclusters followed by growth into unique objects. We find that ordered structures can only be obtained at certain quenching rates and that among those, fullerene-like particles are favored at intermediate densities while nanotubes-like structures require higher initial densities. © XXXX CEA. Elsevier

Ocular malformations (OMs) arise from early defects during embryonic eye development. Despite the identification of over 100 genes linked to this heterogeneous group of disorders, the genetic cause remains unknown for half of the individuals following Whole-Exome Sequencing. Diagnosis procedures are further hampered by the difficulty of studying samples from clinically relevant tissue, which is one of the main obstacles in OMs. Whole-Genome Sequencing (WGS) to screen for non-coding regions and structural variants may unveil new diagnoses for OM individuals. In this study, we report a patient exhibiting a syndromic OM with a de novo 3.15 Mb inversion in the 6p25 region identified by WGS. This balanced structural variant was located 100 kb away from the FOXC1 gene, previously associated with ocular defects in the literature. We hypothesized that the inversion disrupts the topologically associating domain of FOXC1 and impairs the expression of the gene. Using a new type of samples to study transcripts, we were able to show that the patient presented monoallelic expression of FOXC1 in conjunctival cells, consistent with the abolition of the expression of the inverted allele. This report underscores the importance of investigating structural variants, even in non-coding regions, in individuals affected by ocular malformations.

Magnetic Particle Inspection (MPI) is one of the most used methods in Non-Destructive Testing (NDT), allowing precise and robust defect detection on industrial-grade manufactured parts. However, human controllers perform this task in full black environments under UV-A lighting only (with safety glasses) and use chemical products in a confined environment. Those constraints tends to lower control performance and increase stress and fatigue. As a solution, we propose an AI-based assistive machine (called “PARADES”) inside the hazardous environment, remotely manipulated by a human operator, outside of the confined area, in cleaner and safer conditions. This paper focuses on the development of a complete industrial-grade AI machine, both in terms of hardware and software. The result is a standalone assistive AI-based vision system, plug-and-play and controller-friendly, which only needs the usual power supply 230 V plug that detects defects and measures defect length. In conclusion, the PARADES machines address for the first time the problem of occupational health in MPI with an industrial standalone machine which can work on several parts and be integrated into current production lines. Providing cleaner and healthier working conditions for operators will invariably lead to increased quality of detection. These results suggest that it would be beneficial to spread this kind of AI-based assistive technology in NDT, in particular MPI, but also in Fluorescent Penetrant Testing (FPT) or in visual inspection.

A cell’s ability to secrete extracellular vesicles (EVs) for communication is present in all three domains of life. Notably, Gram-negative bacteria produce a specific type of EVs called outer membrane vesicles (OMVs). We previously observed the presence of OMVs in human blood, which could represent a means of communication from the microbiota to the host. Here, in order to investigate the possible translocation of OMVs from the intestine to other organs, the mouse was used as an animal model after OMVs administration. To achieve this, we first optimized the signal of OMVs containing the fluorescent protein miRFP713 associated with the outer membrane anchoring peptide OmpA by adding biliverdin, a fluorescence cofactor, to the cultures. The miRFP713-expressing OMVs produced in E. coli REL606 strain were then characterized according to their diameter and protein composition. Native- and miRFP713-expressing OMVs were found to produce homogenous populations of vesicles. Finally, in vivo and ex vivo fluorescence imaging was used to monitor the distribution of miRFP713-OMVs in mice in various organs whether by intravenous injection or oral gavage. The relative stability of the fluorescence signals up to 3 days post-injection/gavage paves the way to future studies investigating the OMV-based communication established between the different microbiotas and their host.

Physical exercise (EX) is well established for its positive impact on brain health. However, conventional EX may not be feasible for certain individuals. In this regard, this study explores electromyostimulation (EMS) as a potential alternative for enhancing cognitive function. Conducted on both human participants and rats, the study involved two sessions of EMS applied to the quadriceps with a duration of 30 min at one-week intervals. The human subjects experienced assessments of cognition and mood, while the rats underwent histological and biochemical analyses on the prefrontal cortex, hippocampus, and quadriceps. Our findings indicated that EMS enhanced executive functions and reduced anxiety in humans. In parallel, our results from the animal studies revealed an elevation in brain-derived neurotrophic factor (BDNF), specifically in the hippocampus. Intriguingly, this increase was not associated with heightened neuronal activity or cerebral hemodynamics; instead, our data point towards a humoral interaction from muscle to brain. While no evidence of increased muscle and circulating BDNF or FNDC5/irisin pathways could be found, our data highlight lactate as a bridging signaling molecule of the muscle–brain crosstalk following EMS. In conclusion, our results suggest that EMS could be an effective alternative to conventional EX for enhancing both brain health and cognitive function.

Soft back exoskeletons are aimed at reducing musculoskeletal effort during manual handling tasks, contributing to the prevention of low back disorders like lumbar strains and sprains or intervertebral disk problems. However, large differences in their biomechanical effects are observed in the literature. A possible explanation could be the lack or disparity of familiarization protocols with the exoskeleton. The aim of this experimental study was to characterize the familiarization process with a soft back-support occupational exoskeleton and determine the time needed to stabilize biomechanical variables. Participants carried out 6 familiarization sessions of 1 h to the CORFOR® soft back-exoskeleton. Joint kinematics, postural stability, exoskeleton pressure perception, muscle activity, and performance were measured at the beginning of the first session and at the end of each session during stoop and squat liftings. Results showed that back kinematics, performance, and exoskeleton pressure perception changed during the first sessions and stabilized after sessions 3 or 4, depending on the variable. The authors recommend a familiarization protocol for the CORFOR® soft back-exoskeleton of 4 sessions of 1 h duration. This recommendation could help CORFOR® users, for instance, in the automotive industry, the food retail industry, or the agriculture field.