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All viruses on Earth rely on host cell machinery for replication, a process that involves a complex self-assembly mechanism. Our aim here is to scrutinize in real time the growth of icosahedral viral nucleocapsids with single-molecule precision. Using total internal reflection fluorescence microscopy, we probed the binding and unbinding dynamics of fluorescently labeled capsid subunits on hundreds of immobilized viral RNA molecules simultaneously at each time point. A step-detection algorithm combined with statistical analysis allowed us to estimate microscopic quantities such as the equilibrium binding rate and mean residence time, which are otherwise inaccessible through traditional ensemble-averaging techniques. Additionally, we could estimate a set of rate constants modeling the growth kinetics from nonequilibrium measurements, and we observed an acceleration in growth caused by the electrostatic screening effect of monovalent salts. Single-molecule fluorescence imaging will be crucial for elucidating virus self-assembly at the molecular level, particularly in crowded, cell-like environments.

Bacterial infections are common in cirrhosis patients, increasing the risk of decompensation and death. The impact of HLA evolutionary divergence (HED) on infection risk hasn't been studied in humans before. We conducted a retrospective study on cirrhosis patients awaiting liver transplantation (LT) from January 2019 to February 2022, examining class I and II-HED effects on bacterial infections and cirrhosis decompensation. We included 269 cirrhosis patients. Among them, 98 experienced 153 bacterial infections. Multivariable analysis after variable selection revealed that higher class II-HED was linked to fewer bacterial infections (p = 0.034), while class I-HED showed no effect (p = 0.074). Independent risk factors for bacterial infections included invasive procedures (p < 0.001), ICU hospitalization (p < 0.001), recent antibiotic treatment (p = 0.046), rifaximin use (p = 0.043), and cirrhosis decompensation (p = 0.002). Neither class I nor II-HED affected decompensation risk. This pioneering study shows that high class II-HED levels may protect against bacterial infections in cirrhosis patients awaiting LT, suggesting an immunological mechanism at play., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier Inc.)

TiO 2 nanotubes (NTs) obtained via electrochemical anodization (EA) on conventionally machined titanium surfaces are reported to be promising for achieving mucointegration in dental implant therapy. Dental abutments, manufactured by selective laser melting (SLM), combined with thermal post-treatment, present a promising alternative to conventionally machined titanium. Based on an original protocol, this study aims to investigate how the characteristic microstructure of the α + β phases in post-heated SLM Ti6Al4V can influence the growth of NTs and the resulting physical and chemical surface properties. Ti6Al4V-SLM discs were fabricated, heat post-treated and mechanically polished. The samples were then subjected to EA under different voltage conditions (10, 20 and 30 V). The specimens' surfaces were characterized at the same location, before NTs formation by electron backscatter diffraction (EBSD), and after by scanning electron microscopy (SEM). Then, roughness and wettability were studied to determine how EA affects surface properties compared to conventionally machined and polished titanium surfaces without NTs (reference). Surface reactivity was evaluated through chemical analysis and collagen binding capacities. The self-organized TiO 2 layer was developed on the α phase only and the β phase was preferentially dissolved. The characteristic dimensions of the nanotubes (diameter, length and wall thickness), measured by SEM image analysis, increased proportionally with the rise in voltage but were not affected by the crystallographic orientation of the underlying α grain. Micro-roughness was the same for nanotubular and reference surfaces. Wettability was improved, as was surface reactivity towards collagen, which may contribute to improved bioactivity of titanium surfaces in dentistry.

Background: Identifying risk factors contributing the most to mortality of childhood cancer survivors is essential to guide harm reduction efforts in childhood cancer treatments, and long-term follow-up of childhood cancer survivors., Methods: We assessed Life Years Lost from childhood cancer treatments and their health-related late effects among the French Childhood Cancer Survivors Study, a cohort of 7670 5-year childhood cancer survivors. Using a landmark strategy, we also assessed time-varying effects of risk factors, and how the multi-morbidity affects life years lost., Results: We found subsequent malignant neoplasm (9.0 years [95 %CI: 4.3-13.7]), severe cardiac disease (8.0 years [95 %CI: 1.2-14.9]), and the use of radiotherapy (6.0 years [95 %CI: 4.7-7.3]) to be the highest contributors to Life Years Lost among childhood cancer survivors. We found no interaction impact on life years lost between health related late effects considered., Conclusions: Those findings suggest that radiotherapy is the root cause of early mortality among childhood cancer survivors. Moreover patients experiencing a subsequent malignant neoplasm or a cardiac disease should be monitored closely after the event, as comorbidity is common and causes premature deaths., Competing Interests: Declaration of Competing Interest None, (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Understanding the dynamics of electrical signals within neuronal assemblies is crucial to unraveling complex brain functions. Despite recent advances in employing optically active nanostructures in transmembrane potential sensing, there remains room for improvement in terms of response time and sensitivity. Here, we report the development of such a nanosensor capable of detecting electric fields with a submillisecond response time at the single-particle level. We achieve this by using ferroelectric nanocrystals doped with rare-earth ions that produce upconversion (UC). When such a nanocrystal experiences a variation of surrounding electric potential, its surface charge density changes, inducing electric polarization modifications that vary, via a converse piezoelectric effect, the crystal field around the ions. The latter variation is finally converted into UC spectral changes, enabling optical detection of the electric potential. To develop such a sensor, we synthesized erbium and ytterbium-doped barium titanate crystals of ≈160 nm in size. We observed distinct changes in the UC spectrum when individual nanocrystals were subjected to an external field via a conductive atomic force microscope tip, with a response time of 100 μs. Furthermore, our sensor exhibits a remarkable sensitivity of 4.8 kV/cm/ Hz , enabling time-resolved detection of a fast-changing electric field of amplitude comparable to that generated during a neuron action potential.

Pentagonal two-dimensional (2D) materials are notable for unique properties derived from their Cairo pentagonal tiling topology. This study explores the thermoelectric potential of exfoliated penta-palladium-phosphorus-sulfur (PdPS) atomic layers, an air-stable 2D semiconductor with a puckered pentagonal low-symmetry structure, grown via chemical vapor transport (CVT). Thickness-dependent in-plane electrical conductivity (σ) and thermoelectric power factor (PF) of PdPS are investigated from 20-380 K, showing an increase in σ with thickness (11, 13, and 88-layer). Applying back-gate voltage (V g ) modulates the Fermi energy (E F ), and as V g decreases, the Seebeck coefficient (S) rises, achieving S of -700 µV K -1 for 11-layer PdPS at -10 V, significantly higher than the -400 µV K -1 for 88-layer PdPS. The PF increased with decreasing thickness, peaking at ≈50 µW m -1  K -2 for 11-layer PdPS, about twice than that of 88-layer PdPS. The high electron mobility (µ e ) in PdPS is confined to a narrow temperature range, peaking at 300 cm 2  Vs -1 at 100 K, marking the transition temperature from ionized impurity scattering to acoustic phonon scattering mechanism, consistent across all layer counts. This work highlights the significant impact of quantum confinement in ultrathin bodies in enhancing thermoelectric performance across a wide temperature range., (© 2024 Wiley‐VCH GmbH.)

Background and Objectives: In multiple sclerosis (MS), immune cells invade the CNS and destroy myelin. Macrophages contribute to demyelination and myelin repair, and their role in each process depends on their ability to acquire specific phenotypes in response to external signals. In this article, we assess whether defects in MS patient macrophage responses may lead to increased inflammation or lack of neuroregenerative effects., Methods: CD14 + CD16 - monocytes from patients with MS and healthy controls (HCs) were activated in vitro to obtain homeostatic-like, proinflammatory, and proregenerative macrophages. Macrophage activation profiles were assessed through RNA sequencing and metabolomics. Surface molecule expression of CD14, CD16, and HLA-DR and myelin phagocytic capacity were evaluated with flow cytometry. Macrophage supernatant capacity to influence oligodendrocyte precursor cell differentiation toward an astrocytic or oligodendroglia fate was also tested., Results: We observed that MS patient monocytes ex vivo recapitulate their preferential activation toward the CD16 + phenotype, a subset of proinflammatory cells overrepresented in MS lesions. Functionally, MS patient macrophages display a decreased capacity to phagocytose human myelin and a deficit of processing myelin after ingestion. In addition, MS patient macrophage supernatant favors astrocytes over oligodendrocyte differentiation when compared with HC macrophage supernatant. Furthermore, even when exposed to homeostatic or proregenerative stimuli, MS patient macrophages uphold a proinflammatory transcriptomic profile with higher levels of cytokine/chemokine. Of interest, MS patient macrophages exhibit a distinct metabolic signature with a mitochondrial energy metabolism blockage. Transcriptomic data are further substantiated by metabolomics studies that reveal perturbations in the corresponding metabolic pathways., Discussion: Our results show an intrinsic defect of MS patient macrophages, reminiscent of innate immune cell memory in MS, lifting macrophage importance in the disease and as potential therapeutic targets.

Objectives: Clinical Data Warehouses (CDW) are the designated infrastructures to enable access and analysis of large quantities of electronic health record data. Building and managing such systems implies extensive "data work" and coordination between multiple stakeholders. Our study focuses on the challenges these stakeholders face when designing, operating, and ensuring the durability of CDWs for research., Materials and Methods: We conducted semistructured interviews with 21 professionals working with CDWs from France and Belgium. All interviews were recorded, transcribed verbatim, and coded inductively., Results: Prompted by the AI boom, healthcare institutions launched initiatives to repurpose data they were generating for care without a clear vision of how to generate value. Difficulties in operating CDWs arose quickly, strengthened by the multiplicity and diversity of stakeholders involved and grand discourses on the possibilities of CDWs, disjointed from their actual capabilities. Without proper management of the information flows, stakeholders struggled to build a shared vision. This was evident in our interviewees' contrasting appreciations of what mattered most to ensure data quality. Participants explained they struggled to manage knowledge inside and across institutions, generating knowledge loss, repeated mistakes, and impeding progress locally and nationally., Discussion and Conclusion: Management issues strongly affect the deployment and operation of CDWs. This may stem from a simplistic linear vision of how this type of infrastructure operates. CDWs remain promising for research, and their design, implementation, and operation require careful management if they are to be successful. Building on innovation management, complex systems, and organizational learning knowledge will help., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background and Objective: The increasing implementation and use of electronic health records over the last few decades has made a significant volume of clinical data being available. Over the past 20 years, hospitals have also adopted and implemented data warehouse technology to facilitate the reuse of administrative and clinical data for research. However, the implementation of clinical data warehouses encounters a set of barriers: ethical, legislative, technical, human and organizational. This paper proposes an overview of difficulties and barriers encountered during a clinical data warehouse (CDW) development and implementation project., Methods: We conducted a focus group at the 2023 Medical Informatics Europe Conference and invited professionals involved in the implementation of CDW. These experts described their CDW and the difficulties and barriers they encountered at each phase: (i) launching of the data warehouse project, (ii) implementing the data warehouse and (iii) using a data warehouse in routine operations. They were also asked to propose solutions they were able to implement to address the barriers previously reported., Results: After synthesis and consensus, a total of 26 barriers were identified, 10 pertained to tasks, 5 to tools and technologies, 4 to persons, 4 to organization, and 3 to the external environment. To address these challenges, a set of 15 practical recommendations was offered, covering essential aspects such as governance, stakeholder engagement, interdisciplinary collaboration, and external expertise utilization., Conclusions: These recommendations serve as a valuable resource for healthcare institutions seeking to establish and optimize CDWs, offering a roadmap for leveraging clinical data for research, quality enhancement, and improved patient care., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to disclose., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Sodium ion batteries have attracted great attention for large scale energy storage devices to replace lithium-ion batteries. As a promising polyanionic cathode material of sodium-ion batteries, Na 3 V 2 (PO 4 ) 2 F 3 (NVPF) belonging to NASICON exhibits large gap space and excellent structural stability, leading to a high energy density and ultralong cycle lifespan. To improve its stability and Na ion mobility, K + cations are introduced into NVPF crystal as in situ partial substitution for Na + . The influence of K + in situ substitution on crystal structure, electronic properties, kinetic properties, and electrochemical performance of NVPF are investigated. Through ex situ examination, it turns out that K + occupied Na1 ion, in which the K + does not participate in the charge-discharge process and plays a pillar role in improving the mobility of Na + . Moreover, the doping of K + cation can reduce the bandgap energy and improve the electronic conductivity. Besides, the optimal K + doping concentration in N 0.92 K 0.08 VPF/C is found so as to achieve rapid Na + migration and reversible phase transition. The specific capacity of N 0.92 K 0.08 VPF/C is as high as 128.8 mAh g -1 at 0.2 C, and at 10 C its rate performance is excellent, which shows a capacity of 113.3 mAh g -1 ., (© 2024 Wiley‐VCH GmbH.)

Achieving substantial electrostrain alongside a large effective piezoelectric strain coefficient (d 33 *) in piezoelectric materials remains a formidable challenge for advanced actuator applications. Here, a straightforward approach to enhance these properties by strategically designing the domain structure and controlling the domain switching through the introduction of arrays of ordered {100}<100> dislocations is proposed. This dislocation engineering yields an intrinsic lock-in steady-state electrostrain of 0.69% at a low field of 10 kV cm -1 without external stress and an output strain energy density of 5.24 J cm -3 in single-crystal BaTiO 3 , outperforming the benchmark piezoceramics and relaxor ferroelectric single-crystals. Additionally, applying a compression stress of 6 MPa fully unlocks electrostrains exceeding 1%, yielding a remarkable d 33 * value over 10 000 pm V -1 and achieving a record-high strain energy density of 11.67 J cm -3 . Optical and transmission electron microscopy, paired with laboratory and synchrotron X-ray diffraction, is employed to rationalize the observed electrostrain. Phase-field simulations further elucidate the impact of charged dislocations on domain nucleation and domain switching. These findings present an effective and sustainable strategy for developing high-performance, lead-free piezoelectric materials without the need for additional chemical elements, offering immense potential for actuator technologies., (© 2024 Wiley‐VCH GmbH.)

Food-packaging-processing interactions define packaging materials' performance properties and product quality. This study evaluated the effect of ohmic heating (OH) processing and different food simulants on the properties of four multilayer flexible packaging materials (PET met /PE, PET met /PP, PET/Al/PE, and PET/Al/PA/PP). OH treatment was applied to the sealed packages containing the food simulants using a voltage gradient of 3.7 V/cm at a frequency of 20 kHz, resulting in a thermal process of at 80 °C for 1 min. The structure and performance of the different packages were then evaluated. The materials did not show changes in chemical groups nor thermal properties. However, the simulant-packaging-processing interaction resulted in changes in crystallinity, morphology, mechanical and barrier properties (water and oxygen), especially for metallized films in contact with acidic food simulants. The results indicate that although OH resulted in changes in packaging materials, these materials can be used under the conditions applied in this study., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Water pumps powered by photovoltaic energy, often named 'photovoltaic water pumping systems' (PVWPS), offer a promising solution for improving water access in developing regions. Regular pumping tests are essential for characterizing boreholes and ensuring sustainable groundwater extraction. Traditionally, these tests are conducted only at the time of PVWPS installation using diesel pumps. However, since PVWPS typically have a lifespan of around 20 years, the borehole's condition may change over time, necessitating ongoing testing. To overcome this challenge, this article presents a novel method for conducting pumping tests using the PVWPS's own photovoltaic modules as the power source, greatly simplifying regular borehole monitoring over the PVWPS's lifespan. This approach improves the long-term technical sustainability of PVWPS. By eliminating the need for diesel generators, it reduces also costs, emissions, and logistical complexity while ensuring continuous water supply during testing. The principle and protocol for these proposed tests are outlined, as well as the key indicators for analysis. Furthermore, the associated costs and benefits are thoroughly explored. The proposed method is applied to a PVWPS in a village in Burkina Faso. This PVWPS has 750 W p of photovoltaic modules, a 10 m³ water tank, and a 56 m borehole. Results show that the photovoltaic pumping tests allow to accurately determine borehole parameters, achieving a model fit with an average R 2 of 0.99. Additionally, a photovoltaic pumping test costs $43, which is significantly lower than standard pumping tests: a multiple step drawdown test costs $511 and a long pumping test costs $2050. Moreover, the proposed photovoltaic pumping tests can prevent premature replacements of PVWPS components, leading to significant savings. While demonstrated in a specific context, this method is transferable to other systems, offering potential benefits for companies, local authorities, governments, and NGOs involved in the development and maintenance of PVWPS in rural areas., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

As electronic devices continue to be integrated, miniaturized, and operated at higher frequencies, the demand for green, advanced polymer nanocomposites with superior electromagnetic interference (EMI) shielding, thermal conduction, and electrical insulation properties significantly increases. However, achieving such multifunctional nanocomposites is challenging due to the inherent contradiction between electrical and magnetic properties. Biopolymer nanocomposites of polycaprolactone (PCL)/boron nitride (BN)@polylactic acid (PLA)/multi-walled carbon nanotubes (CNTs) ((PCL/BN)@(PLA/CNTs)) exhibit a unique "brick-mud" segregated double-network structure. This configuration effectively separates high-melting-point PLA/CNTs conductive phase from the PCL/BN insulating matrix. PLA/CNTs particles contribute to enhanced EMI shielding by attenuating electromagnetic waves, while also improving insulation by disrupting electron transfer within the PCL/BN phase. Additionally, incorporating conductive CNTs and thermal conductive BN further boosts the thermal conductivity (TC) of the nanocomposites. The structured sample (s-8B8C), which contains 8 wt% BN and 8 wt% CNTs, achieves an EMI shielding effectiveness (SE) of 31.4 dB in the X-band, a TC of 0.6 W m -1 K -1 , and a volume resistivity of 7.2 × 10 11 Ω cm. In summary, the "brick-mud" segregated structure facilitates the development of advanced biopolymer nanocomposites for electronic applications, leveraging sustainable materials for broad potential use.

Understanding the niche interactions between blood and bone through the in vitro co-culture of osteo-competent cells and endothelial cells is a key factor in unraveling therapeutic potentials in bone regeneration. This can be additionally supported by employing numerical simulation techniques to assess local physical factors, such as oxygen concentration, and mechanical stimuli, such as shear stress, that can mediate cellular communication. In this study, we developed a Mesenchymal Stem Cell line (MSC) and a Human Umbilical Vein Endothelial Cell line (HUVEC), which were co-cultured under flow conditions in a three-dimensional, porous, natural pullulan/dextran scaffold that was supplemented with hydroxyapatite crystals that allowed for the spontaneous formation of spheroids. After 2 weeks, their viability was higher under the dynamic conditions (>94%) than the static conditions (<75%), with dead cells central in the spheroids. Mineralization and collagen IV production increased under the dynamic conditions, correlating with osteogenesis and vasculogenesis. The endothelial cells clustered at the spheroidal core by day 7. Proliferation doubled in the dynamic conditions, especially at the scaffold peripheries. Lattice Boltzmann simulations showed negligible wall shear stress in the hydrogel pores but highlighted highly oxygenated zones coinciding with cell proliferation. A strong oxygen gradient likely influenced endothelial migration and cell distribution. Hypoxia was minimal, explaining high viability and spheroid maturation in the dynamic conditions.

Raman spectroscopy and machine learning have become popular in in-line monitoring of bioreactors. However, traditional modeling processes typically entail extensive fermentation batches to collect learning datasets, which are significantly time-consuming and laborious. In addition, these models are limited to configurations with the same conditions as the training batches. The present work proposes a reproducible and adaptable modeling approach by combining standard spectra as a training dataset, with a simple means of correcting for cell scattering. Alcoholic fermentation by Saccharomyces cerevisiae is used as a benchmark. Initially, a partial least squares (PLS) regression model was developed based on the spectra of pure solutions of glucose and ethanol. Then, a mathematical expression was defined to estimate yeast concentration, allowing the correction of Raman intensity attenuated by cell scattering. The corrected spectra demonstrate close alignment with reference spectra in both shape and intensity. Validation of the methodology was conducted across numerous batches and one fed-batch bioreactor. As a result, the developed method enables the simultaneous monitoring of glucose, ethanol, and yeast concentrations, effectively addressing the challenge of implementing an independent standards based PLS model to manage the intricate compositional dynamics in bio-processes. The conclusion underscores the effectiveness of the proposed method and offers new prospects in biotechnological industries., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preoperative work-up relies on MR images and fine needle aspiration biopsy, but these diagnostic tools have low sensitivity and specificity, often leading to surgery for diagnostic purposes. The aim of this paper is (1) to develop a machine learning algorithm based on MR images characteristics to automatically classify parotid gland tumours and (2) compare its results with the diagnoses of junior and senior radiologists in order to evaluate its utility in routine practice. While automatic algorithms applied to parotid tumours classification have been developed in the past, we believe that our study is one of the first to leverage four different MRI sequences and propose a comparison with clinicians. In this study, we leverage data coming from a cohort of 134 patients treated for benign or malignant parotid tumours. Using radiomics extracted from the MR images of the gland, we train a random forest and a logistic regression to predict the corresponding histopathological subtypes. On the test set, the best results are given by the random forest: we obtain a 0.720 accuracy, a 0.860 specificity, and a 0.720 sensitivity over all histopathological subtypes, with an average AUC of 0.838. When considering the discrimination between benign and malignant tumours, the algorithm results in a 0.760 accuracy and a 0.769 AUC, both on test set. Moreover, the clinical experiment shows that our model helps to improve diagnostic abilities of junior radiologists as their sensitivity and accuracy raised by 6 % when using our proposed method. This algorithm may be useful for training of physicians. Radiomics with a machine learning algorithm may help improve discrimination between benign and malignant parotid tumours, decreasing the need for diagnostic surgery. Further studies are warranted to validate our algorithm for routine use., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

In this paper, we introduce functional generalized canonical correlation analysis, a new framework for exploring associations between multiple random processes observed jointly. The framework is based on the multiblock regularized generalized canonical correlation analysis framework. It is robust to sparsely and irregularly observed data, making it applicable in many settings. We establish the monotonic property of the solving procedure and introduce a Bayesian approach for estimating canonical components. We propose an extension of the framework that allows the integration of a univariate or multivariate response into the analysis, paving the way for predictive applications. We evaluate the method's efficiency in simulation studies and present a use case on a longitudinal dataset., (© The Author(s) 2024. Published by Oxford University Press on behalf of The International Biometric Society.)

The catastrophic dendrite hyperplasia and parasitic reactions severely impede the future deployment of aqueous Zn-ion batteries. Controlling zinc orientation growth is considered to be an effective method to overcome the aforementioned concerns, especially for regulating the (002) plane of deposited Zn. Unfortunately, Zn (002) texture is difficult to obtain stable cycling under high deposition capacity resulting from its large lattice distortion and nonuniform distribution in electric field. Herein, different from traditional cognition, a crystallization orientation regulation tactic is proposed to boost Zn (101) texture exposure and inhibit zinc dendrite proliferation during plating/stripping. Experimental results and theoretical calculations demonstrate the malate molecules preferentially adsorb on the Zn (002) facet, leading to the texture exposure of distinctive Zn (101) plane. Meanwhile, the -COOH and -OH groups of malate molecules exhibit strong adsorption on the Zn anode surface and chelate with Zn 2+ , achieving H 2 O-poor electrical double layer. Very impressively, the multifunctional malate additive enlists zinc anode to survive for 600 h under a harsh condition of 15 mA cm -2 /15 mAh cm -2 . Moreover, the symmetric cell harvests highly-reversible cycling life of 6600 h at 5 mA cm -2 /1.25 mAh cm -2 , remarkably outperforming the ZnSO 4 electrolyte. The assembled Zn//MnO 2 full cells also demonstrate prominent electrochemical reversibility., (© 2024 Wiley-VCH GmbH.)

Slow-cooled CF8M duplex stainless steel is used for critical parts of the primary coolant pipes of nuclear reactors. This steel can endure severe service conditions, but it tends to become more brittle upon very long-term aging (tens of years). Therefore, it is essential to understand its specific microstructure and temporal evolution. As revealed by electron backscatter diffraction (EBSD) analyses, the microstructure consists of millimetre-scale ferritic grains within which austenite lath packets have grown with preferred crystallographic orientations concerning the parent ferritic phase far from the ferrite grain boundaries. In these lath packets where the austenite phase is nucleated, the lath morphology and crystal orientation accommodate the two ferrite orientations. Globally, the Pitsch orientation relationship appears to display the best agreement with the experimental data compared with other classical relationships. The austenite lath packets are parallel plate-shaped laths, characterized by their normal n . A novel methodology is introduced to elucidate the expected relationship between n and the crystallographic orientation given the coarse interfaces, even though n is only partly known from the observation surface, in contrast to the 3D crystal orientations measured by EBSD. The distribution of retrieved normals n is shown to be concentrated over a set of discrete orientations. Assuming that the ferrite and austenite obey the Pitsch orientation relationship, the determined lath normals are close to an invariant direction of the parent phase given by the same orientation relationship., (© Maxime Mollens et al. 2024.)

Because of their intrinsic polarization and related properties, ferroelectrics attract significant attention to address energy transformation and environmental protection. Here, by using trivalent-ion-lanthanum doping of BiFeO 3 nanoparticles (NPs), it is shown that defects and piezoelectric potential are synergized to achieve a high piezocatalytic effect for decomposing the model Rhodamine B (RhB) pollutant, reaching a record-high piezocatalytic rate of 21 360 L mol -1 min -1 (i.e., 100% RhB degradation within 20 min) that exceeds most state-of-the art ferroelectrics. The piezocatalytic Bi 0.99 La 0.01 FeO 3 NPs are also demonstrated to be versatile toward various pharmaceutical pollutants with over 90% removal efficiency, making them extremely efficient piezocatalysts for water purification. It is also shown that 1% La-doping introduces oxygen vacancies and Fe 2+ defects. It is thus suggested that oxygen vacancies act as both active sites and charge providers, permitting more surface adsorption sites for the piezocatalysis process, and additional charges and better energy transfer between the NPs and surrounding molecules. Furthermore, the oxygen vacancies are proposed to couple to Fe 2+ to form defect dipoles, which in turn introduces an internal field, resulting in more efficient charge de-trapping and separation when added to the piezopotential. This synergistic mechanism is believed to provide a new perspective for designing future piezocatalysts with high performance., (© 2024 The Author(s). Small published by Wiley‐VCH GmbH.)

Exciton-polaritons, hybrid light-matter excitations arising from the strong coupling between excitons in semiconductors and photons in photonic nanostructures, are crucial for exploring the physics of quantum fluids of light and developing all-optical devices. Achieving room temperature propagation of polaritons with a large excitonic fraction is challenging but vital, e.g., for nonlinear light transport. We report on room temperature propagation of exciton-polaritons in a metasurface made from a subwavelength lattice of perovskite pillars. The large Rabi splitting, much greater than the optical phonon energy, decouples the lower polariton band from the phonon bath of the perovskite. These cooled polaritons, in combination with the high group velocity achieved through the metasurface design, enable long-range propagation, exceeding hundreds of micrometers even with an 80% excitonic component. Furthermore, the design of the metasurface introduces an original mechanism for unidirectional propagation through polarization control, suggesting a new avenue for the development of advanced polaritonic devices.

Purpose: We aimed at identifying prevalence, clinical outcomes and prognostic factors in cancer patients with intravenous chemotherapy-induced severe neutropenia (ICISN)., Methods: In this multicenter retrospective cohort study on the clinical data warehouse of Greater Paris University Hospitals (AP-HP), we included all adult patients with solid cancer hospitalized between 2016 and 2021 with intravenous chemotherapy within 30 days prior to severe neutropenia (D70 or D611 ICD-10 codes AND a neutrophil count < 500/mm3). The primary endpoint was referral to intensive care unit (ICU) or death within 30 days. We collected cancer, patient, and treatment characteristics., Results: Among 141,586 cancer inpatients, 40,660 received chemotherapy among whom 661 (1.6%) had ICISN. Median age was 63 years (interquartile range (IQR), 54-70) and 330 patients (49%) were female. The median Charlson score was 10 (IQR, 8-11). Main primary cancers were lung (n = 204, 31%) and breast (n = 87, 13%). Advanced cancers were found in 551 patients (83%), 331 (50%) were in 1st line of chemotherapy, 284 (42%) in the 1st cycle of the current line and 149 (22%) had primary G-CSF. Documented bacterial (mostly gram-negative bacilli) and fungal infections were observed in 113 (17%) and 19 (3%) patients; 58 (9%) were transferred to ICU and 82 (12%) died within 30 days, 372 (56%) patients received subsequent chemotherapy. Independent prognostic factors were the level of monocyte, lymphocyte counts or albuminemia and a documented bacterial infection, while Charlson index and primary prophylactic G-CSF were not associated with patient clinical outcomes., Conclusion: Despite the use of primary G-CSF, ICISN remains a frequent event, which leads to ICU death in one on five cases Some prognostic factors of severity have been highlighted and could help clinicians to prevent severe complications., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Rationale and Objectives: Automated evaluation of abdominal computed tomography (CT) scans should help radiologists manage their massive workloads, thereby leading to earlier diagnoses and better patient outcomes. Our objective was to develop a machine-learning model capable of reliably identifying suspected bowel obstruction (BO) on abdominal CT., Materials and Methods: The internal dataset comprised 1345 abdominal CTs obtained in 2015-2022 from 1273 patients with suspected BO; among them, 670 were annotated as BO yes/no by an experienced abdominal radiologist. The external dataset consisted of 88 radiologist-annotated CTs. We developed a full preprocessing pipeline for abdominal CT comprising a model to locate the abdominal-pelvic region and another model to crop the 3D scan around the body. We built, trained, and tested several neural-network architectures for the binary classification (BO, yes/no) of each CT. F1 and balanced accuracy scores were computed to assess model performance., Results: The mixed convolutional network pretrained on a Kinetics 400 dataset achieved the best results: with the internal dataset, the F1 score was 0.92, balanced accuracy 0.86, and sensitivity 0.93; with the external dataset, the corresponding values were 0.89, 0.89, and 0.89. When calibrated on sensitivity, this model produced 1.00 sensitivity, 0.84 specificity, and an F1 score of 0.88 with the internal dataset; corresponding values were 0.98, 0.76, and 0.87 with the external dataset., Conclusion: The 3D mixed convolutional neural network developed here shows great potential for the automated binary classification (BO yes/no) of abdominal CT scans from patients with suspected BO., Clinical Relevance Statement: The 3D mixed CNN automates bowel obstruction classification, potentially automating patient selection and CT prioritization, leading to an enhanced radiologist workflow., Key Points: • Bowel obstruction's rising incidence strains radiologists. AI can aid urgent CT readings. • Employed 1345 CT scans, neural networks for bowel obstruction detection, achieving high accuracy and sensitivity on external testing. • 3D mixed CNN automates CT reading prioritization effectively and speeds up bowel obstruction diagnosis., (© 2024. The Author(s), under exclusive licence to European Society of Radiology.)

Dual channel photo-driven H 2 O 2 production in pure water on small-scale on-site setups is a promising strategy to provide low-concentrated H 2 O 2 whenever needed. This process suffers, however, strongly from the fast recombination of photo-generated charge carriers and the sluggish oxidation process. Here, insoluble Keggin-type cesium phosphomolybdate Cs 3 PMo 12 O 40 (abbreviated to Cs 3 PMo 12 ) is introduced to carbonized cellulose (CC) to construct S-scheme heterojunction Cs 3 PMo 12 /CC. Dual channel H 2 O 2 photosynthesis from both H 2 O oxidation and O 2 reduction in pure water has been thus achieved with the production rate of 20.1 mmol L -1  g cat. -1  h -1 , apparent quantum yield (AQY) of 2.1% and solar-to-chemical conversion (SCC) efficiency of 0.050%. H 2 O 2 accumulative concentration reaches 4.9 mmol L -1 . This high photocatalytic activity is guaranteed by unique features of Cs 3 PMo 12 /CC, namely, S-scheme heterojunction, electron reservoir, and proton reservoir. The former two enhance the separation of photo-generated charge carriers, while the latter speeds up the torpid oxidation process. In situ experiments reveal that H 2 O 2 is formed via successive single-electron transfer in both channels. In real practice, exposing the reaction system under natural sunlight outdoors successfully results in 0.24 mmol L -1 H 2 O 2 . This work provides a key practical strategy for designing photocatalysts in modulating redox half-reactions in photosynthesis., (© 2024 Wiley‐VCH GmbH.)

Liver resection is one of the best treatments for small hepatocellular carcinoma (HCC), but post-resection recurrence is frequent. Biotherapies have emerged as an efficient adjuvant treatment, making the identification of patients at high risk of recurrence critical. Microvascular invasion (mVI), poor differentiation, pejorative macrotrabecular architectures, and vessels encapsulating tumor clusters architectures are the most accurate histologic predictors of recurrence, but their evaluation is time-consuming and imperfect. Herein, a supervised deep learning-based approach with ResNet34 on 680 whole slide images (WSIs) from 107 liver resection specimens was used to build an algorithm for the identification and quantification of these pejorative architectures. This model achieved an accuracy of 0.864 at patch level and 0.823 at WSI level. To assess its robustness, it was validated on an external cohort of 29 HCCs from another hospital, with an accuracy of 0.787 at WSI level, affirming its generalization capabilities. Moreover, the largest connected areas of the pejorative architectures extracted from the model were positively correlated to the presence of mVI and the number of tumor emboli. These results suggest that the identification of pejorative architectures could be an efficient surrogate of mVI and have a strong predictive value for the risk of recurrence. This study is the first step in the construction of a composite predictive algorithm for early post-resection recurrence of HCC, including artificial intelligence-based features., Competing Interests: Disclosure Statement None declared., (Copyright © 2024 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Background: The global research on pandemics or epidemics and mental health has been growing exponentially recently, which cannot be integrated through traditional systematic review. Our study aims to systematically synthesize the evidence using natural language processing (NLP) techniques., Methods: Multiple databases were searched using titles, abstracts, and keywords. We systematically identified relevant literature published prior to Dec 31, 2023, using NLP techniques such as text classification, topic modelling and geoparsing methods. Relevant articles were categorized by content, date, and geographic location, outputting evidence heat maps, geographical maps, and narrative synthesis of trends in related publications., Results: Our NLP analysis identified 77,915 studies in the area of pandemics or epidemics and mental health published before Dec 31, 2023. The Covid pandemic was the most common, followed by SARS and HIV/AIDS; Anxiety and stress were the most frequently studied mental health outcomes; Social support and healthcare were the most common way of coping. Geographically, the evidence base was dominated by studies from high-income countries, with scant evidence from low-income counties. Co-occurrence of pandemics or epidemics and fear, depression, stress was common. Anxiety was one of the three most common topics in all continents except North America., Conclusion: Our findings suggest the importance and feasibility of using NLP to comprehensively map pandemics or epidemics and mental health in the age of big literature. The review identifies clear themes for future clinical and public health research, and is critical for designing evidence-based approaches to reduce the negative mental health impacts of pandemics or epidemics., (© 2024. The Author(s).)

New groundwater development is a likely way to meet growing global water demand but needs careful management. To help inform the sustainable development of groundwater resources, a novel method based on the maximum safe installable power for water pumping systems and the maximum safe remaining installable power (considering current abstraction) is developed. The proposed model couples energy, technology and hydrogeological parameters, and is then developed to compute the maximum power that can be safely installed per km 2 without exceeding a maximum annual pumpable volume, calculated through available recharge and storage. The model is applied to estimate the maximum safe installable power across Africa with a 0.2-degree resolution, using available energy and hydrogeological data. Constrained by recharge (considering that 25 % of the annual recharge is available for utilization), the maximum safe installable power ranges between 0 and 9960 W/km 2 across Africa with regions such as the Congo Basin (∼340 W/km 2 ), and western Africa between the Ivory Coast and Nigeria (∼230 W/km 2 ) identified as having high potential for sustainable pumping system development. Constrained by storage (considering that 0.1 % of storage can be withdrawn per year), it ranges between 0 and 13,425 W/km 2 highlighting the ability to harness storage for pumping system development in the large aquifers of Northern Sahara (∼8720 W/km 2 ). When considering limitations posed by both groundwater recharge and aquifer storage (considering that 25 % of the annual recharge and 0.1 % of storage can be withdrawn per year), along with current groundwater withdrawal, 93 % of the maximum safe installable power remains still installable on average across Africa. Nevertheless, 2 % of the locations are estimated to be already experiencing overexploitation, particularly in Sudan, northern Africa, and northeastern South Africa. These findings provide a novel and adaptable way to examine water security, which can assist institutions in targeting investments to meet water demand sustainably., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2024. Published by Elsevier B.V. All rights reserved.)

G protein-coupled receptors (GPCRs) exemplify sophisticated allosteric communication, transducing extracellular signals through ligand-induced structural rearrangements that resonate through the molecular scaffold. Despite extensive study, the biophysical underpinnings of how conformational changes spread remain unclear. This work employs a novel physics-based framework to characterize the role of energy dissipation in directing intramolecular signaling pathways. By modeling each residue as a network of coupled oscillators, we generate a localization landscape depicting the vibrational energy distribution throughout the protein scaffold. Quantifying directional energy flux between residues reveals distinct pathways for energy and information transfer, illuminating sequences of allosteric communication. Our analysis of CB1 and CCR5 crystal structures unveils an anisotropic pattern of energy dissipation aligning with key functional dynamics, such as activation-related conformational changes. These anisotropic patterns of vibrational energy flow constitute pre-configured channels for allosteric signaling. Elucidating the relationship between structural topology and energy dissipation patterns provides key insights into the thermodynamic drivers of conformational signaling. This methodology significantly advances our mechanistic understanding of allostery in GPCRs and presents a broadly applicable approach for rationally dissecting allosteric communication pathways, with potential implications for structure-based drug design targeting these critical receptors., (© 2024 Wiley Periodicals LLC.)

Advancements in high-temperature thermoelectric (TE) materials have been substantial, yet identifying promising near-room-temperature candidates for efficient power generation from low-grade waste heat or TE cooling applications has become critical but proven exceedingly challenging. Bismuth oxyselenide (Bi 2 O 2 Se) emerges as an ideal candidate for near-room-temperature energy harvesting due to its low thermal conductivity, high carrier mobility and remarkable air-stability. In this study, the TE properties of few-layer Bi 2 O 2 Se over a wide temperature range (20-380 K) are investigated, where a charge transport mechanism transitioning from polar optical phonon to piezoelectric scattering at 140 K is observed. Moreover, the Seebeck coefficient ( S ) increases with temperature up to 280 K then stabilizes at∼-200 μ V K -1 through 380 K. Bi 2 O 2 Se demonstrates high mobility (450 cm 2 V -1 s -1 ) within the optimum power factor (PF) window, despite itsT-1.25dependence. The high mobility compensates the minor reduction in carrier density n 2D hence contributes to maintain a robust electrical conductivity∼3 × 10 4 S m -1 . This results in a remarkable PF of 860 μ W m -1 K -2 at 280 K without the necessity for gating ( V g = 0 V), reflecting the innate performance of the as-grown material. These results underscore the considerable promise of Bi 2 O 2 Se for room temperature TE applications., (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Background : Retention in treatment is crucial for the success of interventions targeting alcohol use disorder (AUD), which affects over 100 million people globally. Most previous studies have used classical statistical techniques to predict treatment dropout, and their results remain inconclusive. This study aimed to use novel machine learning tools to identify models that predict dropout with greater precision, enabling the development of better retention strategies for those at higher risk. Methods : A retrospective observational study of 39,030 (17.3% female) participants enrolled in outpatient-based treatment for alcohol use disorder in a state-wide public treatment network has been used. Participants were recruited between 1 January 2015 and 31 December 2019. We applied different machine learning algorithms to create models that allow one to predict the premature cessation of treatment (dropout). With the objective of increasing the explainability of those models with the best precision, considered as black-box models, explainability technique analyses were also applied. Results : Considering as the best models those obtained with one of the so-called black-box models (support vector classifier (SVC)), the results from the best model, from the explainability perspective, showed that the variables that showed greater explanatory capacity for treatment dropout are previous drug use as well as psychiatric comorbidity. Among these variables, those of having undergone previous opioid substitution treatment and receiving coordinated psychiatric care in mental health services showed the greatest capacity for predicting dropout. Conclusions : By using novel machine learning techniques on a large representative sample of patients enrolled in alcohol use disorder treatment, we have identified several machine learning models that help in predicting a higher risk of treatment dropout. Previous treatment for other substance use disorders (SUDs) and concurrent psychiatric comorbidity were the best predictors of dropout, and patients showing these characteristics may need more intensive or complementary interventions to benefit from treatment.

Silicon is considered as the next-generation anode material for lithium-ion batteries due to its high theoretical specific capacity and abundant crustal abundance. However, its poor electrical conductivity results in slow diffusion of lithium ions during battery operation. Simultaneously, the alloying process of silicon undergoes a 300 % volume change, leading to structural fractures in silicon during the cycling process. As a result, it loses contact with the current collector, continuously exposing active sites, and forming a sustained solid electrolyte interface (SEI) membrane. This paper presents the design of a fluorine-ion-regulated yolk-shell carbon-silicon anode material, highlighting the following advantages: (a) Alleviating volume changes through the design of a yolk-shell structure, thereby maintaining material structural integrity during cycling. (b) Carbon shell prevents silicon from coming into contact with the electrolyte, simultaneously improving silicon's electrical conductivity and increasing ion/electron conductivity. (c) Utilizing fluorine-ion interface modification to obtain an SEI membrane rich in fluorine components (such as LiF), thereby enhancing its long cycling performance. The F-Si@Void@C exhibits outstanding electrochemical performance, with a reversible capacity of 1166 mAh/g after 900 cycles at a current density of 0.5 A/g., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective . Digital tomosynthesis (DTS) is a type of limited-angle Computed Tomography (CT) used in orthopedic and oncology care to provide a pseudo-3D reconstructed volume of a body part from multiple x-ray projections. Patient motion during acquisitions results in artifacts which affect screening and diagnostic performances. Hence, accurate reconstruction of moving body parts from a tomosynthesis projection series is addressed in this paper, with a particular focus on the breast. The aim of this paper is to assess the feasibility of a novel dynamic reconstruction technique for DTS and evaluate its accuracy compared to an available ground truth. Approach . The proposed method is a combination of a 4D dynamic tomography strategy leveraging the formalism of Projection-based Digital Volume Correlation (P-DVC) with a multiscale approach to estimate and correct patient motion. Iterations of two operations are performed: (i) a motion-corrected reconstruction based on the Simultaneous Iterative Reconstruction Technique (SIRT) algorithm and (ii) a motion estimation from projection residuals, to obtain motion-free volumes. Performance is evaluated on a synthetic Digital Breast Tomosynthesis (DBT) case. Three slabs of a CIRS breast phantom are imaged on a Senographe Pristina TM , under plate-wise rigid body motions with amplitudes ranging up to 10 mm so that an independent measurement of the motion can be accessed. Results . Results show a motion estimation average precision down to 0.183 mm (1.83 voxels), when compared to the independent measurement. Moreover, an 84.2% improvement on the mean residual error and a 59.9% improvement on the root mean square error (RMSE) with the original static reconstruction are obtained. Significance . Visual and quantitative assessments of the dynamically reconstructed volumes show that the proposed method fully restores conspicuity for important clinical features contained in the phantom., (© 2024 IOP Publishing Ltd.)

This study presents a Bayesian maximum a posteriori (MAP) framework for dynamical system identification from time-series data. This is shown to be equivalent to a generalized Tikhonov regularization, providing a rational justification for the choice of the residual and regularization terms, respectively, from the negative logarithms of the likelihood and prior distributions. In addition to the estimation of model coefficients, the Bayesian interpretation gives access to the full apparatus for Bayesian inference, including the ranking of models, the quantification of model uncertainties, and the estimation of unknown (nuisance) hyperparameters. Two Bayesian algorithms, joint MAP and variational Bayesian approximation, are compared to the least absolute shrinkage and selection operator (LASSO), ridge regression, and the sparse identification of nonlinear dynamics (SINDy) algorithms for sparse regression by application to several dynamical systems with added Gaussian or Laplace noise. For multivariate Gaussian likelihood and prior distributions, the Bayesian formulation gives Gaussian posterior and evidence distributions, in which the numerator terms can be expressed in terms of the Mahalanobis distance or "Gaussian norm" ||y-y^||M-12=(y-y^)⊤M-1(y-y^), where y is a vector variable, y^ is its estimator, and M is the covariance matrix. The posterior Gaussian norm is shown to provide a robust metric for quantitative model selection for the different systems and noise models examined., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Ferroelectric materials display exotic polarization textures at the nanoscale that could be used to improve the energetic efficiency of electronic components. The vast majority of studies were conducted in two dimensions on thin films that can be further nanostructured, but very few studies address the situation of individual isolated nanocrystals (NCs) synthesized in solution, while such structures could have other fields of applications. In this work, we experimentally and theoretically studied the polarization texture of ferroelectric barium titanate (BaTiO 3 , BTO) NCs attached to a conductive substrate and surrounded by air. We synthesized NCs of well-defined quasicubic shape and 160 nm average size that conserve the tetragonal structure of BTO at room temperature. We then investigated the inverse piezoelectric properties of such pristine individual NCs by vector piezoresponse force microscopy (PFM), taking particular care to suppress electrostatic artifacts. In all of the NCs studied, we could not detect any vertical PFM signal, and the maps of the lateral response all displayed larger displacement amplitude on the edges with deformations converging toward the center. Using field phase simulations dedicated to ferroelectric nanostructures, we were able to predict the equilibrium polarization texture. These simulations revealed that the NC core is composed of 180° up and down domains defining the polar axis that rotate by 90° in the two facets orthogonal to this axis, eventually lying within these planes forming a layer of about 10 nm thickness mainly composed of 180° domains along an edge. From this polarization distribution, we predicted the lateral PFM response, which was revealed to be in very good qualitative agreement with the experimental observations. This work positions PFM as a relevant tool to evaluate the potential of complex ferroelectric nanostructures to be used as sensors.

Catalyst systems populated by high-density single atoms are crucial for improving catalytic activity and selectivity, which can potentially maximize the industrial prospects of heterogeneous single-atom catalysts (SACs). However, achieving high-loading SACs with metal contents above 10 wt% remains challenging. Here we describe a general negative pressure annealing strategy to fabricate ultrahigh-loading SACs with metal contents up to 27.3-44.8 wt% for 13 different metals on a typical carbon nitride matrix. Furthermore, our approach enables the synthesis of high-entropy single-atom catalysts (HESACs) that exhibit the coexistence of multiple metal single atoms with high metal contents. In-situ aberration-corrected HAADF-STEM (AC-STEM) combined with ex-situ X-ray absorption fine structure (XAFS) demonstrate that the negative pressure annealing treatment accelerates the removal of anionic ligand in metal precursors and boosts the bonding of metal species with N defective sites, enabling the formation of dense N-coordinated metal sites. Increasing metal loading on a platinum (Pt) SAC to 41.8 wt% significantly enhances the activity of propane oxidation towards liquid products, including acetone, methanol, and acetic acid et al. This work presents a straightforward and universal approach for achieving many low-cost and high-density SACs for efficient catalytic transformations., (© 2024. The Author(s).)

Our previous studies of dissociative recombination and vibrational excitation/de-excitation of the BeH + ion, based on the multichannel quantum defect theory, are extended to collision energies above the dissociation threshold, taking into account the vibrational continua of the BeH + ion and, consequently, its dissociative excitation. We have also significantly increased the number of dissociative states of 2 Π, 2 Σ + and 2 Δ symmetry included in our cross section calculations, generating the most excited ones by using appropriate scaling laws. Our results are suitable for modeling the kinetics of BeH + in edge fusion plasmas for collision energies up to 12 eV.

The relationship between time irreversibility in neuronal dynamics and cognitive effort is a subject of growing interest in the scientific literature. Although correlations between proxies of both concepts have been experimentally observed, the underlying precise linkage between them remains elusive. Here we investigate the case of learning in decision-making tasks; we do so by introducing a thermodynamically grounded metric-inspired by Landauer's principle-which connects time-irreversible information processing to energy consumption. Equipped with this metric, we investigate the role of macroscopic time-reversal symmetry breaking in belief dynamics for the case of an agent with finite sensitivity while performing a static two-armed bandit task-a standard setup in cognitive neuroscience. To gain insights into the belief dynamics, we analogize it to the dynamics of an active particle subject to state-dependent noise and living in a two-dimensional space. This mapping allows an analytical description of learning-induced biases. We deeply explore the case of Q-learning with forgetting the nonchosen option. In this case, learning-induced risk aversion is formally equivalent to standard thermophoresis, i.e., the net motion towards low-temperature regions. Finally, we quantify the irreversibility of belief dynamics in the steady state for different bandit configurations, sensitivity levels, and exploitative behavior. We found a strong correlation in high-sensitivity learning between heightened irreversibility in belief dynamics and improved decision-making outcomes. Notably, as the task's difficulty increases, a greater degree of irreversibility in belief dynamics becomes necessary for having superior performances; this explicitly unravels a plausible connection between time irreversibility and cognitive effort. In conclusion, our investigation reveals that irreversibility in belief dynamics bridges out-of-equilibrium statistical physics concepts and cognitive neuroscience. In decision-making contexts, this perspective offers insights into the notion of cognitive effort, suggesting a potential mechanism driving the evolution of living systems toward out-of-equilibrium structures.

Topologically protected spin whirls in ferromagnets are foreseen as the cart-horse of solitonic information technologies. Nevertheless, the future of skyrmionics may rely on antiferromagnets due to their immunity to dipolar fields, straight motion along the driving force and ultrafast dynamics. While complex topological objects were recently discovered in intrinsic antiferromagnets, mastering their nucleation, stabilization and manipulation with energy-efficient means remains an outstanding challenge. Designing topological polar states in magnetoelectric antiferromagnetic multiferroics would allow one to electrically write, detect and erase topological antiferromagnetic entities. Here we stabilize ferroelectric centre states using a radial electric field in multiferroic BiFeO 3 thin films. We show that such polar textures contain flux closures of antiferromagnetic spin cycloids, with distinct antiferromagnetic entities at their cores depending on the electric field polarity. By tuning the epitaxial strain, quadrants of canted antiferromagnetic domains can also be electrically designed. These results open the path to reconfigurable topological states in multiferroic antiferromagnets., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Increased consumer awareness for healthier and more sustainable products has driven the search for naturally sourced compounds as substitutes for chemically synthesized counterparts. Research on pigments of natural origin, such as carotenoids, particularly lutein, has been increasing for over three decades. Lutein is recognized for its antioxidant and photoprotective activity. Its ability to cross the blood-brain barrier allows it to act at the eye and brain level and has been linked to benefits for vision, cognitive function and other conditions. While marigold flower is positioned as the only crop from which lutein is extracted from and commercialized, microalgae are proposed as an alternative with several advantages over this terrestrial crop. The main barrier to scaling up lutein production from microalgae to the commercial level is the low productivity compared to the high costs. This review explores strategies to enhance lutein production in microalgae by emphasizing the overall productivity over lutein content alone. Evaluation of how culture parameters, such as light quality, nitrogen sufficiency, temperature and even stress factors, affect lutein content and biomass development in batch phototrophic cultures was performed. Overall, the total lutein production remains low under this metabolic regime due to the low biomass productivity of photosynthetic batch cultures. For this reason, we describe findings on microalgal cultures grown under different metabolic regimes and culture protocols (fed-batch, pulse-feed, semi-batch, semi-continuous, continuous). After a careful literature examination, two-step heterotrophic or mixotrophic cultivation strategies are suggested to surpass the lutein productivity achieved in single-step photosynthetic cultures. Furthermore, this review highlights the urgent need to develop technical feasibility studies at a pilot scale for these cultivation strategies, which will strengthen the necessary techno-economic analyses to drive their commercial production., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Myeloproliferative neoplasms (MPN) are blood cancers that appear after acquiring a driver mutation in a hematopoietic stem cell. These hematological malignancies result in the overproduction of mature blood cells and, if not treated, induce a risk of cardiovascular events and thrombosis. Pegylated IFN$\alpha $ is commonly used to treat MPN, but no clear guidelines exist concerning the dose prescribed to patients. We applied a model selection procedure and ran a hierarchical Bayesian inference method to decipher how dose variations impact the response to the therapy. We inferred that IFN$\alpha $ acts on mutated stem cells by inducing their differentiation into progenitor cells; the higher the dose, the higher the effect. We found that the treatment can induce long-term remission when a sufficient (patient-dependent) dose is reached. We determined this minimal dose for individuals in a cohort of patients and estimated the most suitable starting dose to give to a new patient to increase the chances of being cured., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.)

Spatial omics data allow in-depth analysis of tissue architectures, opening new opportunities for biological discovery. In particular, imaging techniques offer single-cell resolutions, providing essential insights into cellular organizations and dynamics. Yet, the complexity of such data presents analytical challenges and demands substantial computing resources. Moreover, the proliferation of diverse spatial omics technologies, such as Xenium, MERSCOPE, CosMX in spatial-transcriptomics, and MACSima and PhenoCycler in multiplex imaging, hinders the generality of existing tools. We introduce Sopa ( https://github.com/gustaveroussy/sopa ), a technology-invariant, memory-efficient pipeline with a unified visualizer for all image-based spatial omics. Built upon the universal SpatialData framework, Sopa optimizes tasks like segmentation, transcript/channel aggregation, annotation, and geometric/spatial analysis. Its output includes user-friendly web reports and visualizer files, as well as comprehensive data files for in-depth analysis. Overall, Sopa represents a significant step toward unifying spatial data analysis, enabling a more comprehensive understanding of cellular interactions and tissue organization in biological systems., (© 2024. The Author(s).)

Ionizing radiation can have a wide range of impacts on tumor-immune interactions, which are being studied with the greatest interest and at an accelerating pace by the medical community. Despite its undeniable immunostimulatory potential, it clearly appears that radiotherapy as it is prescribed and delivered nowadays often alters the host's immunity toward a suboptimal state. This may impair the full recovery of a sustained and efficient antitumor immunosurveillance posttreatment. An emerging concept is arising from this awareness and consists of reconsidering the way of designing radiation treatment planning, notably by taking into account the individualized risks of deleterious radio-induced immune alteration that can be deciphered from the planned beam trajectory through lymphocyte-rich organs. In this review, we critically appraise key aspects to consider while planning immunologically fitted radiotherapy, including the challenges linked to the identification of new dose constraints to immune-rich structures. We also discuss how pharmacologic immunomodulation could be advantageously used in combination with radiotherapy to compensate for the radio-induced loss, for example, with (i) agonists of interleukin (IL)2, IL4, IL7, IL9, IL15, or IL21, similarly to G-CSF being used for the prophylaxis of severe chemo-induced neutropenia, or with (ii) myeloid-derived suppressive cell blockers., (©2024 The Authors; Published by the American Association for Cancer Research.)

To enhance char formation of flame retardant epoxy (EP) composites, carboxymethyl β-cyclodextrin (CM-β-CD) is employed as an etchant for or ZIF-67 derivatives. In the early stage, etching plays a dominant role. The mismatch in size between CM-β-CD opening and ZIF-67 pore leads to the stacking of carboxyl cobalt complexes on the shell. When the reaction time is prolonged, crosslinking occurs between carboxyl and hydroxyl groups. Crosslinked CM-β-CD weakens and eventually stops the etching process. Triethyl phosphate (TEP), an additive to improve flame retardancy, is also absorbed on the shell in this one-pot synthesis. Herin, the synthesis of metal-organic framework (MOF) derivatives can impart multiple functions to MOF. This novel nanohybrid significantly improved flame retardancy of EP composites with only 2.0 wt% loading. The peak heat release rate (pHRR) and total smoke production (TSP) were reduced by 54.8 and 46.9%, respectively. The integrated multi-element system resulted in an expanded and reinforced char layer. This study proposes a simple and precise method for controlling the structure of MOF-carbohydrate hybrids through competition between chemical reactions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Lignocellulolytic enzymes play a crucial role in efficiently converting lignocellulose into valuable platform molecules in various industries. However, they are limited by their production yields, costs, and stability. Consequently, their production by producers adapted to local environments and the choice of low-cost raw materials can address these limitations. Due to the large amounts of olive stones (OS) generated in Morocco which are still undervalued, Penicillium crustosum , Fusarium nygamai , Trichoderma capillare , and Aspergillus calidoustus , are cultivated under different fermentation techniques using this by-product as a local lignocellulosic substrate. Based on a multilevel factorial design, their potential to produce lignocellulolytic enzymes during 15 days of dark incubation was evaluated. The results revealed that P. crustosum expressed a maximum total cellulase activity of 10.9 IU/ml under sequential fermentation (SF) and 3.6 IU/ml of β-glucosidase activity under submerged fermentation (SmF). F. nygamai recorded the best laccase activity of 9 IU/ml under solid-state fermentation (SSF). Unlike T. capillare , SF was the inducive culture for the former activity with 7.6 IU/ml. A. calidoustus produced, respectively, 1,009 μg/ml of proteins and 11.5 IU/ml of endoglucanase activity as the best results achieved. Optimum cellulase production took place after the 5th day under SF, while ligninases occurred between the 9th and the 11th days under SSF. This study reports for the first time the lignocellulolytic activities of F. nygamai and A. calidoustus . Furthermore, it underlines the potential of the four fungi as biomass decomposers for environmentally-friendly applications, emphasizing the efficiency of OS as an inducing substrate for enzyme production.

Luminescent carbon dots (CDs) were locally synthesized in the core of CYTOP fibers using IR femtosecond laser direct writing (FLDW), a one-step simple method serving as a post-treatment of the pristine fiber. This approach enables the creation of several types of modifications such as ellipsoid voids. The CDs and photoluminescence (PL) distribute at the periphery of the voids. The PL spectral properties were studied through the excitation/emission matrix in the visible range and excitation/emission spectra in the UV/visible range. Our findings reveal the presence of at least three distinct luminescent species, facilitating a broad excitation range extending from UV to green, and light emission spanning from blue to red. The average laser power and dose influence the quantity and ratio of these luminescent CD species. Additionally, we measured the spatially resolved lifetime of the luminescence during and after the irradiation. We found longer lifetimes at the periphery of the laser-induced modified regions and shorter ones closer to the center, with a dominant lifetime ~2 ns. Notably, unlike many other luminophores, these laser-induced CDs are insensitive to oxygen, enhancing their potential for display or data storage applications.

We derive a numerical method based on coupled density functional theory and effective Hamiltonian schemes to calculate the linear and quadratic electro-optic response of ferroelectrics at finite temperature and in different frequency ranges. By applying the developed method to BaTiO&#95;{3}, we successfully resolve apparent discrepancies in the experimental literature that reported a linear or quadratic electro-optic response when visible or terahertz radiation was employed to measure the optical index, respectively. We further demonstrate that (and explain why), in the case of the Ba&#95;{1-x}Sr&#95;{x}TiO&#95;{3} disordered solid solutions, structural phase transitions not only lead to larger linear electro-optic constants, as previously demonstrated in the literature, but also significantly enhance the quadratic electro-optic constants.

Thanks to the Cassini-Huygens space mission between 2004 and 2017, a lot was learned about Titan, the biggest satellite of Saturn, and its intriguing atmosphere, surface, and organic chemistry complexity. However, key questions about the potential for the atmosphere and surface chemistry to produce organic molecules of direct interest for prebiotic chemistry and life did not find an answer. Due to Titan potential as a habitable world, NASA selected the Dragonfly space mission to be launched in 2027 to Titan's surface and explore the Shangri-La surface region for minimum 3 years. One of the main goals of this mission will be to understand the past and actual abundant prebiotic chemistry on Titan, especially using the Dragonfly Mass Spectrometer (DraMS). Two recently used sample pre-treatments for Gas Chromatography - Mass Spectrometry (GC-MS mode of DraMS) analyses are planned prior analysis to extract refractory organic molecules of interest for prebiotic chemistry and astrobiology. The dimethylformamide dimethylacetal (DMF-DMA) derivatization reaction offers undoubtedly an opportunity to detect biosignatures by volatilizing refractory biological or prebiotic molecules and conserving the chiral carbons' conformation while an enantiomeric excess indicates a chemical feature induced primarily by life (and may be aided on the primitive systems by light polarization). The goal of this study is to investigate the ageing of DMF-DMA in DraMS (and likely MOMA) capsules prior to in situ analysis on Titan (or Mars). The main results highlighted by our work on DMF-DMA are first its satisfactory stability for space requirements through time (no significant degradation over a year of storage and less than 30 % of lost under thermal stress) to a wide range of temperature (0 °C to 250 °C), or the presence of water and oxidants during the derivatization reaction (between 0 and 10 % of DMF-DMA degradation). Moreover, this reagent derivatized very well amines and carboxylic acids in high or trace amounts (ppt to hundreds of ppm), conserving their molecular conformation during the heat at 145 °C for 3 min (0 to 4% in the enantiomeric form change)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)