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Abstract Background Essential oils of Cymbopogon citratus and Hyptis suaveolens are known for their insecticidal properties, but remain ineffective against mosquitoes resistant to synthetic insecticides. In order to improve insecticidal properties of these plants, this study aimed to investigate the chemical composition and insecticidal activity against Anopheles gambiae mosquitoes of essential oil obtained by co-distillation of dry leaves of C. citratus and H. suaveolens. Methods Essential oils were extracted by hydrodistillation from dry leaves of C. citratus and H. suaveolens, separately, then from the mixture of the dry leaves of the two plants in mass ratio 50/50. Each pure essential oil and the mixture obtained either by co-distillation or by combining pure essential oils in volume ratio 50/50 were then analysed by GC/MS. All essential oils and Deltamethrin 0.05% (positive control) were tested on two species of mosquitoes of the genus Anopheles gambiae according to the World Health Organization standard methods. Results Essential oil obtained by co-distillation mainly contained piperitone (40.80%), 1,8-cineole (24.64%), p-menth-4(8)-ene (13.20%), limonene (6.09%) and α-pinene (4.73%). However, the mixture of pure essential oils of these two plants mostly contained geranial (20.74%), neral (16.42%), 1,8-cineole (19.79%), sabinene (6.03%) and β-pinene (3.87%). The essential oil of C. citratus mainly contained geranial (41.49%), neral (32.83%), β-myrcene (13.66%) and geraniol (3.49%) while the major constituents of essential oil of H. suaveolens were 1,8-cineole (39.58%), sabinene (12.06%), β-pinene (7.73%), α-terpinolene (6.72%) and (E)-caryophyllene (7.49%). At the dose of 1%, all essential oils, except that of H. suaveolens, induced about 100% of mortality on the sensitive species of An. gambiae. However, on the resistant species at the same dose, the essential oil obtained by co-distillation induced the highest mortality (53.44%). The essential oils of C. citratus, H. suaveolens and the mixture of the two pure essential oils caused respectively 2.47, 15.28 and 18.33% of mortality. The synthetic insecticide caused 100 and 14.84% of mortality respectively on the sensitive and resistant species of An. gambiae. Conclusion Essential oil obtained by co-distillation showed good insecticidal efficacy against a resistant species of An. gambiae and might constitute a new solution to fight against mosquitoes resistant to synthetic insecticides.

Abstract Cardiorenal fibrosis is a common feature of chronic cardiovascular disease and recent data suggests that cytokines and chemokines may also drive fibrosis. Here we tested the hypothesis that CXCR7, a highly conserved chemokine receptor, contributes to cardiac and renal fibrosis. We generated an anti-mouse CXCR7-specific monoclonal antibody (CXCR7 mAb) and tested its anti-fibrotic actions in cardiorenal fibrosis induced using the deoxycorticosterone acetate/uni-nephrectomy (DOCA-UNX) model. CXCR7 mAb treatment (10 mg/kg, twice weekly for 6 weeks) significantly attenuated the development of cardiac and renal fibrosis, and reduced fibrotic and inflammatory gene expression levels, in the absence of an effect on blood pressure. Immunohistochemical analysis demonstrated an increase in the vascular expression of CXCR7 in DOCA-UNX-treated mice. This study demonstrated that a CXCR7 mediated pathway plays a significant role in cardiac and renal fibrosis induced by DOCA-UNX treatment. Accordingly, antagonism of CXCR7 may provide a therapeutic opportunity to mitigate against fibrosis in the setting of mineralocorticoid excess.

Abstract Objective Memory is one of the most sensitive markers of cognitive compromise in people with new‐onset epilepsy. Nonetheless, around half of these cases score within the normal range on standard memory testing. Here we explore whether memory retention at a 1‐week delay reveals otherwise undetected memory compromise in such individuals, and how it relates to subjective memory complaints and mood. Methods Using a prospective design, 38 adults with new‐onset epilepsy underwent baseline memory screening via telephone using an abbreviated Rey Auditory Verbal Learning Test (RAVLT). Psychological screening occurred via online questionnaires. One week later, without forewarning, participants completed three follow‐up memory tasks. Of particular focus, we explored longer‐term memory performances and forgetting trajectories in those individuals (n = 23) who demonstrated normal memory performances (scores >10th percentile) at baseline (30‐min delay). Outcomes were compared to 32 healthy controls, matched for age, sex, and education. Results As a group, people with epilepsy performed worse than controls on all memory measures, with 44 percent impaired at baseline testing. Of those unimpaired at baseline, the rate and volume of information loss over 1 week was significantly greater than for controls. Contextual memory performance at 1 week was also significantly poorer for people with epilepsy. At the individual level, the prevalence of impaired forgetting was not significantly different between patients and controls. Subjective memory complaints were not related to any objective tests but were strongly related to self‐reported mood and anxiety symptoms. Significance People with new‐onset epilepsy show reduced memory at short and extended intervals. For those showing normal memory at baseline, information does appear to be forgotten more quickly than in healthy controls, though the effect is not large. The findings indicate that while extended delay memory testing is not essential in all new epilepsy cases, it could provide useful information for particular individuals. Plain Language Statement Memory problems are common in people with epilepsy shortly after seizure onset, however, many individuals still show normal memory performances on standard neuropsychological testing. Through testing memory at an extended timepoint (1 week), our study found that on average, these individuals showed a slightly quicker rate of forgetting over a 1‐week period than people without a brain condition. Self‐reported memory complaints in people with new epilepsy were unrelated to their actual memory skills on testing at short and long timepoints but were rather linked to lower mood and quality of life.

Abstract Metastatic urothelial carcinoma (mUC) is a lethal cancer, with limited therapeutic options. Large-scale studies in early settings provided critical insights into the genomic and transcriptomic characteristics of non-metastatic UC. The genomic landscape of mUC remains however unclear. Using Whole Exome (WES) and mRNA sequencing (RNA-seq) performed on metastatic biopsies from 111 patients, we show that driver genomic alterations from mUC were comparable to primary UC (TCGA data). APOBEC, platin, and HRD mutational signatures are the most prevalent in mUC, identified in 56%, 14%, and 9% of mUC samples, respectively. Molecular subtyping using consensus transcriptomic classification in mUC shows enrichment in neuroendocrine subtype. Paired samples analysis reveals subtype heterogeneity and temporal evolution. We identify potential therapeutic targets in 73% of mUC patients, of which FGFR3 (26%), ERBB2 (7%), TSC1 (7%), and PIK3CA (13%) are the most common. NECTIN4 and TACSTD2 are highly expressed regardless of molecular subtypes, FGFR3 alterations and sites of metastases.

Abstract Aims Diagnosing acute heart failure (AHF) remains particularly challenging in older patients. Natriuretic peptides are recommended as valuable diagnostic tools in this context. This study aims to establish the diagnostic thresholds of B‐type natriuretic peptide (BNP) and N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) for AHF in patients aged over 75 years, both with and without co‐morbidities. Methods and results In this retrospective longitudinal multicentre cohort study, data were gathered from 12 071 hospitalized patients aged 75 years or older, presenting with acute dyspnoea and undergoing BNP or NT‐proBNP measurement within 48 h of admission across 10 Assistance Publique‐Hôpitaux de Paris facilities between 2011 and 2022, encompassing geriatrics, cardiology, and pulmonology departments. Final diagnoses were categorized using ICD‐10 criteria as either AHF or other acute respiratory conditions such as COPD exacerbation, pulmonary embolism, and pneumonia. The mean (SD) age of the population was 84.0 (80.0, 89.0) years, with 52.7% being female. Out of these, 7946 (65.8%) were diagnosed with AHF upon discharge. For NT‐proBNP, the identified ‘optimal’ threshold for diagnosing AHF was 1748 ng/L, with a positive predictive value (PPV) of 84%. Among patients aged over 85 years, a threshold of 2235 pg/mL for NT‐proBNP was associated with an 84% PPV. In patients with atrial fibrillation (AF), a threshold of 2332 pg/mL for NT‐proBNP demonstrated a PPV of 90% for AHF diagnosis. Additionally, in patients with an estimated glomerular filtration rate (eGFR)

Abstract Antibody-dependent complement activation plays a key role in the natural human immune response to infections. Currently, the understanding of which antibody-antigen combinations drive a potent complement response on bacteria is limited. Here, we develop an antigen-agnostic approach to stain and single-cell sort human IgG memory B cells recognizing intact bacterial cells, keeping surface antigens in their natural context. With this method we successfully identified 29 antibodies against K. pneumoniae, a dominant cause of hospital-acquired infections with increasing antibiotic resistance. Combining genetic tools and functional analyses, we reveal that the capacity of antibodies to activate complement on K. pneumoniae critically depends on their antigenic target. Furthermore, we find that antibody combinations can synergistically activate complement on K. pneumoniae by strengthening each other’s binding in an Fc-independent manner. Understanding the molecular basis of effective complement activation by antibody combinations to mimic a polyclonal response could accelerate the development of antibody-based therapies against problematic infections.

Introduction Smoking elevates catecholamines that increase the risk for cardiovascular disease. Sparse evidence exists about the effects of e-cigarettes and catecholamines. Higher levels of catecholamines could trigger the increased heart rate, blood pressure, and decreased vascular function reported with the use of e-cigarettes. We investigated the difference in urinary catecholamines and their metabolites before and after the use of an e-cigarette containing nicotine or cigarettes compared to no tobacco use. Methods In our observational cohort exposure study, healthy adults aged 21– 45 years who were currently using e-cigarettes, cigarettes, or had never used tobacco, participated in an acute exposure visit using their most common tobacco product. Urine was collected before, 1, and 2 hours after a 3-second puff every 30 seconds for 10 minutes on an e-cigarette or straw or use of 1 cigarette. Urinary catecholamines and their metabolites were measured by ultra-high-performance liquid chromatography. Participants (n=323) were grouped by the product used at the visit. We compared levels of creatinine normalized log-transformed urinary catecholamines and their metabolites across groups using Dunn’s test following a Kruskal-Wallis test in unadjusted and demographically adjusted models. Results Prior to use, individuals who used cigarettes (n=70) had lower urinary metabolites from epinephrine, serotonin, and norepinephrine. No differences were seen in those who used e-cigarettes (n=171) and those who did not use tobacco (n=82). In fully adjusted models, 1 h after the use of a combustible or e-cigarette, log-transformed urinary metabolites from norepinephrine (β=1.22; 95% CI: 0.39– 2.05, p=0.004 and β=1.06; 95% CI: 0.39–1.74, p=0.002), dopamine (β=0.37; 95% CI: 0.24–0.5, p

Abstract Background Colostrum is the first milk for a newborn. Its high content in microbiota shaping compounds and its intake at the time of gut microbiota seeding suggests colostrum may be critical in the establishment of a healthy microbiota. There is also accumulating evidence on the importance of the gut microbiota for healthy growth. Here, we aimed to investigate the contribution of colostrum, and colostrum-induced microbiota to growth promotion. Addressing this question is highly significant because (1) globally, less than half of the newborns are fully colostrum fed (2) the evidence for the importance of the microbiota for the prevention of undernutrition has only been demonstrated in juvenile or adult pre-clinical models while stunting already starts before weaning. Results To address the importance of diet at birth in growth failure, we developed a unique mouse model in which neonates are breastfed by mothers at an advanced stage of lactation who no longer provide colostrum. Feeding newborn mice with mature milk instead of colostrum resulted in significant growth retardation associated with the biological features of chronic undernutrition, such as low leptin levels, dyslipidemia, systemic inflammation, and growth hormone resistance. We next investigated the role of colostrum in microbiota shaping. At the end of the lactation period, we found a major difference in gut microbiota alpha diversity, beta diversity, and taxa distribution in control and colostrum-deprived mice. To determine the causal relationship between changes in microbiota and growth trajectories, we repeated our experiment in germ-free mice. The beneficial effect of colostrum on growth remained in the absence of microbiota. Conclusion Our data suggest that colostrum may play an important role in the prevention of growth failure. They highlight that the interplay between neonatal gut microbiome assembly and diet may not be as crucial for growth control in the developing newborn as described in young adults. This opens a paradigm shift that will foster research for colostrum’s bioactives that may exert a similar effect to microbiota-derived ligands in promoting growth and lead to new avenues of translational research for newborn-tailored prevention of stunting. Video Abstract

Abstract The recent SarsCov2 pandemic has disrupted healthcare system notably impacting intensive care units (ICU). In severe cases, the immune system is dysregulated, associating signs of hyperinflammation and immunosuppression. In the present work, we investigated, using a joint modeling approach, whether the trajectories of cellular immunological parameters were associated with survival of COVID‐19 ICU patients. This study is based on the REA‐IMMUNO‐COVID cohort including 538 COVID‐19 patients admitted to ICU between March 2020 and May 2022. Measurements of monocyte HLA‐DR expression (mHLA‐DR), counts of neutrophils, of total lymphocytes, and of CD4+ and CD8+ subsets were performed five times during the first month after ICU admission. Univariate joint models combining survival at day 28 (D28), hospital discharge and longitudinal analysis of those biomarkers’ kinetics with mixed‐effects models were performed prior to the building of a multivariate joint model. We showed that a higher mHLA‐DR value was associated with a lower risk of death. Predicted mHLA‐DR nadir cutoff value that maximized the Youden index was 5414 Ab/C and led to an AUC = 0.70 confidence interval (95%CI) = [0.65; 0.75] regarding association with D28 mortality while dynamic predictions using mHLA‐DR kinetics until D7, D12 and D20 showed AUCs of 0.82 [0.77; 0.87], 0.81 [0.75; 0.87] and 0.84 [0.75; 0.93]. Therefore, the final joint model provided adequate discrimination performances at D28 after collection of biomarker samples until D7, which improved as more samples were collected. After severe COVID‐19, decreased mHLA‐DR expression is associated with a greater risk of death at D28 independently of usual clinical confounders.

Abstract The interferometric control of dissipation in a two-port system is a fruitful concept enabling the enhancement or cancellation of the input amplitudes as a function of their relative phases. Here, beyond the canonical configuration of Coherent Perfect Absorption (CPA), we apply this concept to two simultaneously excited strongly-coupled nanoscale electromechanical resonators submitted to independently controlled phase-shifted excitations. Both subsystems are read simultaneously by optical means allowing us to completely reconstruct the signature of coherent annihilation or amplification on both quadrature. We evidence that the mechanical modes amplitude can be enhanced or inhibited with respect to the case of single port excitation while phase experiences strong variations with the excitation imbalance and phase difference. Meanwhile, phase singularities with opposite topological charges are observed for mechanical normal modes. Close to the phase singularity, we demonstrate that the input of a weak phase modulation induces a large, pure phase modulation of the normal mode. These experimental demonstrations are fully modelled via the mechanical dynamical equations of our system. The interferometric control may open avenues for low-power amplitude controlled phase modulation schemes and vice-versa for potential switches and logical gates.

Abstract Background Bacterial infection plays an important role in persistent periapical lesions and inadequate disinfection of root canals is considered the biggest factor responsible for endodontic treatment failure. Antimicrobial Photodynamic Therapy (aPDT) has become the latest choice to eradicate microorganisms in root canals. Objective This study aims to evaluate the effectiveness of Antimicrobial Photodynamic Therapy (aPDT) in bacterial count reduction compared to Passive Ultrasonic Activation (PUI) and Ca(OH)2 dressings. Materials and methods Forty-five anterior single canal teeth with medium-sized periapical lesions (2–5 mm) were divided into three groups according to the disinfecting technique (each group consists of 15 canals with 1:1:1 allocation ratio): Group A: Ca(OH)2 dressing. Group B: Passive Ultrasonic Activation (PUI). Group C: Antimicrobial Photodynamic Therapy (aPDT). Direct bacterial viable count method was used to count the colonies forming units (CFU) before and after the disinfecting and the bacterial count reduction was estimated, the statistical analysis was performed at a 95% confidence level using the Chi-square and Mann–Whitney U test. Results aPDT showed no statistically significant difference when compared to passive ultrasonic irrigation (P > 0.05) but showed higher and more promising results when compared to Ca(OH)2 dressings (P

Mixtures of chemical contaminants can pose a significant health risk to humans and wildlife, even at levels considered safe for each individual chemical. There is a critical need to develop statistical methods to evaluate the drivers of toxic effects in chemical mixtures (i.e., bad actors) from exposure studies. Here, we develop a hierarchical modeling framework to disentangle the toxicity of complex metal mixtures from a screening study of 92 drinking well water samples containing multiple metal elements from Maine and New Hampshire, USA. In order to screen for neurodevelopmental impacts from exposure to these drinking water samples, we use a larval zebrafish (Danio rerio) behavioral assay. Zebrafish are an advantageous toxicological model organism due to combining the complexity of a vertebrate organism and higher-throughput exposure methods. We formulate a linear mixed modeling approach that captures intrinsic complexity in a common larval behavioral assay in order to improve its sensitivity and rigor and identify drivers of behavioral toxicity from the metal mixtures within the drinking water samples. Our analysis identifies lead (Pb), cadmium (Cd), nickel (Ni), copper (Cu), barium (Ba), and uranium (U) as metals that consistently impact larval locomotor activity, individually and across nine pairs of those metals. Our model also elucidates three distinct clusters of metal mixture components that drive behavioral effects: (Ba:Cu:U), (Ni:Pb:U), (Ba:Pb:U). Having identified a set of “bad-actor” metals from the water samples, we conduct exposure experiments for each individual metal (Pb, Cd, Ni, Cu, and Ba) at levels considered safe by the US Environmental Protection Agency drinking water regulatory limits and validate Pb, Ni, Cu, and Ba as behavioral toxicants at these concentrations. Collectively, our modeling approach estimates the impact of metal elements on a complex behavioral outcome in a statistically robust manner and establishes an approach to capture “bad actors” and key chemical interactions in a complex mixture.

Daratumumab-based treatment could control severe, treatment-refractory, life-threatening angioedema due to acquired C1-inhibitor deficiency associated with monoclonal gammopathy.

The present study sought to replicate two non-intuitive effects reported in the literature on lateral manual interception of uniformly moving targets, the angle-of-approach (AoA) effect and the reversal-movement (RM) effect. Both entail an influence of the target trajectory’s incidence angle on the observed interceptive hand movements along the interception axis; they differ in the interception location considered. The AoA effect concerns all trajectory conditions requiring hand movement to allow successful interception, while the RM effect concerns the particular condition where the target will in fact arrive at the hand’s initial position and no hand movement is therefore required but nevertheless regularly produced. Whereas the AoA effect has been systematically replicated, the RM effect has not. To determine whether the RM effect is in fact a reproducible phenomenon, we deployed a procedure enhancing the uncertainty about the target’s future arrival locations with respect to the hand’s initial position and included low-to-high target motion speeds. Results demonstrated the presence of both the AoA effect and the RM effect. The AoA effect was observed for all relevant interception locations, with the effect being stronger for the farther interception locations and the lower target speeds. The RM effect, with the hand first moving away from its initial position, in the direction of the target, before reversing direction, was observed in a higher proportion of trials for target trajectories with larger incidence angles and lower speeds. Earlier initiation gave rise to reversal movements of larger amplitude. Both effects point to visual guidance of hand movement partially based in reliance on information with respect to current lateral ball position. We conclude that the information used in lateral manual interception is of an intermediate order, which can be conceived as resulting from a partial combination of target position and velocity information or information in the form of a fractional order derivative.

This embedded single-case study investigates four secondary school L2 teachers’ perceptions of metacognitive oracy instruction (MOI) over a two-year Design-Based Research (DBR) project and examines the effects of the project on their declared practices almost a year after its completion. Questionnaires, learner notes, and interviews to the double were used to collect data. Data analysis included descriptive statistics, content analysis, and thematic analysis. The results indicate that the DBR project had an overall positive effect on three of the four teachers’ perceptions of MOI. The study also found a link between the teachers’ perceptions of MOI and their self-reported implementation in practice. The findings highlight difficulties teachers face in developing metacognitive practices, even when they believe in their efficacy and intend to implement them. The study offers insights into language teachers’ adoption of metacognitive practices through DBR and can serve to inform teacher educators and researchers.

Temporal lobe epilepsy (TLE) is a type of focal epilepsy characterized by spontaneous recurrent seizures originating from the hippocampus. The epigenetic reprogramming hypothesis of epileptogenesis suggests that the development of TLE is associated with alterations in gene transcription changes resulting in a hyperexcitable network in TLE. DNA 5-methylcytosine (5-mC) is an epigenetic mechanism that has been associated with chronic epilepsy. However, the contribution of 5-hydroxymethylcytosine (5-hmC), a product of 5-mC demethylation by the Ten-Eleven Translocation (TET) family proteins in chronic TLE is poorly understood. 5-hmC is abundant in the brain and acts as a stable epigenetic mark altering gene expression through several mechanisms. Here, we found that the levels of bulk DNA 5-hmC but not 5-mC were significantly reduced in the hippocampus of human TLE patients and in the kainic acid (KA) TLE rat model. Using 5-hmC hMeDIP-sequencing, we characterized 5-hmC distribution across the genome and found bidirectional regulation of 5-hmC at intergenic regions within gene bodies. We found that hypohydroxymethylated 5-hmC intergenic regions were associated with several epilepsy-related genes, including Gal, SV2, and Kcnj11 and hyperdroxymethylation 5-hmC intergenic regions were associated with Gad65, TLR4, and Bdnf gene expression. Mechanistically, Tet1 knockdown in the hippocampus was sufficient to decrease 5-hmC levels and increase seizure susceptibility following KA administration. In contrast, Tet1 overexpression in the hippocampus resulted in increased 5-hmC levels associated with improved seizure resiliency in response to KA. These findings suggest an important role for 5-hmC as an epigenetic regulator of epilepsy that can be manipulated to influence seizure outcomes.

Sweet cherry pits, date seeds, and grape seeds are abundant fruit by-products in the Mediterranean region. Assessing their antioxidant capacity is crucial for their valorization. Grape and date seeds exhibited higher concentrations of total phenolic and flavonoid contents, and significant antioxidant capacity. Epicatechin was the main flavonoid in sweet cherry pits and date seeds (29–85 mg/g), while vanillic acid was the predominant phenolic acid across all by-products (5–23 mg/g). However, some sweet cherry pit varieties exceeded Maximum Residue Levels (MRL) for five pesticides, while grape seeds contained thirteen fungicide residues, all below MRL. Ochratoxin A was detected in one date seed but below the limit of quantification. Additionally, grape seeds showed an Al content of approximately 130 mg/kg, along with levels of As, Cd, and Pb. Date seeds exhibited high potential for food and pharmaceutical applications, pending evaluation for chemical contaminants.

A pitaieira (Hylocereus polyrhizus) é uma cactácea com grande destaque no mercado de frutas atual. Possui elevada rusticidade e tolerância às condições edafoclimáticas adversas possuindo potencial para o seu cultivo nas regiões semiáridas. Apesar de ser pouco acometida por pragas, a sua exploração comercial pode ser prejudicada se medidas de controle não forem realizadas. Ademais, produtos fitossanitários não foram registrados para o controle de pragas nesta cultura. Devido a isto, o conhecimento de insetos que acometem esta cultura é de fundamental importância para o seu correto controle e o sucesso produtivo do pomar. O objetivo deste estudo foi realizar um levantamento entomofaunístico visando avaliar a ocorrência de insetos danosos em um pomar de pitaia implantado no sertão Pernambucano. A avaliação ocorreu por meio de registros fotográficos, coleta e identificação dos insetos por meio de dados na literatura. Os registros e coletas foram realizadas unicamente no período diurno. Os insetos observados foram: lagarta Aricoris campestris (Bates, 1868) (Lepidoptera: Riodinidae), formiga Atta sexdens rubropilosa (Forel, 1908) (Hymenoptera: Formicidae), arapuá Trigona spinipes (Fabricius, 1793) (Hymenoptera: Apidae), pulgão Myzus persicae (Sulzer, 1776) (Hemiptera: Aphididae). Este trabalho relata o primeiro registro de lagartas de A. campestris, formiga, arapuá e pulgão causando danos na pitaieira.

The aim of this study is to propose a model for predicting the mechanical properties of natural sisal yarn based on mechanical strength of used fibers, unit twist of yarn and its density. To achieve this, a complete factorial design modelling method was used, based on a design of experiments approach, which is recommended today because of the ease it offers in taking into account the most complex phenomena. It was developed on the basis of laboratory tests. The model obtained predicts mechanical strength and elasticity modulus of sisal yarn, based on control parameters such as fiber strength, unit twist and yarn mass. This model is currently one of the most accurate tools for predicting and optimising the mechanical properties of sisal yarns. The iso-surface curves represented by this model, can be used to obtain the strength and elasticity modulus of sisal yarn during manufacture, by varying the optimum control parameters. This model is an original tool that can be recommended to the spinning and sisal fiber composite manufacturing industries and others, as it saves time and materials and ensures precision in the manufacture of yarns according to the field of application, thereby contributing to safety in use.

Abstract Background Early life environmental stressors play an important role in the development of multiple chronic disorders. Previous studies that used environmental risk scores (ERS) to assess the cumulative impact of environmental exposures on health are limited by the diversity of exposures included, especially for early life determinants. We used machine learning methods to build early life exposome risk scores for three health outcomes using environmental, molecular, and clinical data. Methods In this study, we analyzed data from 1622 mother-child pairs from the HELIX European birth cohorts, using over 300 environmental, 100 child peripheral, and 18 mother-child clinical markers to compute environmental-clinical risk scores (ECRS) for child behavioral difficulties, metabolic syndrome, and lung function. ECRS were computed using LASSO, Random Forest and XGBoost. XGBoost ECRS were selected to extract local feature contributions using Shapley values and derive feature importance and interactions. Results ECRS captured 13%, 50% and 4% of the variance in mental, cardiometabolic, and respiratory health, respectively. We observed no significant differences in predictive performances between the above-mentioned methods.The most important predictive features were maternal stress, noise, and lifestyle exposures for mental health; proteome (mainly IL1B) and metabolome features for cardiometabolic health; child BMI and urine metabolites for respiratory health. Conclusions Besides their usefulness for epidemiological research, our risk scores show great potential to capture holistic individual level non-hereditary risk associations that can inform practitioners about actionable factors of high-risk children. As in the post-genetic era personalized prevention medicine will focus more and more on modifiable factors, we believe that such integrative approaches will be instrumental in shaping future healthcare paradigms.

Background: Real-world evidence (RWE) can reinforce clinical trial evidence in health technology assessment (HTA). Objectives: Review HTA bodies’ (HTAbs) requirements for RWE, real uses, and acceptance across seven countries (Brazil, Canada, France, Germany, Italy, Spain, and the United Kingdom) and outline recommendations that may improve acceptance of RWE in efficacy/effectiveness assessments and appraisals processes. Methods: RWE requirements were summarized based on HTAbs’ guidelines. Acceptance by HTAbs was evaluated based on industry experience and case studies. Results: As of June 2022, RWE methodological guidelines were in place in three of the seven countries. HTAbs typically requested analyses based on local data sources, but the preferred study design and data sources differed. HTAbs had individual submission, assessment, and appraisal processes; some allowed early meetings for the protocol and/or results validation, though few involved external experts or medical societies to provide input to assessment and appraisal. The extent of submission, assessment, and appraisal requirements did not necessarily reflect the degree of acceptance. Conclusion: All the countries reviewed face common challenges regarding the use of RWE. Our proposals address the need to facilitate collaboration and communication with industry and regulatory agencies and the need for specific guidelines describing RWE design and criteria of acceptance throughout the assessment and appraisal processes.

Abstract Background A 10-day dexamethasone regimen has emerged as the internationally adopted standard-of-care for severe COVID-19 patients. However, the immune response triggered by SARS-CoV-2 infection remains a complex and dynamic phenomenon, leading to various immune profiles and trajectories. The immune status of severe COVID-19 patients following complete dexamethasone treatment has yet to be thoroughly documented. Results To analyze monocyte HLA-DR expression (mHLA-DR) and CD4 + T lymphocyte count (CD4) in critically ill COVID-19 patients after a dexamethasone course and evaluate their association with 28-day ICU mortality, adult COVID-19 patients (n = 176) with an ICU length of stay of at least 10 days and under dexamethasone treatment were included. Associations between each biomarker value (or in combination) measured at day 10 after ICU admission and 28-day mortality in ICU were evaluated. At day 10, the majority of patients presented decreased values of both parameters. A significant association between low mHLA-DR and 28-day mortality was observed. This association remained significant in a multivariate analysis including age, comorbidities or pre-existing immunosuppression (adjusted Hazard ratio (aHR) = 2.86 [1.30–6.32], p = 0.009). Similar results were obtained with decreased CD4 + T cell count (aHR = 2.10 [1.09–4.04], p = 0.027). When combining these biomarkers, patients with both decreased mHLA-DR and low CD4 presented with an independent and significant elevated risk of 28-day mortality (i.e., 60%, aHR = 4.83 (1.72–13.57), p = 0.001). Conclusions By using standardized immunomonitoring tools available in clinical practice, it is possible to identify a subgroup of patients at high risk of mortality at the end of a 10-day dexamethasone treatment. This emphasizes the significance of integrating immune monitoring into the surveillance of intensive care patients in order to guide further immumodulation approaches.

Abstract Background, objective and hypotheses During emerging adulthood, vocational indecision (i.e., the inability to make coherent career choices) develops in a heterogeneous fashion, with three distinct patterns: low; decreasing (i.e., developmental or adaptative); high and stable or increasing (i.e., chronic or maladaptive). Among the determinants of vocational indecision that have been identified in past research, academic motivation is a crucial an excellent choice, since it is at school that students' vocational choices are validated or not. According to SDT, this motivation can vary both in quantity and quality, and students tend to experience more positive academic outcomes when their motivational profile is optimal (high quantity, high quality) as opposed to suboptimal (e.g., low quantity, low quality). Thus, the purpose of this longitudinal study was to verify if the patterns found with emerging adulthood students characterized vocational indecision in adolescent students, and if supported, to predict the belonging to the most problematic trajectory by using students’ academic motivational profiles. We expected several distinct trajectories of vocational indecision that would differ in shape and magnitude, and several motivational profiles that vary in quality as well as in quantity. We also expected students in high-quality or quantity motivational profiles to be less likely to follow a chronic indecision trajectory. Method and results Using data from 384 students (56% female; Mage = 13.52 years; SD = .52 at Secondary 2) surveyed annually from Secondary 2 to 5, person-centered analyses enabled estimation of motivational profile in Secondary 2 and vocational indecision trajectories during the 4-year period. Results revealed four distinct patterns of vocational indecision during adolescence labelled Low and Stable, Moderate and Stable, Developmental and Chronic Intermittent. Four motivational profiles were also identified in Secondary 2, ranging from poor (Highly Amotivated) to moderate (Autonomous-Introjected) quality of self-determination level. Also, in reference to the most self-determined profile, students in the Mixed profile were at greatest risk of following Chronically-Intermittently Undecided trajectory. Finally, the most self-determined students were at greatest probability of following the Developmentally Undecided trajectory. Conclusion Overall, the findings suggest that the student motivational functioning in early secondary school years could be used to identify students at risk of experiencing the negative indecision patterns across secondary school. Several theoretical and practical implications are suggested.

Industrial residues with high concentrations of hexavalent chromium [Cr(VI)], characterized by an alkaline pH (between 9 and 13) and high salinity (around 100 psu), were used as a source for extremophilic chromium-resistant and -reducing microorganisms. An investigation of biodiversity through MiSeq showed the presence of 20 bacterial classes, with Bacilli (47%), Negativicutes (15%), Bacteriodia (8%), Gammaproteobacteria (7%) and Clostridia (5%) being the most abundant. The bioprospection allowed the cultivation of 87 heterotrophic bacterial colonies and 17 bacterial isolates at the end of the isolation, and screening procedures were obtained. The isolates were related to Cellulosimicrobium aquatile, C. funkei, Acinetobacter radioresistens, Staphylococcus equorum, S. epidermis, Brachybacterium paraconglometratum, Glutamicibacter creatinolyticus, Pseudomonas songnenensis, Microbacterium algeriense and Pantoea eucalypti, most of them being resistant to Cr(VI). Resistances of up to 400 mg.L−1 of chromate were obtained for four related strains (QReMLB55A, QRePRA55, QReMLB33A and QReMLB44C). The C. aquatile strain QReMLB55A and the P. songnenensis strain QReMLB33A were exposed to K2Cr2O7 (200 mg.L−1) under optimal conditions, diminishing 94% and 24% of the Cr(VI) in 6 days, respectively. These strains exhibited a high potential for chromium remediation biotechnologies.

Trash screens are used to prevent debris from entering critical parts of rivers. However, debris can accumulate on the screen and generate floods. This makes their monitoring critical both for maintenance and flood modeling purposes (e.g., local forecasts may change because the trash screen is blocked). We developed three novel deep learning methods for trash screen maintenance management consisting of automatically detecting trash screen blockage using cameras: a method based on image classification, a method based on image similarity matching, and a method based on anomaly detection. To facilitate their use by end users, these methods are designed so that they can be directly applied to any new trash screen camera installed by the end users. We have built a new dataset of labeled trash screen images to train and evaluate the efficiency of our methods, in terms of both accuracy and implications for end users. This dataset consists of 80,452 trash screen images from 54 cameras installed by the Environment Agency (UK). This work demonstrates that trash screen blockage detection can be automated using trash screen cameras and deep learning, which could have an impact on both trash screen management and flood modeling. HIGHLIGHTS Development and analysis of three deep learning-based trash screen monitoring methods using cameras, tailored for various investment levels.; Binary classification: ready-to-use, no additional labeling or retraining required.; Image similarity matching: requires minimal user annotation for improved accuracy.; Anomaly detection: able to use unlabeled datasets.; Network and dataset provided to support further research.;

Abstract Background The colorectal cancer (CRC) screening program B-PREDICT is a population based invited two stage screening project using a faecal immunochemical test (FIT) for initial screening followed by a colonoscopy for those with a positive FIT. B-PREDICT was compared with the opportunistic screening colonoscopy (OPP-COL), performed in course of the nationwide screening program. Methods Within B-PREDICT all residents of the Austrian federal state Burgenland, aged between 40 and 80 are annually invited to FIT testing. All individuals who underwent initial colonoscopy in Burgenland between 01/2003 and 12/2014, were included in this study. Individuals from the FIT-triggered invited screening program B-PREDICT were compared with those from the non-FIT triggered OPP-COL. Results 15 133 individuals from B-PREDICT were compared to 10 045 individuals with OPP-COL. CRC detection rates were 1.34% (CI-95%, [1.15; 1.52]) in B-PREDICT compared to 0.54% in OPP-COL (95%-CI, [0.39; 0.68] p

Abstract There has been huge recent interest in the potential of making operational weather forecasts using machine learning techniques. As they become a part of the weather forecasting toolbox, there is a pressing need to understand how well current machine learning models can simulate high-impact weather events. We compare short to medium-range forecasts of Storm Ciarán, a European windstorm that caused sixteen deaths and extensive damage in Northern Europe, made by machine learning and numerical weather prediction models. The four machine learning models considered (FourCastNet, Pangu-Weather, GraphCast and FourCastNet-v2) produce forecasts that accurately capture the synoptic-scale structure of the cyclone including the position of the cloud head, shape of the warm sector and location of the warm conveyor belt jet, and the large-scale dynamical drivers important for the rapid storm development such as the position of the storm relative to the upper-level jet exit. However, their ability to resolve the more detailed structures important for issuing weather warnings is more mixed. All of the machine learning models underestimate the peak amplitude of winds associated with the storm, only some machine learning models resolve the warm core seclusion and none of the machine learning models capture the sharp bent-back warm frontal gradient. Our study shows there is a great deal about the performance and properties of machine learning weather forecasts that can be derived from case studies of high-impact weather events such as Storm Ciarán.

Abstract Disordered protein sequences can exhibit different binding modes, ranging from well-ordered folding-upon-binding to highly dynamic fuzzy binding. The primary function of the intrinsically disordered region of the antitoxin HigA2 from Vibrio cholerae is to neutralize HigB2 toxin through ultra-high-affinity folding-upon-binding interaction. Here, we show that the same intrinsically disordered region can also mediate fuzzy interactions with its operator DNA and, through interplay with the folded helix-turn-helix domain, regulates transcription from the higBA2 operon. NMR, SAXS, ITC and in vivo experiments converge towards a consistent picture where a specific set of residues in the intrinsically disordered region mediate electrostatic and hydrophobic interactions while “hovering” over the DNA operator. Sensitivity of the intrinsically disordered region to scrambling the sequence, position-specific contacts and absence of redundant, multivalent interactions, point towards a more specific type of fuzzy binding. Our work demonstrates how a bacterial regulator achieves dual functionality by utilizing two distinct interaction modes within the same disordered sequence.

Abstract Objective Neuropsychological comorbidities found in chronic epilepsy have also been reported earlier in the disease course. However, recurrent seizures, antiseizure medication (ASM), and adjustment to a chronic diagnosis remain potential confounds of this literature. It thus remains unclear whether these comorbidities are primary or secondary attributes of epilepsy. To capture individuals as close to disease onset as possible, we studied the cognitive and psychological functioning in adults after their first seizure, yet prior to epilepsy diagnosis and treatment. Methods Using a telehealth‐based prospective design, we screened cognition, mood, and anxiety symptoms in adult patients referred to a First Seizure Clinic (FSC), who were over 18 years, English‐speaking and not taking ASM. We screened cognition via telephone, and psychological symptoms via online questionnaires, all prior to the patients' diagnostic evaluation. Data were collected on 32 individuals subsequently diagnosed with epilepsy at the FSC, and 30 healthy controls from the community, who were matched to the epilepsy group for age, gender, and education. Results A multivariate analysis of variance revealed that the groups differed significantly on combined cognitive measures with a large effect size (F[1,56] = 5.75, p

In the manual ball-and-beam task, participants have to control a ball that is rolling continuously on a long and hand-held beam. Since the task can be performed individually, in a solo action setting, as well as collaboratively, in a (dyadic) joint action setting, it allows us to investigate how joint performances arise from individual performances, which we investigate in a series of interrelated studies. Here we focused on individual skill acquisition on the ball-and-beam task in the solo action setting, with the goal to characterize the behavioral dynamics that arise from learning to couple (ball motion) perception and (beam motion) action. By moving a beam extremity up and down to manipulate the beam’s inclination angle, the task’s objective was to roll the ball as fast as and accurately as possible between two indicated targets on the beam. Based on research into reciprocal aiming tasks, we hypothesized that the emergent dynamics of the beam’s inclination angle would be constrained by the size of the targets, such that large targets would evoke a continuous beam movement strategy, while small targets would lead to a discrete beam movement strategy. 16 participants individually practiced the task in two separate six-block sessions. Each block consisted of one trial per target-size condition (small, medium and large). Overall, the number of target hits increased over trials, due to a larger range of motion of the beam’s inclination angle, a stronger correlation between the ball and beam motion and a smaller variability of the beam motion. Contrary to our expectations, target size did not appreciably affect the shape of the beam movement patterns. Instead, we found stable inter-individual differences in the movement strategies adopted that were uncorrelated with the number of target hits on a trial. We concluded that multiple movement strategies may lead to success on the task, while individual skill acquisition was characterized by the refinement of behavioral dynamics that emerged in an early stage of learning. We speculate that such differences in individual strategies on the task may affect the interpersonal coordination that arises in joint-action performances on the task.

The need to explore contemporary alternatives for industrial production has driven the development of innovative techniques that address critical limitations linked to traditional batch mechanochemistry. One particularly promising strategy involves the integration of flow processes with mechanochemistry. Three noteworthy technologies in this domain are single-screw extrusion (SSE) and twin-screw extrusion (TSE) and Impact (Induction) in Continuous-flow Heated Mechanochemistry (ICHeM). These technologies go beyond the industrial production of polymers, extending to the synthesis of active pharmaceutical ingredients, the fabrication of (nano)materials, and the extraction of high-added value products through the valorisation of biomass and waste materials. In accordance with the principles of green chemistry, ball milling processes are generally considered greener compared to conventional solvothermal processes. In fact, ball milling processes require less solvent, enhance reaction rates and reaction conversion by increasing surface area and substituting thermal energy with mechanochemical energy, among others. Special attention will be given to the types of products, reactants, size of the milling balls and reaction conditions, selecting 60 articles after applying a screening methodology during the period 2020–2022. This paper aims to compile and analyze the cutting edge of research in utilizing mechanochemistry for green chemistry applications.

School reopenings in 2021 and 2022 coincided with the rapid emergence of new SARS-CoV-2 variants in the United States. In-school mitigation efforts varied, depending on local COVID-19 mandates and resources. Using a stochastic age-stratified agent-based model of SARS-CoV-2 transmission, we estimate the impacts of multiple in-school strategies on both infection rates and absenteeism, relative to a baseline scenario in which only symptomatic cases are tested and positive tests trigger a 10-day isolation of the case and 10-day quarantine of their household and classroom. We find that monthly asymptomatic screening coupled with the 10-day isolation and quarantine period is expected to avert 55.4% of infections while increasing absenteeism by 104.3%. Replacing quarantine with test-to-stay would reduce absenteeism by 66.3% (while hardly impacting infection rates), but would require roughly 10-fold more testing resources. Alternatively, vaccination or mask wearing by 50% of the student body is expected to avert 54.1% or 43.1% of infections while decreasing absenteeism by 34.1% or 27.4%, respectively. Separating students into classrooms based on mask usage is expected to reduce infection risks among those who wear masks (by 23.1%), exacerbate risks among those who do not (by 27.8%), but have little impact on overall risk. A combined strategy of monthly screening, household and classroom quarantine, a 50% vaccination rate, and a 50% masking rate (in mixed classrooms) is expected to avert 81.7% of infections while increasing absenteeism by 90.6%. During future public health emergencies, such analyses can inform the rapid design of resource-constrained strategies that mitigate both public health and educational risks.

As renewable energy sources become more prevalent, effective grid balancing becomes crucial due to their inherent uncertainty. Battery Energy Storage Systems (BESS) can enhance grid reliability and efficiency by complementing these variable sources. However, to encourage investments in BESS, market participation must be economically viable for owners. Energy arbitrage is one of the main revenue streams for BESS allowing them to buy electricity when prices are low and sell it when they become higher, thus optimizing the revenues. However, in energy markets such as the Day-Ahead market (DA), the BESS owners submit their bids/offers one day before delivery, without perfect foresight of the future rates. This uncertainty poses a challenge that limits the energy provision capabilities and can incur a loss of profit due to the imperfect price forecast. Tailored strategies are then needed to mitigate those uncertainties and minimize the profit loss. This article proposes different operational planning strategies for a BESS participating in DA. Specific interest is attached to the explainability of the proposed methods to assure high profits while reducing the model’s complexity and computational time. The proposed strategies include 1) price forecast and scenario generation, using Geometric Brownian Motion (GBM) based either on a single-point forecast or historical data; 2) optimization process; and 3) choice of a single BESS bidding and operating schedule that is ultimately applied in real-time. Two baselines are introduced, one relying on a back-casting method, and a second based on traditional stochastic optimization. Several studies have neglected to thoroughly assess the bidding strategies by evaluating the profit against the actual prices. Hence, this study assesses the performance of the proposed methods and the baselines relative to the profit obtained in an ideal scenario with a perfect forecast in the French market over 2021.

Abstract Bispecific antibodies (BsAbs) are a new group of targeted therapies that are revolutionizing the treatment landscape of B-cell non-Hodgkin’s lymphoma (B-NHL). In the relapsed/refractory setting, salvage chemotherapy and autologous stem cell transplantation are capable of curing 50% of patients, whereas the other half will have a dismal outcome with a median overall survival of less than 12 months. This unmet need reinforced the importance of innovative therapies like the BsAbs and CAR-T cell therapies. In this review, we delve into BsAbs in B-NHL from the preclinical development to clinical data in both refractory and frontline settings, and then discuss future perspectives.

Xicotli data is the short name given to the dataset generated within the project framework "Integration of Biodiversity Data for the Management and Conservation of Wild Bee-Plant Interactions in Mexico (2021-2023)", as xicotli is the generic word for a bee in Nahuatl. The team comprised eco-informaticians, ecologists and taxonomists of both native bees and flora. The generated dataset contains so far 4,532 curated records of the plants, which are potential hosts of species of three focal families of bees native to Mexico: Apidae, Halictidae and Megachilidae and morphological and ecological data of the plant-bee interactions. This dataset was integrated and mobilised from citizen observations available at naturalista.mx (iNat), which were compiled through the iNaturalist project.The new information obtained with the Xicotli data project was:Taxonomic information about bee species curated by taxonomists based on the information contained in iNaturalist;Taxonomic identification of the host plants by a botanist from the photos compiled by the Xicotli Data project;Data on the ecomorphological traits of bees and plants based on expert knowledge and literature.All the data were integrated into the Xicotli Data Project via the creation of new “observation fields". The visibility of the information originally contained in iNaturalist was maximized and can be consulted directly on the iNaturalist platform.

Agonimia gargominyi ( Verrucariaceae , Verrucariales ) is described and illustrated from bark samples collected from Morane atoll (Tuāmotu-Gambier Islands, French Polynesia). It is characterized by the large superficial perithecia having a pale brown-colored ostiolar region, the 8-spored asci, and the relatively large lobed squamules. Micromorphology of the ascomata and the thalline squamules matches the genus Agonimia . Additionally, to accommodate the inclusion of this newly identified species, the existing comprehensive key encompassing all known Agonimia species worldwide has been modified and updated accordingly. Detailed illustrations supplement the description of Agonimia gargominyi .

The growth in the amount of data in companies puts analysts in difficulties when extracting hidden knowledge from data. Several models have emerged that focus on the notion of distances while ignoring the notion of conditional probability density. This research study focuses on segmentation using mixture models and Bayesian networks for medical data mining. As enterprise data becomes large, there is a way to apply data mining methods to make sense of it using classification methods. We designed different models with different architectures and then applied these models to the medical database. The algorithms were implemented for the real data. The objective is to classify individuals according to the conditional probability density of random variables, in addition to identifying causalities between traits from tests of conditional independence and a correlation measure, both based on χ2. After a quick illustration of several models (decision tree, SVM, K-means, Bayes), we applied our method to data from an epidemiological study (done at the University of Kinshasa University clinics) of case-control of prostate cancer. Thus, we found after interpretation of the results followed by discussion that our model allows us to classify a new individual with an accuracy of 96%.

Wire-based additive manufacturing (AM) is at the forefront of complex metal fabrication because of its scalability for large components, potential for high deposition rates, and ease of use. A common goal of wire directed energy deposition (DED) is preserving a stable process throughout deposition. If too little energy is put into the deposition, the wire will stub into the substrate and begin oscillating, creating turbulence within the meltpool. If too much energy exists, the wire will overheat, causing surface tension to take over and create liquid drips as opposed to a solid bead. This paper proposes a computer vision technique to work as both a state detection and event detection system for wire stability. The model utilizes intensity variations along with frame-to-frame difference calculations to determine process stability. Because the proposed model does not rely on machine learning techniques, it is possible for an individual to interpret and adjust as they see fit. The first part of this paper describes creation and implementation of the model. The model’s capability was then evaluated using a 1D laser power experiment, which generated a wide range of stability states across varying powers. The model’s accuracy was evaluated through 3D geometry data gathered from the experimentally deposited beads. The model proved to be both capable and accurate and has potential to be used as a real-time control system with future work.

Summary: Background: Although immunomodulators have established benefit against the new coronavirus disease (COVID-19) in general, it is uncertain whether such agents improve outcomes without increasing the risk of secondary infections in the specific subgroup of previously immunocompromised patients. We assessed the effect of immunomodulators on outcomes of immunocompromised patients hospitalized for COVID-19. Methods: The protocol was prospectively registered with PROSPERO (CRD42022335397). MEDLINE, Cochrane Central Register of Controlled Trials and references of relevant articles were searched up to 01-06-2022. Authors of potentially eligible randomized controlled trials were contacted to provide data on immunocompromised patients randomized to immunomodulators vs control (i.e., placebo or standard-of-care). Findings: Eleven randomized controlled trials involving 397 immunocompromised patients hospitalized for COVID-19 were included. Ten trials had low risk of bias. There was no difference between immunocompromised patients randomized to immunomodulators vs control regarding mortality [30/182 (16.5%) vs 41/215 (19.1%); RR 0.93, 95% CI 0.61–1.41; p = 0.74], secondary infections (RR 1.00, 95% CI 0.64–1.58; p = 0.99) and change in World Health Organization ordinal scale from baseline to day 15 (weighed mean difference 0.27, 95% CI -0.09–0.63; p = 0.15). In subgroup analyses including only patients with hematologic malignancy, only trials with low risk of bias, only trials administering IL-6 inhibitors, or only trials administering immunosuppressants, there was no difference between comparators regarding mortality. Interpretation: Immunomodulators, compared to control, were not associated with harmful or beneficial outcomes, including mortality, secondary infections, and change in ordinal scale, when administered to immunocompromised patients hospitalized for COVID-19. Funding: Hellenic Foundation for Research and Innovation.

BackgroundThe present study evaluated the therapeutic efficacy and tolerability of 10 transcranial direct current stimulation (tDCS) sessions in treatment-resistance obsessive-compulsive disorder (OCD) patients using a multisite double-blind sham-controlled design.MethodsEighty treatment-resistance outpatients suffering from obsessive-compulsive disorder were randomized to receive either active or sham transcranial direct current stimulation. The cathode was positioned over the supplementary motor area and the anode over the right supraorbital area. Patients were evaluated at baseline, end of treatment (day 14), one-month follow-up (day 45), and three-month follow-up (day 105) on the Yale-Brown Obsessive Compulsive Scale.ResultsAlthough a significant interaction between time and treatment was observed, the primary endpoint—measuring the change in Yale-Brown obsessive compulsive scale scores after two weeks—was not achieved. Conversely, the secondary endpoint, which concerned the change in Yale-Brown obsessive compulsive scale scores after three months, was successfully met. It is important to note, however, that there were no significant differences in the percentage of responders and remitters at any of the post-treatment assessments. This suggests that the treatment may not have had a clinically relevant impact. Patients well received the transcranial direct current stimulation treatment, indicating its good tolerability.ConclusionThis is the largest controlled trial using transcranial direct current stimulation in treatment-resistance obsessive-compulsive disorder patients. Our results indicate the importance of studying the placebo effect in transcranial direct current stimulation and the necessity to consider a long follow-up time to best evaluate the effects of the intervention.Clinical trial registrationClinicalTrials.gov, identifier NCT03304600.

BACKGROUND AND OBJECTIVES: Pandemic-related life changes may have had a deleterious impact on suicidal behaviours. Early detection of suicidal ideation and identification of subgroups at increased risk could help prevent suicide, one of the leading causes of death among adolescents worldwide. Here, we aimed to investigate the prevalence of and risk factors for suicidal ideation in adolescents using a population-based sample from Switzerland, two years into the pandemic. METHODS: Between December 2021 and June 2022, adolescents aged 14 to 17 years already enrolled in a population-based cohort study (State of Geneva, Switzerland) were asked about suicidal ideation over the previous year. In addition to a regression model, we conducted a network analysis of exposures which identified direct and indirect risk factors for suicidal ideation (i.e. those connected through intermediate risk factors) using mixed graphical models. RESULTS: Among 492 adolescents, 14.4% (95% CI: 11.5–17.8) declared having experienced suicidal ideation over the previous year. Using network analysis, we found that high psychological distress, low self-esteem, identifying as lesbian, gay or bisexual, suffering from bullying, extensive screen time and a severe COVID-19 pandemic impact were major risk factors for suicidal ideation, with parent-adolescent relationship having the highest centrality strength in the network. CONCLUSION: Our results show that a significant proportion of adolescents experience suicidal ideation, yet these rates are comparable with pre-pandemic results. Providing psychological support is fundamental, with a focus on improving parent-adolescent relationships.

In utero and children’s exposure to per- and polyfluoroalkyl substances (PFAS) is a major concern in health risk assessment as early life exposures are suspected to induce adverse health effects. Our work aims to estimate children’s exposure (from birth to 12 years old) to PFOA and PFOS, using a Physiologically-Based Pharmacokinetic (PBPK) modelling approach.A model for PFAS was updated to simulate the internal PFAS exposures during the in utero life and childhood, and including individual characteristics and exposure scenarios (e.g., duration of breastfeeding, weight at birth, etc.). Our approach was applied to the HELIX cohort, involving 1,239 mother–child pairs with measured PFOA and PFOS plasma concentrations at two sampling times: maternal and child plasma concentrations (6 to 12 y.o).Our model predicted an increase in plasma concentrations during fetal development and childhood until 2 y.o when the maximum concentrations were reached. Higher plasma concentrations of PFOA than PFOS were predicted until 2 y.o, and then PFOS concentrations gradually became higher than PFOA concentrations. From 2 to 8 y.o, mean concentrations decreased from 3.1 to 1.88 µg/L or ng/mL (PFOA) and from 4.77 to 3.56 µg/L (PFOS). The concentration–time profiles vary with the age and were mostly influenced by in utero exposure (on the first 4 months after birth), breastfeeding (from 5 months to 2 (PFOA) or 5 (PFOS) y.o of the children), and food intake (after 3 (PFOA) or 6 (PFOS) y.o of the children). Similar measured biomarker levels can correspond to large differences in the simulated internal exposures, highlighting the importance to investigate the children’s exposure over the early life to improve exposure classification.Our approach demonstrates the possibility to simulate individual internal exposures using PBPK models when measured biomarkers are scarce, helping risk assessors in gaining insight into internal exposure during critical windows, such as early life.

Introduction Patients with a first venous thromboembolism (VTE) are at risk of recurrence. Recurrent VTE (rVTE) can be prevented by extended anticoagulant therapy, but this comes at the cost of an increased risk of bleeding. It is still uncertain whether patients with an intermediate recurrence risk or with a high recurrence and high bleeding risk will benefit from extended anticoagulant treatment, and whether a strategy where anticoagulant duration is tailored on the predicted risks of rVTE and bleeding can improve outcomes. The aim of the Leiden Thrombosis Recurrence Risk Prevention (L-TRRiP) study is to evaluate the outcomes of tailored duration of long-term anticoagulant treatment based on individualised assessment of rVTE and major bleeding risks.Methods and analysis The L-TRRiP study is a multicentre, open-label, cohort-based, randomised controlled trial, including patients with a first VTE. We classify the risk of rVTE and major bleeding using the L-TRRiP and VTE-BLEED scores, respectively. After 3 months of anticoagulant therapy, patients with a low rVTE risk will discontinue anticoagulant treatment, patients with a high rVTE and low bleeding risk will continue anticoagulant treatment, whereas all other patients will be randomised to continue or discontinue anticoagulant treatment. All patients will be followed up for at least 2 years. Inclusion will continue until the randomised group consists of 608 patients; we estimate to include 1600 patients in total. The primary outcome is the combined incidence of rVTE and major bleeding in the randomised group after 2 years of follow-up. Secondary outcomes include the incidence of rVTE and major bleeding, functional outcomes, quality of life and cost-effectiveness in all patients.Ethics and dissemination The protocol was approved by the Medical Research Ethics Committee Leiden-Den Haag-Delft. Results are expected in 2028 and will be disseminated through peer-reviewed journals and during (inter)national conferences.Trial registration number NCT06087952.

Holacanthus angelfishes are some of the most iconic marine fishes of the Tropical Eastern Pacific (TEP). However, very limited genomic resources currently exist for the genus. In this study we: (i) assembled and annotated the nuclear genome of the King Angelfish (Holacanthus passer), and (ii) examined the demographic history of H. passer in the TEP. We generated 43.8 Gb of ONT and 97.3 Gb Illumina reads representing 75× and 167× coverage, respectively. The final genome assembly size was 583 Mb with a contig N50 of 5.7 Mb, which captured 97.5% of the complete Actinoterygii Benchmarking Universal Single-Copy Orthologs (BUSCOs). Repetitive elements accounted for 5.09% of the genome, and 33,889 protein-coding genes were predicted, of which 22,984 were functionally annotated. Our demographic analysis suggests that population expansions of H. passer occurred prior to the last glacial maximum (LGM) and were more likely shaped by events associated with the closure of the Isthmus of Panama. This result is surprising, given that most rapid population expansions in both freshwater and marine organisms have been reported to occur globally after the LGM. Overall, this annotated genome assembly provides a novel molecular resource to study the evolution of Holacanthus angelfishes, while facilitating research into local adaptation, speciation, and introgression in marine fishes.

IntroductionMany sampling methods are used for entomological surveillance of vector borne diseases. This paper, evaluated the performance of five methods with regard to various ecosystems encountered in Cameroon. Material and methodsTwo entomological databases generated during two study periods were examined: 2011-2014 in the North Region, and 2018-2019 in the Centre Region. Mosquitoes were collected using the (Human Landing Catches) (HLC) and four alternative methods including Clay Pots (CPs), Pyrethroid Spray Catches (PSCs), Window Exit Traps (WETs) and Centers for Disease Control-Light Traps (CDC-LTs) for which the performance was assessed in this study.ResultsA total of 29 anopheline species were identified from samples collected during the two study periods. All these anopheline species were found in North Region, with 5 species being the most abundant and prévalent, i.e. An. gambiae s.l, An. funestus, An. rufipes, An. paludis and An. pharoensis. In the Centre Region, only five species including An. gambiae s.l, An. funestus, An. coustani, An. ziemanni and An. paludis were recorded. Among these, An. gambiae s.l was the most abundant and prevalent species. Data confirmed HLC as the best in sampling outdoor and indoor mosquitoes in the surveyed HDs. The alternative methods showed variable records regarding the species richness. Based on the number of mosquitoes collected, CP was an alternative to HLC for outdoor collections in Garoua and Pitoa HDs, while WET was an alternative in Mayo Oulo HD. In the Centre Region, CDC-LT was an alternative to HLC for indoor collections in Ekié and Nkolbisson HDs, while PSC proved to be the best alternative in Nkolondom HD. Regarding the species richness WET appeared as an alternative to HLC in sampling outdoor mosquitoes in Garoua and Mayo Oulo HDs, while CP was the best alternative in Pitoa HD. In the Centre Region, CDC-LT was an alternative for outdoor and indoor collections in Nkolbisson HD, and the best alternative for outdoor collections in Ekie HD. Conclusion The current study revealed variable performance of the five tested adult mosquito collection methods across the prospected HDs in North and Centre Regions of Cameroon. Further investigations will be conducted on other collection methods, e.g., aspiration, mosquito electrocuting grid trap, ovitraps and human-baited double net trap.

Chronic stress and alcohol (ethanol) use are highly interrelated and can change an individual’s behavior through molecular adaptations that do not change the DNA sequence, but instead change gene expression. A recent wealth of research has found that these nongenomic changes can be transmitted across generations, which could partially account for the “missing heritability” observed in genome-wide association studies of alcohol use disorder and other stress-related neuropsychiatric disorders. In this review, we summarize the molecular and behavioral outcomes of nongenomic inheritance of chronic stress and ethanol exposure and the germline mechanisms that could give rise to this heritability. In doing so, we outline the need for further research to: (1) Investigate individual germline mechanisms of paternal, maternal, and biparental nongenomic chronic stress- and ethanol-related inheritance; (2) Synthesize and dissect cross-generational chronic stress and ethanol exposure; (3) Determine cross-generational molecular outcomes of preconception ethanol exposure that contribute to alcohol-related disease risk, using cancer as an example. A detailed understanding of the cross-generational nongenomic effects of stress and/or ethanol will yield novel insight into the impact of ancestral perturbations on disease risk across generations and uncover actionable targets to improve human health.