Tree species influence below-ground soil chemistry and microbial communities, both of which are key drivers of soil formation. The study compared soils under native European beech and first-generation non-native Norway spruce growing at the same site. Soil under beech was classified as Dystric Cambisol, whereas soil under spruce had developed into Entic Podzol. The objective was to link soil chemical processes with microbial community composition and the resulting quantity and quality of soil organic carbon (SOC) across soil horizons. Soil pH and concentrations of available cations and anions were measured together with dissolved organic carbon (DOC), represented by low-molecular-weight organic acids (LMMOA; ion-exchange chromatography). SOC quantity and functional group composition were characterized using Fourier-transform infrared spectroscopy. Microbial abundance and community composition were assessed by 16S/18S rRNA gene amplicon sequencing and droplet digital PCR. Total carbon contents did not differ between soils, but DOC showed horizon-specific differences, with quinate strongly enriched under spruce. More pronounced differences were observed in carbon quality and its vertical distribution. Elevated concentrations and specific forms of Si, Al, P, and S under spruce indicated progressing podzolization, a process absent under beech. Distinct soil conditions and carbon sources supported contrasting microbial communities. Higher pH and labile carbon availability under beech promoted Pseudomonadota and Bacteroidota, distinguished particularly in the L horizon. In contrast, spruce soils, especially the H horizon were enriched in fungi and metabolically versatile Actinomycetota. Increased abundance of erm resistance genes under spruce also suggested a more competitive microbial environment. Tree species effects on soil properties were detectable throughout the soil profile but weakened with depth. Overall, differences in soil chemistry, microbial communities, and enzymatic activities reflect contrasting decomposition and carbon sequestration pathways, with implications for ecosystem resilience and microbial diversity.
Artificial intelligence (AI) is transforming organic materials discovery by enabling the rapid exploration of chemical space. This review examines machine learning techniques being used to accelerate the identification of novel compounds for organic semiconductors through computational approaches linking molecular structure to properties. Key methodologies include graph neural networks, generative approaches, chemical representations, Δ $\Delta$ -learning frameworks, machine learning force fields, active learning, transfer learning, and generative models. These methods address fundamental challenges in organic materials discovery, from property prediction and inverse design to high-throughput screening and molecular generation. An example of applications to the topic of organic photovoltaics demonstrates practical impact in predicting energy levels, morphology, charge transport, exciton dynamics, and power conversion efficiency. Rather than replacing human scientists, we envision AI as a tool that amplifies their capacity to explore unconventional regions of chemical space. Advantages, drawbacks and bottlenecks of AI use in chemistry are discussed together with future research directions, such as the adoption of human-centered AI practices, the construction of materials-science-oriented benchmarking databases and protocols, the integration of green chemistry constraints into generative pipelines, and the further exploration of end-to-end in-silico-to-technical validation workflows, all tailored to the needs of the materials science community.
Establishing and maintaining laboratory colonies of the malaria vector, Anopheles funestus using newly collected material has proven challenging, in part because of their low propensity to mate in captivity. In this study we assessed how cage conditions influence the mating success of two An. funestus strains originating from different geographic areas, Angola (FANG) and Mozambique (FUMOZ). The visual environment in adult mosquito-rearing cages was manipulated either by covering the cages in different planes with black opaque cloth (referred to as black horizons) or by placing black visual markers at various positions inside the cages. Mating success was assessed by dissecting the spermathecae capsule of the females after the standard 10-day mating period. Insemination rates were consistently higher in the An. funestus FANG strain than in the FUMOZ strain in both the black horizon (odds ratio [OR] 0.31, 95% confidence interval [CI] 0.21-0.44, p < 0.001) and visual marker experiments (OR 0.12, 95% CI 0.08-0.19, p < 0.001). The inclusion of black horizons and visual markers significantly increased insemination in both strains (p < 0.001). However, strain-specific responses were evident: FANG showed significantly greater insemination rates in the side-covered cages (OR 2.06, 95% CI 1.41-3.01, p < 0.001), whereas FUMOZ insemination rates declined under the same condition (OR 0.41, 95% CI 0.24-0.70, p < 0.001). The insemination rate of the FUMOZ strain was significantly higher in top-covered cages (OR 0.59, 95% CI 0.38-0.95, p = 0.03) and when a visual marker was placed at the bottom of cage (OR 2.18, 95% CI 1.25-3.81, p = 0.006), while FANG insemination rates were unaffected by marker position. This study demonstrates that manipulating the visual environment within adult mosquito-rearing cages can significantly enhance mating success in An. funestus, although the effectiveness of specific visual cues varies between strains. While both FANG and FUMOZ responded positively to visual enhancements, their differing responses to the same conditions underscore the importance of tailoring rearing protocols as mating stimuli at their original location may be associated with specific environmental features. These findings offer preliminary guidance for improving the colonisation and maintenance of An. funestus in laboratory settings, while highlighting the need for further research to improve mating success for this species.
New conceptual and technological developments bring neuroscientists closer to other disciplines and other fields in neuroscience with different traditions. Although some neuroscientists may underrate the potential benefits of successful interdisciplinary collaborations, others may be unaware of the typical difficulties of such collaborations or are not trained in skills that render them fruitful. Here, we argue that interdisciplinary interactions have long been part of neuroscience, although they are often challenging, because neuroscientists may be confronted with concepts, assumptions, and interpretative horizons that differ from their own. This can lead to misunderstandings and little mutual appreciation. Using the historical development of brain imaging techniques, we distinguish between different types of interdisciplinary interactions and illustrate some of their benefits. In addition, we present various challenges for collaborations at the interface between traditional laboratory-type approaches and those of clinical or computational neuroscience or of ecological field approaches. To address these challenges, we invite neuroscientists to consider philosophers as collaboration partners with complementary expertise, which includes special consideration of language use, underlying assumptions and proficiency in conceptual analysis. This expertise can be used by neuroscientists to increase their understanding and address some difficulties in interdisciplinary interactions more effectively. The benefits of these interactions can be expected to outweigh challenges in the dialogue with philosophers. Importantly, neuroscientists can choose between reading philosophical literature, participating in joint events with philosophers, and integrating philosophers into neuroscience projects. This may allow neuroscientists to explore unforeseen possibilities to improve or initiate collaborations with scientists from other fields and disciplines.
Diabetic foot complications (DFCs) are common diabetes complications. Existing tools for predicting incident DFCs remain insufficient. This study aimed to develop and validate a novel machine learning-based model for incident DFC prediction. Using UK Biobank data, we built a longitudinal incident DFC cohort, with DFCs identified using International Classification of Diseases codes. Clinical features were screened by Cox models, and a machine learning model (DFC-Clin) was developed using fivefold cross-validation and leave-one-center-out validation. Performance was compared with diabetic foot risk stratification tools using the DeLong test. A web-based tool and risk stratification system were also developed. Among 502,175 participants, 29,766 individuals formed the incident cohort, with 1,252 incident DFC events. Demographics, blood markers, lifestyle factors, and comorbidities were selected to construct DFC-Clin, with glycated hemoglobin and body mass index emerging as the most predictive features. The model showed improved discrimination compared with existing risk stratification tools, achieving area under the receiver operating characteristic curves of 0.782 ± 0.042, 0.766 ± 0.042, and 0.747 ± 0.021 for 5-year, 10-year, and overall incident DFC prediction, respectively. DFC-Clin is a machine learning model for incident DFC prediction that uses accessible clinical features from a large population-based cohort and is coupled with a web-based application and risk stratification system. DFC-Clin estimates the risk of incident DFC across multiple time horizons and demonstrates improved discrimination compared with existing approaches. The web-based application and stratification framework are intended to support risk identification and preventive decision-making. Further studies are required for clinical deployment and evaluation on more clinical outcomes, including amputations, recurrence, and health care costs.[Figure: see text][Figure: see text][Figure: see text].
Ambient documentation tools (ADTs) are an emerging technology designed to help clinicians complete documentation more effectively with less time and effort. This study aimed to understand the impact of ADT on the pharmacist care experience. Data from Epic Signal, surveys, and interviews were collected between February 2024 and October 2025 for 41 medication therapy disease management (MTDM) pharmacists given ADT licenses across 33 primary care and subspecialty clinics at a large integrated health system. Study variables included the pharmacist ADT utilization rate and changes from before to after ADT implementation in the time spent in notes per encounter, as well as pharmacists' perceptions of documentation burden, patient access, undivided attention for patients, afterhours documentation, and burnout. Quantitative data were analyzed using descriptive statistics, regression models, and comparative tests of pre- vs postimplementation statistical significance and effect size. Qualitative data were mined for exemplary excerpts to deepen understanding. Thirty pharmacists from 28 clinics utilized ADT and provided usable responses. ADT was utilized for 65% of eligible encounters, and the average time in notes per encounter fell by 86 seconds after ADT implementation (P < 0.001). Pharmacist perceptions of documentation burden (P < 0.0001), undivided attention ability (P < 0.0001), and afterhours documentation (P = 0.003) improved after ADT implementation. Interview responses were largely positive for most variables and revealed multiple explanatory mechanisms. ADT meaningfully improved several care experience aspects for MTDM pharmacists over a short period of time (in 2 to 7 months). Future research with larger samples and longer time horizons across multiple health systems is needed to investigate the full and sustained impact of ADT on the care experience.
Oil bodies are a synapomorphy of liverworts (Marchantiophyta), a major group of land plants with a sparse fossil record. Paleozoic liverworts sometimes possess dark cells that appear similar in distribution to liverwort oil body cells. The Middle Devonian Metzgeriothallus sharonae provides an opportunity for comparison with modern liverworts. Shale samples were collected, and the carbonaceous fossils were isolated by acid maceration. Museum shale specimens of Pallaviciniites devonicus were also obtained and processed. The relative location, frequency, and spatial distribution of the fossil dark cells were compared to those of oil body cells in extant taxa. Quantitative analyses revealed that the frequency and spatial distribution of dark cells are comparable to those of oil body cells. Microscopy results show evidence of oil body membranes within dark cells. The dark cells of M. sharonae show clumping near the thallus margin, suggesting an anti-herbivore function. These results support the hypothesis that the dark cells of Paleozoic liverworts and the oil body cells of extant lineages are homologous structures with a shared developmental origin, providing a new character that can aid in the classification of fossils and that sheds light on the evolution and function of liverwort oil bodies.
Anticoagulation for stroke prevention in subclinical, device-detected atrial fibrillation (AF) remains an area of clinical equipoise, and its cost-effectiveness is unknown. To evaluate the cost-effectiveness of direct oral anticoagulant (DOAC) therapy in patients with device-detected AF. This economic evaluation was a cost-effectiveness analysis using a Markov model comparing initiation of DOAC therapy vs no anticoagulation over a 10-year time horizon. Base-case analyses modeled 10 000 patients per strategy with device-detected subclinical AF, with baseline characteristics and risks of stroke, bleeding, and mortality reflecting those observed in randomized clinical trials. The evaluation was conducted from the health system perspective, with treatment and event costs derived from Nordic health care data. The modeling was conducted on March 10, 2026. The associations of DOAC therapy with the risk and severity of clinical events were incorporated into the analysis, based on a meta-analysis of trials evaluating DOAC therapy in subclinical AF. Probabilistic sensitivity analysis also considered the 95% CIs in the reported treatment effect sizes. Incremental quality-adjusted life-years (QALYs), costs, and the incremental cost-effectiveness ratio (ICER; cost difference per QALY gained) from a health system perspective, with 3% annual discounting of both costs and QALYs. Cost-effectiveness was assessed using a €50 000 per QALY willingness-to-pay threshold. The mean age of the 20 000-person simulated cohort was 77 years. In the base case analysis, DOAC therapy was associated with an additional 0.016 QALYs and an incremental cost of €1676 per patient, resulting in an ICER of €105 293 per QALY. In probabilistic sensitivity analysis, DOAC therapy was cost-effective in 35% of simulations and dominated in 38%, with a mean QALY gain of 0.016 per patient, a mean incremental cost of €2883 per patient, and a mean ICER of €176 772. Probabilistic sensitivity analyses by CHA2DS2-VASc (congestive heart failure; hypertension; age ≥75 years; diabetes; prior stroke, transient ischemic attack, or thromboembolism; vascular disease; age 65-74 years; and sex category) score showed probabilities of cost-effectiveness of 31%, 41%, and 52% for patients with scores less than 4, of 4, and greater than 4, respectively. This economic evaluation found that routinely initiating DOAC therapy in all patients with device-detected subclinical AF is unlikely to be cost-effective. Whether treatment is cost-effective in patients with very high CHA2DS2-VASc scores is uncertain.
Innovative pedagogies and support systems are critical for engaging diverse students in biochemistry and molecular biology education. This qualitative study explored biomedical science students' experiences of teaching, learning and support at a UK post-92 university through surveys and focus groups (n = 15). Reflexive thematic analysis revealed three themes. Students' motivations were shaped by scientific curiosity and career aspirations in bioscience. Barriers to progression included financial strain, pandemic-related disruption to laboratory access and cultural exclusion. Support and belonging were mediated through peer networks, while institutional support was inconsistently accessed and curriculum gaps limited experiential skill development in practical laboratory work. The findings underscore the need for pedagogies that blend active, experiential learning with codesigned curricula and integrated support. Such innovations are crucial for creating inclusive bioscience learning environments, improving retention and addressing structural inequalities in science education. These insights provide actionable guidance for biochemistry and molecular biology educators seeking to enhance student engagement and success.
Phthalates are ubiquitous environmental contaminants and suspected endocrine disruptors, used as plasticizers and constituents of fragrances. Regulation of their use in consumer products has largely been guided by male reproductive outcomes. However, as evidenced in rodent models, extended contact with phthalates also affects ovarian function. Data from human ovarian samples, ovary-derived cell lines, and epidemiological studies of infertile patient cohorts have demonstrated adverse associations between phthalate-related chemical burden and female fertility. Due to the sustained use of phthalate-containing products, women may experience earlier fertility decline. These outcomes can be linked to molecular disturbances in ovarian follicles, where phthalate metabolites are frequently detected. This review synthesizes current human evidence on phthalate impacts on the ovary.
Background: Atopic dermatitis (AD) is a chronic and burdensome condition that causes intense itching and painful skin lesions and affects around 10% of adults and adolescents across the US. Potent systemic treatments, such as tralokinumab, are needed to treat patients with moderate-to-severe disease who have experienced inadequate symptom control using topical therapies. Novel systemic treatments can not only provide effective relief for these patients but can also be cost saving. Aim: To evaluate the budgetary implications of tralokinumab as a treatment for moderate-to-severe AD in a hypothetical US commercial healthcare plan with 1 million (M) members. Materials & methods: A budget impact model was developed to estimate the difference in total systemic treatment costs between two scenarios: one in which dupilumab, lebrikizumab, nemolizumab, abrocitinib and upadacitinib are assumed to be the only treatments available, and one in which tralokinumab is assumed to be an additional option. The analysis took the perspective of a US commercial payer and estimated total treatment costs over a 3-year time horizon. Patients were distributed to treatments based on forecasted market share data and could switch from dupilumab to other systemic treatments in the model at any time. Switching rates were also informed using forecasting data. Adult patients receiving tralokinumab and adults or adolescents receiving lebrikizumab and nemolizumab could switch to a lower frequency administration schedule if they achieved clear or almost clear skin, reducing the number of doses received and consequently the treatment costs. Treatment costs were informed by 2025 wholesale acquisition costs. Results: Total costs when tralokinumab was not available were estimated to be $21.0 M, $27.7 M and $35.9 M in years 1-3, respectively. When tralokinumab was available, estimates were $20.6 M (Δ-0.5 M) in year 1, $26.6 M (Δ-1.1 M) in year 2 and $34.1 M (Δ-1.8 M) in year 3. Therefore, availability of tralokinumab led to cumulative cost savings of $3.4 M across all 3 years ($2.3 M in adults and $1.1 M in adolescents). Cumulative treatment costs per plan member at year 3 also reduced from $84.68 to $81.26 (Δ-3.42) due to tralokinumab. Lastly, cumulative per patient treatment costs across the 653 patients estimated to receive systematic therapy over the 3 years reduced from $129,794 to $124,556 when tralokinumab was available. Conclusion: Tralokinumab is a cost-saving therapy when used for the treatment of moderate-to-severe AD in both adult and adolescent populations, with cost savings driven by competitive skin clearance rates, low monthly treatment costs and flexible dosing options in adults (i.e., Q2W → Q4W). What is this article about? This article reports the estimated cost implications of providing tralokinumab as a treatment option for patients with moderate-to-severe eczema; a debilitating condition that affects many adults and adolescents in the US. What were the results? Costs were estimated and compared for two scenarios: one where tralokinumab was available and one where it was not. The differences in total costs between these scenarios represented the cost implications associated with tralokinumab use. Results showed that tralokinumab had the potential to reduce total treatment costs for moderate-to-severe eczema for both adults and adolescents by a cumulative total of $3.4 million over a 3-year period. Why is this important? Eczema treatments that provide cost savings are important as they help to manage the ever-increasing healthcare costs associated with the disease, which put pressure on the budgets of commercial and public healthcare providers. The evidence provided by this research suggests that tralokinumab has cost-saving potential and our findings can be used to inform decisions around which treatments are offered to patients with moderate-to-severe eczema.
The SYMPATICO trial demonstrated that ibrutinib combined with venetoclax significantly improved progression-free survival in patients with relapsed or refractory (R/R) mantle cell lymphoma (MCL). This study evaluated the cost-effectiveness of the combination of ibrutinib-venetoclax for R/R MCL from the healthcare perspectives of China and the United States (US). A partitioned survival model with a 35-year simulation time horizon was developed to compare the cost-effectiveness of ibrutinib-venetoclax versus ibrutinib-placebo. Primary outcomes included total costs, life-years (LYs), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). The robustness of the model was evaluated through one-way sensitivity analysis (OWSA) and probabilistic sensitivity analysis (PSA). Base-case analysis showed that the ICER of ibrutinib-venetoclax versus ibrutinib-placebo was $128,183.93/QALY in China, which was significantly higher than the willingness-to-pay (WTP) threshold of $40,334/QALY. It was still not cost-effective below the $150,000/QALY WTP threshold in the US, with an ICER of $951,082.87/QALY. OWSA demonstrated the robustness of the model. PSA showed that ibrutinib-venetoclax had a 0% probability of being cost-effective under the current WTP thresholds in China and the US. Price reduction analysis indicated that in China, reducing the price of venetoclax to 20% of its original cost could achieve cost-effectiveness with a 60.80% probability. In the US, a combined price reduction of ibrutinib and venetoclax to 22.53% of their original costs is necessary to achieve a 50% probability of cost-effectiveness. Ibrutinib-venetoclax is unlikely to be cost-effective versus ibrutinib-placebo for R/R MCL in both China and the US.
To describe the short-term and long-term mortality of pulmonary embolism patients admitted to the ICU. Retrospective cohort study of data from the Netherlands Intensive Care Evaluation registry. All ICUs in the Netherlands. All adult critically ill patients (≥ 18 yr) with pulmonary embolism as ICU admission diagnosis between 2013 and 2023 were included in the study. None. The primary outcome is hospital mortality for patients with pulmonary embolism admitted to the ICU, as this represents short-term outcomes of pulmonary embolism and its treatment. The secondary outcome was 1-year mortality as a long-term outcome. Next, we compared patient characteristics and outcomes for survivors and nonsurvivors of the hospital admission. Of 10,210 eligible patients, 1,506 patients died (14.6%) during admission. This hospital mortality rate was higher in high-risk pulmonary embolism patients (n = 1372, 25.4%) than in non-high-risk pulmonary embolism patients (n = 134, 2.8%). Multivariable analysis also shows a higher 1-year mortality rate in high-risk pulmonary embolism patients than in non-high-risk pulmonary embolism patients (hazard ratio [HR], 3.98; CI, 3.59-4.40). The 1-year mortality of hospital survivors after hospital discharge is also higher in high-risk pulmonary embolism patients than in non-high-risk pulmonary embolism patients (HR, 1.70; CI, 1.49-1.96). This nationwide registry study confirmed that high-risk pulmonary embolism patients have a higher mortality than patients with non-high-risk pulmonary embolism admitted to the ICU. The unfavorable difference in mortality risk persists in the first year after hospital discharge. These numbers should be considered when making management decisions in patients with pulmonary embolism.
Variation in the expression of behavior is a critical measure for understanding how socio-ecological factors shape cognitive and behavioral evolution and adaptability. Detailed descriptions of behavioral repertoires and how they are combined and structured into programs of actions is an essential foundation for this work. However, comparisons within and across species are made challenging where there is substantial variation in the level of detail at which behaviors are described. Here, we use a systematic, multi-level framework to describe a recently reported chimpanzee tool use behavior-algae fishing-at three levels of granularity: Functional Behavioral Categories, Behaviors, and Behavioral Elements. We then describe how these units are combined into structured programs of action. Despite variation in the detail at which tool use behaviors are described in the literature, we suggest that chimpanzees' algae fishing repertoire is relatively large, as compared to other forms of chimpanzee tool using, and flexibly deployed at each level of description. The varied use of techniques by adults suggests that there is no single optimal solution for algae fishing, and that chimpanzees benefit from maintaining multiple strategies for this dynamic foraging challenge. We provide an example of a structured framework that can be applied to describe different levels of detail and used to show within- and between-task variation. Systematic frameworks that can be consistently applied across species and contexts are critical for providing the like-with-like comparisons necessary for robust investigations of species-level cognition and behavior.
Social event cognition draws on both higher level semantic processes and lower level mechanisms in visual perception. However, the interaction between these levels has not yet been precisely characterized. The present article investigates whether the visual perception of social events is encapsulated from the direct, top-down influence of semantic information. To test this, we leverage a phenomenon reflecting the visual perception of social relations: the two-body inversion effect. Across a series of experiments conducted on French-speaking participants (N = 373), we identified a novel semantic priming effect: Verbs (as opposed to nouns) selectively enhance responses to socially relevant stimuli. However, the two-body inversion effect itself was not influenced by this priming effect, suggesting that the visual perception of social events is encapsulated from higher level semantic processes. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Non-native plant pests can pose major threats to biodiversity, with destructive ecological and economic consequences. The ability to predict future threats would allow limited resources to be concentrated on managing the most serious risks. We built a Bayesian model to predict hosts at risk from Agrilus, a beetle genus of over 3000 species including one of the world's worst tree pests, using phylogenetic and geographic relationships between known and potential hosts. We assess risk to Quercus (oak), their most common host, by predicting the probability of over 7000 possible oak-Agrilus interactions to identify species at risk and inform future prevention efforts. Our model detects known hosts with 83.6% accuracy under Leave-One-Out cross-validation, and successfully classifies novel hosts of Agrilus species in new areas, indicating strong predictive performance on independent or misclassified data. Geographic proximity is a strong predictor of host sharing, with the likelihood declining rapidly with distance. In general, hosts cluster phylogenetically, with a tendency for closely related oaks to share the same Agrilus species. Our approach uses readily available data and could be implemented to assess Agrilus interactions with other plant genera, and extended to additional host-pest systems to help prioritise countermeasures against threats world-wide. Las plagas no nativas de plantas pueden representar graves amenazas para la biodiversidad, con consecuencias ecológica y económicamente devastadoras. La predicción de futuras amenazas permitiría concentrar los limitados recursos disponibles para la gestión de los riesgos más graves. Aquí, desarrollamos un modelo bayesiano para predecir posibles nuevas plantas huésped de Agrilus, un género de escarabajo con más de 3.000 especies que incluye a una de las peores plagas arbóreas del mundo, usando relaciones filogenéticas y geográficas entre huéspedes conocidos y potenciales. Evaluamos el riesgo para Quercus (roble), su huésped más común, prediciendo la probabilidad de más de 7.000 posibles interacciones roble–Agrilus, para identificar especies en riesgo e informar futuras medidas de prevención. Nuestro modelo detecta huéspedes conocidos con una precisión de 83,6% en validación cruzada dejando uno fuera (‘Leave‐One‐Out’), y clasifica con éxito nuevos huéspedes de especies de Agrilus que ya han invadido áreas nuevas. Esto indica un sólido rendimiento predictivo sobre datos independientes o mal clasificados. La proximidad geográfica es un fuerte predictor del uso compartido de huéspedes, cuya probabilidad disminuye rápidamente con la distancia. En general, las especies huésped se agrupan filogenéticamente. Los robles estrechamente emparentados suelen compartir la misma especie de Agrilus. Nuestro enfoque utiliza datos fácilmente disponibles y puede implementarse para evaluar interacciones de Agrilus con otros géneros de plantas, así como ser extendido a otros sistemas huésped–plaga para ayudar a priorizar medidas de control frente a riesgos a escala mundial.
GAT-1 is a neurotransmitter:sodium symporter responsible for the reuptake of GABA from the synaptic cleft. Because of its involvement in various pathological conditions, it is an important target for drug development; however, its mechanism of action remains under debate. Using high-resolution solid-supported membrane-based electrophysiology, we identified three sequential electrogenic events (E1, E2, and E3) in human GAT-1-mediated GABA transport. E1 reflects the transition to an occluded intermediate, upon GABA binding to the Na+ bound carrier; E2 was attributed to an uncoupled Na+ conductance triggered by GABA binding, while E3 represents Na+-coupled GABA transport. This triphasic model provides a robust electrophysiological framework for dissecting individual molecular transitions in the GAT-1 transport cycle. We also established a 2 : 1 stoichiometry for Na+ : GABA cotransport under standard conditions. However, this stoichiometric relationship breaks down under conditions of steep transmembrane Na+ gradients, which promote an uncoupled Na+ leak current. Our data further suggests that Cl- translocation is not coupled to GABA transport. These findings refine the current understanding of the GAT-1 transport mechanism, providing a foundation to support the development of novel therapeutics.
Critically ill and high-risk perioperative patients requiring intensive care are often multimorbid and depend on rapid, highly specialized management. While most comorbidities are difficult to modify in the acute setting, anemia, particularly iron-defi ciency anemia, represents a potentially modifiable risk factor. Clinicians are also often confronted with complex alterations in hemostasis that require rapid assessment and targeted therapeutic interventions, including the optimal use of blood products. This narrative review summarizes the current evidence on Patient Blood Management strategies, including anemia management, the use of small-volume tubes, and the appropriate use of blood products in intensive care unit patients. Intravenous iron supplementation can safely raise hemoglobin to a clinically meaningful degree. Erythropoietin therapy may also raise hemoglobin, but its use should remain selective given uncertain thromboembolic risk. Small-volume blood collection tubes and closed blood-conservation systems should be routinely used to reduce iatrogenic anemia. Current evidence supports restrictive red blood cell transfusion strategies in most clinical settings, particularly in patients with gastrointestinal bleeding. Similarly, a restrictive platelet transfusion strategy is supported by current evidence. Prophylactic platelet transfusion should be reserved for high-risk hematologic malignancies. In other critically ill patients with severe thrombocytopenia, a therapeutic (bleeding-driven) approach is preferred. Finally, current evidence does not support prophylactic fresh frozen plasma transfusion in non-bleeding patients. Overall, these findings support the implementation of Patient Blood Management strategies that optimize blood health and promote safer, more individualized care in critically ill patients.
In recent years, millions of adolescents have joined school strikes to demand climate action from governments and industries, standing in solidarity with young people from future generations and from vulnerable geographical regions (i.e., the Global South). The goal of the present study is to explore adolescents' climate activism from a developmental science perspective, analyzing how climate activism may be rooted in adolescents' developing identity and developmentally salient motives. Eleven 14-18-year-old Dutch adolescent climate activists (six female, two male, one non-binary, two not disclosed) participated in an online semi-structured interview between September 2022 and 2023. Data were analyzed in NVivo through theoretical reflexive thematic analysis, exploring patterns of meaning across the dataset while embracing researchers' active, subjective, and reflective role in data analysis. We constructed three themes: "Activism is motivated by the desire to make contributions to a just world;" "Activism is an autonomous choice that helps explore and express who I am;" and "Activism makes me feel connected to (some but not all) others." Taken together, the present analysis suggests that adolescents' climate activism-and pro-environmental engagement more generally-is driven by and satisfies their developmentally salient motives to contribute to a socially just world, to make autonomous choices, to explore and express their identity, and to feel connected to others. As such, our work sheds light on how we may promote and support adolescents' engagement in acts of solidarity to contribute to today's societal challenges, and suggests avenues for further research.
Cortical lesions (CLs) are a common finding in multiple sclerosis (MS) but data regarding the impact of treatment on their evolution are lacking. This study evaluates CLs status and new CLs accrual over two-year follow-up in a cohort of patients treated with ocrelizumab (OCR) and the correlation with brain structural metrics and clinical measures. 87 relapsing-remitting MS patients [59 (67.8%) women, mean (SD) age 39.2 (10) years, median (IQR) baseline EDSS 2.5 (1.75)] underwent clinical, neuropsychological assessment and brain 3T MRI at baseline and two years after OCR start. CLs were manually segmented using Artificial Intelligence-Driven Imaging Reconstruction (AIDIR) sequences. At baseline, 21 patients (24.1%) had no CLs, 30 (34.5%) had 1 CL, 17 (19.5%) had 2 CLs, and 19 (21.8%) had ≥ 3 CLs. Higher CLs number and volume were associated with lower normalized TBV (r = -0.29, p = 0.01; r = -0.23, p = 0.03) and SDMT-raw score (r = -0.28, p = 0.02; r = -0.26, p = 0.03). After multiple-comparison correction, CLs number remained associated with normalized TBV. 14 patients (16.1%) experienced white matter lesions (WMLs) accrual and 15 patients (17.2%) disability progression over follow-up, but none of them developed new CLs. We observed the formation of only one CL at follow-up in a female patient that showed improved physical disability and no cognitive decline without concurrent WMLs accrual. OCR might also prevent lesion-driven cortical atrophy. These data seem to confirm the role of cortical pathology as an early marker of disease severity in MS, support OCR efficacy in minimizing lesion accrual and suggest distinct mechanisms underlying CLs and WMLs development.