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Abstract For high rate water electrolysers, minimising Ohmic losses through efficient gas bubble evacuation away from the active electrode is as important as minimising activation losses by improving the electrode’s electrocatalytic properties. In this work, by a combined experimental and computational fluid dynamics (CFD) approach, we identify the topological parameters of flow-engineered 3-D electrodes that direct their performance towards enhanced bubble evacuation. In particular, we show that integrating Ni-based foam electrodes into a laterally-graded bi-layer zero-gap cell configuration allows for alkaline water electrolysis to become Proton Exchange Membrane (PEM)-like, even when keeping a state-of-the-art Zirfon diaphragm. Detailed CFD simulations, explicitly taking into account the entire 3-D electrode and cell topology, show that under a forced uniform upstream electrolyte flow, such a graded structure induces a high lateral velocity component in the direction normal to and away from the diaphragm. This work is therefore an invitation to start considering PEM-like cell designs for alkaline water electrolysis as well, in particular the use of square or rectangular electrodes in flow-through type electrochemical cells.

Abstract Reliable automatic diagnosis of Diabetic Retinopathy (DR) and Macular Edema (ME) is an invaluable asset in improving the rate of monitored patients among at-risk populations and in enabling earlier treatments before the pathology progresses and threatens vision. However, the explainability of screening models is still an open question, and specifically designed datasets are required to support the research. We present MAPLES-DR (MESSIDOR Anatomical and Pathological Labels for Explainable Screening of Diabetic Retinopathy), which contains, for 198 images of the MESSIDOR public fundus dataset, new diagnoses for DR and ME as well as new pixel-wise segmentation maps for 10 anatomical and pathological biomarkers related to DR. This paper documents the design choices and the annotation procedure that produced MAPLES-DR, discusses the interobserver variability and the overall quality of the annotations, and provides guidelines on using the dataset in a machine learning context.

Abstract Encephalitis is a rare and potentially fatal manifestation of herpes simplex type 1 infection. Following genome-wide genetic analyses, we identified a previously uncharacterized and very rare heterozygous variant in the E3 ubiquitin ligase WWP2, in a 14-month-old girl with herpes simplex encephalitis. The p.R841H variant (NM_007014.4:c.2522G > A) impaired TLR3 mediated signaling in inducible pluripotent stem cells-derived neural precursor cells and neurons; cells bearing this mutation were also more susceptible to HSV-1 infection compared to control cells. The p.R841H variant increased TRIF ubiquitination in vitro. Antiviral immunity was rescued following the correction of p.R841H by CRISPR-Cas9 technology. Moreover, the introduction of p.R841H in wild type cells reduced such immunity, suggesting that this mutation is linked to the observed phenotypes.

Abstract Background Code-free deep learning (CFDL) is a novel tool in artificial intelligence (AI). This study directly compared the discriminative performance of CFDL models designed by ophthalmologists without coding experience against bespoke models designed by AI experts in detecting retinal pathologies from optical coherence tomography (OCT) videos and fovea-centered images. Methods Using the same internal dataset of 1,173 OCT macular videos and fovea-centered images, model development was performed simultaneously but independently by an ophthalmology resident (CFDL models) and a postdoctoral researcher with expertise in AI (bespoke models). We designed a multi-class model to categorize video and fovea-centered images into five labels: normal retina, macular hole, epiretinal membrane, wet age-related macular degeneration and diabetic macular edema. We qualitatively compared point estimates of the performance metrics of the CFDL and bespoke models. Results For videos, the CFDL model demonstrated excellent discriminative performance, even outperforming the bespoke models for some metrics: area under the precision-recall curve was 0.984 (vs. 0.901), precision and sensitivity were both 94.1% (vs. 94.2%) and accuracy was 94.1% (vs. 96.7%). The fovea-centered CFDL model overall performed better than video-based model and was as accurate as the best bespoke model. Conclusion This comparative study demonstrated that code-free models created by clinicians without coding expertise perform as accurately as expert-designed bespoke models at classifying various retinal pathologies from OCT videos and images. CFDL represents a step forward towards the democratization of AI in medicine, although its numerous limitations must be carefully addressed to ensure its effective application in healthcare.

Abstract Background We designed this study based on both a physician practice survey and real-world patient data to: (1) evaluate clinical management practices in extensive-stage small cell lung cancer (ES-SCLC) among medical centers located across France; and (2) describe first-line treatment patterns among patients with ES-SCLC following the introduction of immunotherapy into clinical practice. Methods A 50-item questionnaire was completed by physicians from 45 medical centers specialized in SCLC management. Responses were collected from June 2022 to January 2023. The survey questions addressed diagnostic workup of ES-SCLC, chemoimmunotherapy in first-line and second-line settings, and use of prophylactic cranial irradiation (PCI) and radiotherapy. In parallel, using a chart review approach, we retrospectively analyzed aggregated information from 548 adults with confirmed ES-SCLC receiving first-line treatment in the same centers. Results In ES-SCLC, treatment planning is based on chest computed tomography (CT) (as declared by 100% of surveyed centers). Mean time between diagnosis and treatment initiation was 2–7 days, as declared by 82% of centers. For detection of brain metastases, the most common imaging test was brain CT (84%). The main exclusion criteria for first-line immunotherapy in the centers were autoimmune disease (87%), corticosteroid therapy (69%), interstitial lung disease (69%), and performance status ≥ 2 (69%). Overall, 53% and 36% of centers considered that patients are chemotherapy-sensitive if they relapse within ≥ 3 months or ≥ 6 months after first-line chemoimmunotherapy, respectively. Among the 548 analyzed patients, 409 (75%) received chemoimmunotherapy as a first-line treatment, 374 (91%) of whom received carboplatin plus etoposide and 35 (9%) cisplatin plus etoposide. Overall, 340/548 patients (62%) received maintenance immunotherapy. Most patients (68%) did not receive radiotherapy or PCI. Conclusions There is an overall alignment of practices reflecting recent clinical guidelines among medical centers managing ES-SCLC across France, and a high prescription rate of immunotherapy in the first-line setting.

Background and purpose: Magnetic resonance imaging (MRI)-to-computed tomography (CT) synthesis is essential in MRI-only radiotherapy workflows, particularly through deep learning techniques known for their accuracy. However, current supervised methods are limited to specific center’s learnings and depend on registration precision. The aim of this study was to evaluate the accuracy of unsupervised and supervised approaches in the context of prostate MRI-to-CT generation for radiotherapy dose calculation. Methods: CT/MRI image pairs from 99 prostate cancer patients across three different centers were used. A comparison between supervised and unsupervised conditional Generative Adversarial Networks (cGAN) was conducted. Unsupervised training incorporates a style transfer method with. Content and Style Representation for Enhanced Perceptual synthesis (CREPs) loss. For dose evaluation, the photon prescription dose was 60 Gy delivered in volumetric modulated arc therapy (VMAT). Imaging endpoint for sCT evaluation was Mean Absolute Error (MAE). Dosimetric endpoints included absolute dose differences and gamma analysis between CT and sCT dose calculations. Results: The unsupervised paired network exhibited the highest accuracy for the body with a MAE at 33.6 HU, the highest MAE was 45.5 HU obtained with unsupervised unpaired learning. All architectures provided clinically acceptable results for dose calculation with gamma pass rates above 94 % (1 % 1 mm 10 %). Conclusions: This study shows that multicenter data can produce accurate sCTs via unsupervised learning, eliminating CT-MRI registration. The sCTs not only matched HU values but also enabled precise dose calculations, suggesting their potential for wider use in MRI-only radiotherapy workflows.

Background and objectivesUp to 46% of patients with presumed autoimmune limbic encephalitis are seronegative for all currently known central nervous system (CNS) antigens. We developed a cell-based assay (CBA) to screen for novel neural antibodies in serum and cerebrospinal fluid (CSF) using neurons and astrocytes derived from human-induced pluripotent stem cells (hiPSCs).MethodsHuman iPSC-derived astrocytes or neurons were incubated with serum/CSF from 99 patients [42 with inflammatory neurological diseases (IND) and 57 with non-IND (NIND)]. The IND group included 11 patients with previously established neural antibodies, six with seronegative neuromyelitis optica spectrum disorder (NMOSD), 12 with suspected autoimmune encephalitis/paraneoplastic syndrome (AIE/PNS), and 13 with other IND (OIND). IgG binding to fixed CNS cells was detected using fluorescently-labeled antibodies and analyzed through automated fluorescence measures. IgG neuronal/astrocyte reactivity was further analyzed by flow cytometry. Peripheral blood mononuclear cells (PBMCs) were used as CNS-irrelevant control target cells. Reactivity profile was defined as positive using a Robust regression and Outlier removal test with a false discovery rate at 10% following each individual readout.ResultsUsing our CBA, we detected antibodies recognizing hiPSC-derived neural cells in 19/99 subjects. Antibodies bound specifically to astrocytes in nine cases, to neurons in eight cases, and to both cell types in two cases, as confirmed by microscopy single-cell analyses. Highlighting the significance of our comprehensive 96-well CBA assay, neural-specific antibody binding was more frequent in IND (15 of 42) than in NIND patients (4 of 57) (Fisher’s exact test, p = 0.0005). Two of four AQP4+ NMO and four of seven definite AIE/PNS with intracellular-reactive antibodies [1 GFAP astrocytopathy, 2 Hu+, 1 Ri+ AIE/PNS)], as identified in diagnostic laboratories, were also positive with our CBA. Most interestingly, we showed antibody-reactivity in two of six seronegative NMOSD, six of 12 probable AIE/PNS, and one of 13 OIND. Flow cytometry using hiPSC-derived CNS cells or PBMC-detected antibody binding in 13 versus zero patients, respectively, establishing the specificity of the detected antibodies for neural tissue.ConclusionOur unique hiPSC-based CBA allows for the testing of novel neuron-/astrocyte-reactive antibodies in patients with suspected immune-mediated neurological syndromes, and negative testing in established routine laboratories, opening new perspectives in establishing a diagnosis of such complex diseases.

Abstract Background Pelvic organ prolapse is a common debilitating condition worldwide. Despite surgical treatment, its recurrence can reach up to 30%. It has multiple risk factors, some of which are particular for a low-resource settings. The identification these factors would help to devise risk models allowing the development of prevention policies. The objective of this study was to explore risk factors for pelvic organ prolapse in a population in eastern Democratic Republic of Congo (DRC). Methods This was an unmatched case-control study conducted between January 2021 and January 2022. The sample size was estimated to be a total of 434 women (217 with prolapse as cases and 217 without prolapse as controls). Data comparisons were made using the Chi-Square and Student T tests. Binary and multivariate logistic regressions were used to determine associated factors. A p

Abstract Cancer cells integrate multiple biosynthetic demands to drive unrestricted proliferation. How these cellular processes crosstalk to fuel cancer cell growth is still not fully understood. Here, we uncover the mechanisms by which the transcription factor Carbohydrate responsive element binding protein (ChREBP) functions as an oncogene during hepatocellular carcinoma (HCC) development. Mechanistically, ChREBP triggers the expression of the PI3K regulatory subunit p85α, to sustain the activity of the pro-oncogenic PI3K/AKT signaling pathway in HCC. In parallel, increased ChREBP activity reroutes glucose and glutamine metabolic fluxes into fatty acid and nucleic acid synthesis to support PI3K/AKT-mediated HCC growth. Thus, HCC cells have a ChREBP-driven circuitry that ensures balanced coordination between PI3K/AKT signaling and appropriate cell anabolism to support HCC development. Finally, pharmacological inhibition of ChREBP by SBI-993 significantly suppresses in vivo HCC tumor growth. Overall, we show that targeting ChREBP with specific inhibitors provides an attractive therapeutic window for HCC treatment.

Extracellular vesicles (EVs) are membrane-bound vesicles secreted by all cell types that play a central role in cell-to-cell communication. Since these vesicles serve as vehicles of cellular content (nucleic acids, proteins and lipids) with the potential to cross biological barriers, they represent a novel attractive window into an otherwise inaccessible organ, such as the brain. The composition of EVs is cell-type specific and mirrors the physiological condition of the cell-of-origin. Consequently, during viral infection, EVs undergo significant changes in their content and morphology, thereby reflecting alterations in the cellular state. Here, we briefly summarize the potential of brain-derived EVs as a lens into viral infection in the central nervous system, thereby: 1) uncovering underlying pathophysiological processes at play and 2) serving as liquid biopsies of the brain, representing a non-invasive source of biomarkers for monitoring disease activity. Although translating the potential of EVs from research to diagnosis poses complexities, characterizing brain-derived EVs in the context of viral infections holds promise to enhance diagnostic and therapeutic strategies, offering new avenues for managing infectious neurological diseases.

Background: MET exon 14 (METex14) skipping mutations are oncogenic drivers observed in approximately 3–4% of non-small cell lung cancers (NSCLC). Several distinct genetic alterations leading to METex14 have been reported but clinical significances of rare mutations are not well defined as well as outcomes of patients upon MET inhibitors (METi). Case presentation: This report presents the case of a patient with metastatic NSCLC harboring an uncommon MET mutational landscape including notably a novel METex14 mutation (R1022L). Dramatic but transient efficacy was observed under crizotinib, due to early occurrence of acquired both on- and off-target mechanisms of resistance such as MET D1246H mutation and wild-type KRAS amplification. Conclusion: Our case provides additional data on MET rare oncogenic variants and their sensitivity to METi. Systematic assessment of post-tyrosine kinase inhibitor tumor sample remains critical to identify on- and off-target mechanisms that may represent therapeutically targetable drivers in resistant patients.

Abstract Background Endometriosis is a chronic disease characterized by growth of endometrial tissue outside the uterine cavity which could affect 200 million women (The term “woman” is used for convenience. Individuals gendered as man or as nonbinary can also suffer from this disease) worldwide. One of the most common symptoms of endometriosis is pelvic chronic pain associated with fatigue. This pain can cause psychological distress and interpersonal difficulties. As for several chronic diseases, adapted physical activity could help to manage the physical and psychological symptoms. The present study will investigate the effects of a videoconference-based adapted physical activity combined with endometriosis-based education program on quality of life, pain, fatigue, and other psychological symptoms and on physical activity. Methods This multicentric randomized-controlled trial will propose to 200 patients with endometriosis to be part of a trial which includes a 6-month program with 45 min to more than 120 min a week of adapted physical activity and/or 12 sessions of endometriosis-based education program. Effects of the program will be compared to a control group in which patients will be placed on a waiting list. All participants will be followed up 3 and 6 months after the intervention. None of the participants will be blind to the allocated trial arm. The primary outcome measure will be quality of life. Secondary outcomes will include endometriosis-related perceived pain, fatigue, physical activity, and also self-image, stereotypes, motivational variables, perceived support, kinesiophobia, basic psychological need related to physical activity, and physical activity barriers. General linear models and multilevel models will be performed. Predictor, moderator, and mediator variables will be investigated. Discussion This study is one of the first trials to test the effects of a combined adapted physical activity and education program for improving endometriosis symptoms and physical activity. The results will help to improve care for patients with endometriosis. Trial registration ClinicalTrials.gov, NCT05831735 . Date of registration: April 25, 2023

Abstract Background The use of naso‐esophageal feeding tubes (NFT) at home could represent an alternative way to reduce the costs for owners and facilitate enteral feeding until recovery of a spontaneous appetite. Objective To describe the use of NFT at home in dogs and cats and evaluate the satisfaction of owners and their capacity to handle the device. Animals One hundred nineteen client‐owned animals (90 cats and 29 dogs) which remained anorexic during hospitalization and were discharged with NFT for at least 24 hours after placement. Methods Medical records were reviewed retrospectively, and owners were contacted by telephone calls. Complications were reported according to their relative severity (minor and major). Owners were asked to report their experience and comfort with NFT management. Results Naso‐esophageal feeding tubes were kept in place at home for a median of 6 days (range, 1‐17) and 62.2% (95% confidence interval [CI]: 53.3‐70.7) of animals recovered a spontaneous appetite while wearing NFT, 60% (95% CI: 44.4‐75.6) of the remaining animals recovered a spontaneous appetite after removal. Overall complication rate was 65.5% (95% CI: 57.0‐74.0), but only 18.5% (95% CI: 11.5‐25.5) required a consultation and no life‐threatening complication occurred. Owners were satisfied in 94.1% (95% CI: 89.9‐98.3) of cases. Conclusion and Clinical Importance Although most animals discharged with NFT at home presented complications, no major adverse effects were reported and NFT were easily handled by owners. This study provides evidence that NFT can be well tolerated at home.

Abstract Noncardiogenic pulmonary edema (NCPE) in hunting dogs is an uncommon and poorly described condition for which no preventive treatment is available. Two dogs were presented for recurrent respiratory distress strictly associated with hunting activities. Diagnosis was based on bilateral, symmetrical, interstitial‐to‐alveolar pattern in the caudodorsal lung fields on thoracic radiographs, exclusion of other causes, and spontaneous clinical and radiographic improvement. Considering that the pathogenesis of exercise‐induced NCPE likely involves α‐ and β‐adrenergic overstimulation, treatment with sympathetic blockers was used in both dogs. The first dog no longer showed respiratory signs during hunting activities. However, treatment failed to prevent respiratory distress in the other dog. Based on the large number of red blood cells in the bronchoalveolar lavage fluid of the second dog, exercise‐induced pulmonary hemorrhage was suspected, as described in racing horses. The loop diuretic furosemide successfully prevented further hunting‐associated respiratory distress episodes in this dog.

Abstract Background As a consequence of SARS-CoV-2 infection various neurocognitive and neuropsychiatric symptoms can appear, which may persist for several months post infection. However, cell type-specific routes of brain infection and underlying mechanisms resulting in neuroglial dysfunction are not well understood. Methods Here, we investigated the susceptibility of cells constituting the blood-brain barrier (BBB) and the blood-cerebrospinal fluid barrier (BCSFB) of the choroid plexus (ChP) to SARS-CoV-2 infection using human induced pluripotent stem cell (hiPSC)-derived cellular models and a ChP papilloma-derived epithelial cell line as well as ChP tissue from COVID-19 patients, respectively. Results We noted a differential infectibility of hiPSC-derived brain microvascular endothelial cells (BMECs) depending on the differentiation method. Extended endothelial culture method (EECM)-BMECs characterized by a complete set of endothelial markers, good barrier properties and a mature immune phenotype were refractory to SARS-CoV-2 infection and did not exhibit an activated phenotype after prolonged SARS-CoV-2 inoculation. In contrast, defined medium method (DMM)-BMECs, characterized by a mixed endothelial and epithelial phenotype and excellent barrier properties were productively infected by SARS-CoV-2 in an ACE2-dependent manner. hiPSC-derived brain pericyte-like cells (BPLCs) lacking ACE2 expression were not susceptible to SARS-CoV-2 infection. Furthermore, the human choroid plexus papilloma-derived epithelial cell line HIBCPP, modeling the BCSFB was productively infected by SARS-CoV-2 preferentially from the basolateral side, facing the blood compartment. Assessment of ChP tissue from COVID-19 patients by RNA in situ hybridization revealed SARS-CoV-2 transcripts in ChP epithelial and ChP stromal cells. Conclusions Our study shows that the BCSFB of the ChP rather than the BBB is susceptible to direct SARS-CoV-2 infection. Thus, neuropsychiatric symptoms because of COVID-19 may rather be associated with dysfunction of the BCSFB than the BBB. Future studies should consider a role of the ChP in underlying neuropsychiatric symptoms following SARS-CoV-2 infection.

The noise reduction effect of noise barriers has been extensively studied, but the effect on pollutant dispersion remains unclear. A computational fluid dynamics (CFD) simulation is conducted to investigate the effects of different heights, lengths, and types of noise barriers and different wind speeds on pollutant dispersion in street canyons with viaducts. The field synergy theory of the convective mass transfer process is used for quantitative analysis of pollutant dispersion in street canyons. The results show that as the height and length of the noise barrier increase, the pollutant dispersion capacity decreases. As the wind speed increases, the rate of decrease in the average CO concentration declines. The effect of the wind speed on the synergistic improvement of the speed and concentration gradient vectors differs for different types of noise barriers. The performance follows the order: fully-closed noise barrier > left noise barrier > right noise barrier > semi-closed noise barrier. The different noise barrier types significantly impact the flow field and pollutant dispersion and reduce the CO concentration to varying degrees, except for the fully-closed type. The average CO concentration in the pedestrian breathing zone is reduced by a maximum of 55.85% on the leeward side and by 53% on the windward side, indicating that an appropriate noise barrier on the viaduct reduces noise pollution and improves the air quality in street canyons, especially in the pedestrian breathing zone.

The detection of contrast-enhancing lesions (CELs) is fundamental for the diagnosis and monitoring of patients with multiple sclerosis (MS). This task is time-consuming and suffers from high intra- and inter-rater variability in clinical practice. However, only a few studies proposed automatic approaches for CEL detection. This study aimed to develop a deep learning model that automatically detects and segments CELs in clinical Magnetic Resonance Imaging (MRI) scans. A 3D UNet-based network was trained with clinical MRI from the Swiss Multiple Sclerosis Cohort. The dataset comprised 372 scans from 280 MS patients: 162 showed at least one CEL, while 118 showed no CELs. The input dataset consisted of T1-weighted before and after gadolinium injection, and FLuid Attenuated Inversion Recovery images. The sampling strategy was based on a white matter lesion mask to confirm the existence of real contrast-enhancing lesions. To overcome the dataset imbalance, a weighted loss function was implemented. The Dice Score Coefficient and True Positive and False Positive Rates were 0.76, 0.93, and 0.02, respectively. Based on these results, the model developed in this study might well be considered for clinical decision support.

Synchrotron Microbeam Radiation Therapy (MRT) has repeatedly proven its superiority compared with conventional radiotherapy for glioma control in preclinical research. The clinical transfer phase of MRT has recently gained momentum; seven dogs with suspected glioma were treated under clinical conditions to determine the feasibility and safety of MRT. We administered a single fraction of 3D-conformal, image-guided MRT. Ultra-high-dose rate synchrotron X-ray microbeams (50 µm-wide, 400 µm-spaced) were delivered through five conformal irradiation ports. The PTV received ~25 Gy peak dose (within microbeams) per port, corresponding to a minimal cumulated valley dose (diffusing between microbeams) of 2.8 Gy. The dogs underwent clinical and MRI follow-up, and owner evaluations. One dog was lost to follow-up. Clinical exams of the remaining six dogs during the first 3 months did not indicate radiotoxicity induced by MRT. Quality of life improved from 7.3/10 [±0.7] to 8.9/10 [±0.3]. Tumor-induced seizure activity decreased significantly. A significant tumor volume reduction of 69% [±6%] was reached 3 months after MRT. Our study is the first neuro-oncologic veterinary trial of 3D-conformal Synchrotron MRT and reveals that MRT does not induce acute to subacute radiotoxicity in normal brain tissues. MRT improves quality of life and leads to remarkable tumor volume reduction despite low valley dose delivery. This trial is an essential step towards the forthcoming clinical application of MRT against deep-seated human brain tumors.

This paper describes the objectives and results of a joint European project named FLYING WAFER. The goal of the project was to provide a methodology for interlinking European R&D centers in micro and nano technologies to a distributed 300-mm CMOS R&D line. The project was carried out as a feasibility study. Therefore, the results provide a model and concept which has the potential of guaranteeing a safe and fast exchange of wafers and data between European R&D nodes to allow multisite processing. An implementation phase is planned as a second step. Index Terms--Multisite processing, nanotechnology, semiconductor manufacturing, 300 mm.