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Background Diagnosis of autism falls under the remit of psychiatry. Recognition that psychiatrists could be autistic is recent. Psychiatrists are the second largest specialty group in Autistic Doctors International, a peer support group for autistic doctors. Aims To explore the experiences of autistic psychiatrists in relation to recognising themselves and others as autistic. Method This was a qualitative study using loosely structured interviews and an interpretive phenomenological analysis. Results Eight autistic senior psychiatrists based in the UK participated. One had a childhood diagnosis, two had been diagnosed in adulthood and the remainder self-identified as autistic as adults. Recognition of autism followed diagnosis of their children or encounters with autistic patients. Barriers to self-recognition included lack of autism training, the deficit-based diagnostic criteria and stereotypical views of autism. Recognising that they were autistic led to the realisation that many colleagues were also likely to be autistic, particularly in neurodevelopmental psychiatry. All participants reported the ability to quickly recognise autistic patients and to develop a good rapport easily, once they were aware of their own autistic identity. Difficulties recognising patients as autistic occurred before self-recognition when they shared autistic characteristics and experiences. ‘If we don't recognise ourselves as autistic how on earth can we diagnose patients accurately?’ Conclusions Autistic psychiatrists face multiple barriers to recognising that they are autistic. Lack of self-recognition may impede diagnostic accuracy with autistic patients. Self-recognition and disclosure by autistic psychiatrists may be facilitated by reframing the traditional deficit-based view of autism towards a neurodiversity-affirmative approach, with consequent benefits for autistic patients.

Background: Borderline personality disorder is a severe mental health condition characterised by a pattern of emotional instability, interpersonal dysfunction, disturbed self-image and impulsive behaviour, including self-harm. Symptoms of borderline personality disorder typically emerge during adolescence. Although there is compelling evidence in support of early intervention for borderline personality disorder, current evidence-based interventions are resource intensive, with the result that few young people access timely treatment. Therefore, there is an urgent need for accessible interventions to facilitate early intervention for adolescents with borderline personality disorder symptoms. Objectives: The first objective was to adapt a brief psychological treatment for adolescent borderline personality disorder that had previously been delivered within secondary mental health services for co-delivery within schools and colleges. The second objective was to assess the feasibility of evaluating the clinical effectiveness and cost-effectiveness of this intervention in a future randomised controlled trial. Design: We first conducted a rapid evidence synthesis of barriers to and facilitators of the implementation of indicated mental health interventions for adolescents within educational settings and piloted the prototype intervention with three schools/colleges. Based on the findings of the evidence synthesis and pilot, we refined the intervention and study procedures in preparation for a feasibility randomised controlled trial. The feasibility randomised controlled trial involved 12 schools and colleges, whose pastoral staff members received training to deliver the intervention alongside a mental health practitioner. Participants were randomised in a 1 : 1 ratio to receive either the BEST (Brief Education Supported Treatment) intervention plus treatment as usual or treatment as usual alone. Participants were assessed pre randomisation (baseline) and at 12 and 24 weeks post randomisation. Mixed-methods process data were collected to understand how the intervention was implemented, to assess acceptability and to monitor contamination of the control arm. Participants: Young people eligible to participate were aged 13–18 years, reported symptoms of borderline personality disorder above an established threshold and had a history of repeated self-harm. Results: The intervention was refined based on findings of the rapid evidence synthesis, which included 50 studies, feedback from staff participants in the pilot and analysis of session recordings. In the feasibility randomised controlled trial, we randomised 32 participants prior to the premature closure of recruitment. The rate of recruitment was slower than anticipated but would probably have narrowly surpassed our progression criterion over the full recruitment window. Participant retention was high (89.5% at 12 weeks and 73.7% at 24 weeks) and the performance of the proposed outcome measures was satisfactory. We did not find any evidence that participants allocated to the treatment-as-usual arm received the BEST intervention or its components. Fidelity of intervention delivery was high (93.5% of recordings rated as adherent) and the intervention was viewed as offering benefits for individual participants, practitioners involved in co-delivery and the wider school/college. Limitations: The feasibility randomised controlled trial was disrupted by the closure of schools and colleges in response to the COVID-19 pandemic. This reduced the window for participant recruitment and limited the data that could be collected. Conclusions: The refined BEST intervention was able to be delivered successfully within schools and colleges and was found to be acceptable to staff and young people. The findings provide support for continuing this programme of research and would inform the design of a future trial. Trial registration: This trial is registered as ISRCTN16862589. Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in full in Health and Social Care Delivery Research; Vol. 10, No. 37. See the NIHR Journals Library website for further project information.

Abstract We assess the impact of atmospheric horizontal resolution on the prediction skill and fidelity of seasonal forecasts. We show the response to an increase of atmospheric resolution from 0.8 to 0.3° horizontal grid spacing in parallel ensembles of forecasts. Changes in the prediction skill of major modes of tropical El Nino Southern Oscillation (ENSO) and extratropical North Atlantic Oscillation (NAO) variability are small and not detected and there is no discernible impact on the weak signal‐to‐noise ratio in seasonal predictions of the winter NAO at this range of resolutions. Although studies have shown improvements in the simulation of tropical cyclones as model resolution is increased, we find little impact on seasonal prediction skill of either their numbers or intensity. Over this range of resolutions it appears that the benefit of increasing atmospheric resolution to seasonal climate predictions is minimal. However, at yet finer scales there appears to be increased eddy feedback which could strengthen weak signals in predictions of the NAO. Until prediction systems can be run operationally at these scales, it may be better to use additional computing resources for other enhancements such as increased ensemble size, for which there is a clear benefit in extratropical seasonal prediction skill.

Background: Decreases in iron status have been reported [...]

The North Atlantic Oscillation (NAO), the regional manifestation of the Arctic Oscillation (AO), dominates winter climate variability in Europe and North America. Skilful seasonal forecasting of the winter NAO/AO has been demonstrated recently by dynamical prediction systems. However, the role of initial conditions in this predictability remains unknown. Using a latest generation seasonal forecasting system and reanalysis data, we show that the initial upper stratospheric zonal wind anomaly contributes to winter NAO/AO predictability through downward propagation of initial conditions. An initial polar westerly/easterly anomaly in the upper stratosphere propagates down to the troposphere in early winter, favoring a poleward/equatorward shift of the tropospheric mid-latitude jet. This tropospheric anomaly persists well into the late winter and induces the positive/negative phase of NAO/AO in the troposphere. Our results imply that good representation of stratospheric initial condition and stratosphere-troposphere coupling in models is important for winter climate prediction.

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Not available.

Background: Inferior vena cava agenesis (IVCA) is a rare vascular abnormality characterised by the absence of one or more segments of the inferior vena cava and represents an underestimated cause of deep vein thrombosis (DVT). Given the very low prevalence of this condition and the lack of clinical trials, there is no consensus about the optimal anticoagulation strategy in IVCA-associated DVT. Objectives: To investigate efficacy and safety of direct oral anticoagulants (DOACs) in IVCA-associated DVT. Methods: We described three patients with IVCA-associated DVT followed at our Institution and treated with DOACs. Then, we performed a systematic review of the literature for ICVA-associated DVT treated with DOACs. Results: In addition to our 3 cases, we found data from 19 publications for a total of 30 patients with IVCA-associated DVT treated with DOACs (24 subjects treated with rivaroxaban, 8 with apixaban, and one with dabigatran). Most patients were males (72.7 %) with a median age at DVT onset of 26.0 years (min–max range 13–64 years). The majority of DVT events were unprovoked (76.0 %). The standard thrombophilia tests were mainly negative. The median follow-up period during DOAC therapy was 1.0 years (min–max range 0–10 years), with one recurrent splanchnic vein thrombosis reported and no haemorrhagic events. Conclusions: IVCA is a rare cause of DVT, which should be suspected in young adults with unprovoked DVT. Although future studies are needed, available data may support the use of DOACs in IVCA-associated DVT, with a reassuring profile of both efficacy and safety.

The sodium chloride cotransporter (NCC) is essential for electrolyte balance, blood pressure regulation, and pathophysiology of hypertension as it mediates the reabsorption of ultrafiltered sodium in the renal distal convoluted tubule. Given its pivotal role in the maintenance of extracellular fluid volume, the NCC is regulated by a complex network of cellular pathways, which eventually results in either its phosphorylation, enhancing sodium and chloride ion absorption from urines, or dephosphorylation and ubiquitination, which conversely decrease NCC activity. Several factors could influence NCC function, including genetic alterations, hormonal stimuli, and pharmacological treatments. The NCC’s central role is also highlighted by several abnormalities resulting from genetic mutations in its gene and consequently in its structure, leading to dysregulation of blood pressure control. In the last decade, among other improvements, the acquisition of knowledge on the NCC and other renal ion channels has been favored by studies on extracellular vesicles (EVs). Dietary sodium and potassium intake are also implicated in the tuning of NCC activity. In this narrative review, we present the main cornerstones and recent evidence related to NCC control, focusing on the context of blood pressure pathophysiology, and promising new therapeutical approaches.

The carbon source/sink nature and the water balance of a drip-irrigated and mulched watermelon cultivated under a semi-arid climate were investigated. Biodegradable films, plants and some fruits were left on the soil as green manure. The study spanned from watermelon planting to the subsequent crop (June–November 2023). The eddy covariance technique was employed to monitor water vapor (H2O) and carbon dioxide (CO2) fluxes, which were partitioned into transpiration, evaporation, photosynthesis and respiration, respectively, using the flux variance similarity method.This method utilizesthe Monin–Obukhov similarity theory to separate stomatal (photosynthesis and transpiration) from non-stomatal (respiration and evaporation) processes. The results indicate that mulching films contribute to carbon sequestration in the soil (+19.3 g C m−2). However, the mulched watermelon crop presented in this study functions as a net carbon source, with a net biome exchange, representing the net rate of C accumulation in or loss from ecosystems, equal to +230 g C m−2. This is primarily due to the substantial amount of carbon exported through marketable fruits. Fixed water scheduling led to water waste through deep percolation (approximately 1/6 of the water supplied), which also contributed to the loss of organic carbon via leaching (−4.3 g C m−2). These findings recommend further research to enhance the sustainability of this crop in terms of both water and carbon balances.

Tissue factor (TF) is a transmembrane glycoprotein that represents the fundamental physiological initiator of the coagulation cascade through its interaction with factor VII. TF belongs to the cytokine receptor protein superfamily and contributes to the transduction of cellular signaling. Therefore, TF-related pathways are involved in multiple pathophysiological processes, not only in coagulation/thrombosis but in a wider mechanisms’ panorama, ranging from infective to neoplastic diseases. Consistently, the measurement of TF activity could have a diagnostic and/or prognostic meaning in different clinical conditions. However, the transmembrane localization, the expression on different cellular types and circulating extracellular vesicles, and the different conformations (encrypted and decrypted) and variants (such as the soluble alternatively spliced TF) hamper TF assessment in clinical practice. The activated factor VII-antithrombin (FVIIa–AT) complex is proposed as an indirect biomarker of the TF–FVIIa interaction and, consequently, of the functionally active TF expression. In this narrative review, we evaluate the clinical studies investigating the role of plasma concentration of FVIIa–AT in health and disease. Although without conclusive data, high FVIIa–AT concentrations predict the worst clinical outcomes in different pathologic conditions, such as cardiovascular disease and cancer, thereby suggesting that overactivation of TF-related pathways may play an unfavorable role in various clinical settings.

Abstract Narratives are paradigmatic examples of natural language, where nouns represent a proxy of information. Functional magnetic resonance imaging (fMRI) studies revealed the recruitment of temporal cortices during noun processing and the existence of a noun-specific network at rest. Yet, it is unclear whether, in narratives, changes in noun density influence the brain functional connectivity, so that the coupling between regions correlates with information load. We acquired fMRI activity in healthy individuals listening to a narrative with noun density changing over time and measured whole-network and node-specific degree and betweenness centrality. Network measures were correlated with information magnitude with a time-varying approach. Noun density correlated positively with the across-regions average number of connections and negatively with the average betweenness centrality, suggesting the pruning of peripheral connections as information decreased. Locally, the degree of the bilateral anterior superior temporal sulcus (aSTS) was positively associated with nouns. Importantly, aSTS connectivity cannot be explained by changes in other parts of speech (e.g., verbs) or syllable density. Our results indicate that the brain recalibrates its global connectivity as a function of the information conveyed by nouns in natural language. Also, using naturalistic stimulation and network metrics, we corroborate the role of aSTS in noun processing.

Brugada Syndrome (BrS) is a primary electrical epicardial disease characterized by ST-segment elevation followed by a negative T-wave in the right precordial leads on the surface electrocardiogram (ECG), also known as the ‘type 1’ ECG pattern. The risk stratification of asymptomatic individuals with spontaneous type 1 ECG pattern remains challenging. Clinical and electrocardiographic prognostic markers are known. As none of these predictors alone is highly reliable in terms of arrhythmic prognosis, several multi-factor risk scores have been proposed for this purpose. This article presents a new workflow for processing endocardial signals acquired with high-density RV electro-anatomical mapping (HDEAM) from BrS patients. The workflow, which relies solely on Matlab software, calculates various electrical parameters and creates multi-parametric maps of the right ventricle. The workflow, but it has already been employed in several research studies involving patients carried out by our group, showing its potential positive impact in clinical studies. Here, we will provide a technical description of its functionalities, along with the results obtained on a BrS patient who underwent an endocardial HDEAM.

Abstract Background Segmentation of cardiovascular magnetic resonance (CMR) images is an essential step for evaluating dimensional and functional ventricular parameters as ejection fraction (EF) but may be limited by artifacts, which represent the major challenge to automatically derive clinical information. The aim of this study is to investigate the accuracy of a deep learning (DL) approach for automatic segmentation of cardiac structures from CMR images characterized by magnetic susceptibility artifact in patient with cardiac implanted electronic devices (CIED). Methods In this retrospective study, 230 patients (100 with CIED) who underwent clinically indicated CMR were used to developed and test a DL model. A novel convolutional neural network was proposed to extract the left ventricle (LV) and right (RV) ventricle endocardium and LV epicardium. In order to perform a successful segmentation, it is important the network learns to identify salient image regions even during local magnetic field inhomogeneities. The proposed network takes advantage from a spatial attention module to selectively process the most relevant information and focus on the structures of interest. To improve segmentation, especially for images with artifacts, multiple loss functions were minimized in unison. Segmentation results were assessed against manual tracings and commercial CMR analysis software cvi42(Circle Cardiovascular Imaging, Calgary, Alberta, Canada). An external dataset of 56 patients with CIED was used to assess model generalizability. Results In the internal datasets, on image with artifacts, the median Dice coefficients for end-diastolic LV cavity, LV myocardium and RV cavity, were 0.93, 0.77 and 0.87 and 0.91, 0.82, and 0.83 in end-systole, respectively. The proposed method reached higher segmentation accuracy than commercial software, with performance comparable to expert inter-observer variability (bias ± 95%LoA): LVEF 1 ± 8% vs 3 ± 9%, RVEF − 2 ± 15% vs 3 ± 21%. In the external cohort, EF well correlated with manual tracing (intraclass correlation coefficient: LVEF 0.98, RVEF 0.93). The automatic approach was significant faster than manual segmentation in providing cardiac parameters (approximately 1.5 s vs 450 s). Conclusions Experimental results show that the proposed method reached promising performance in cardiac segmentation from CMR images with susceptibility artifacts and alleviates time consuming expert physician contour segmentation.