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Abstract Microglia and the border-associated macrophages contribute to the modulation of cerebral blood flow, but the mechanisms have remained uncertain. Here, we show that microglia regulate the cerebral blood flow baseline and the responses to whisker stimulation or intra-cisternal magna injection of adenosine triphosphate, but not intra-cisternal magna injection of adenosine in mice model. Notably, microglia repopulation corrects these cerebral blood flow anomalies. The microglial-dependent regulation of cerebral blood flow requires the adenosine triphosphate-sensing P2RY12 receptor and ectonucleotidase CD39 that initiates the dephosphorylation of extracellular adenosine triphosphate into adenosine in both male and female mice. Pharmacological inhibition or CX3CR1-CreER-mediated deletion of CD39 mimics the cerebral blood flow anomalies in microglia-deficient mice and reduces the upsurges of extracellular adenosine following whisker stimulation. Together, these results suggest that the microglial CD39-initiated breakdown of extracellular adenosine triphosphate co-transmitter is an important step in neurovascular coupling and the regulation of cerebrovascular reactivity.

Background and aims – Ongoing studies on Colombian mistletoes revealed an undescribed species of Maracanthus (Loranthaceae) endemic to the Colombian Eastern Cordillera (Cordillera Oriental). This species is described and illustrated here, and a checklist of the species accepted in Maracanthus is also provided, including a taxonomic key, references to the known iconography of the genus, and taxonomic and geographic comments. Material and methods – This study is based on a literature review according to the International Code of Nomenclature for Algae, Fungi, and Plants, examination of herbarium specimens using physical specimens and digital images, and morphological studies based on samples from dried and rehydrated specimens. Key results – A detailed morphological analysis revealed that the new species is part of the little-known genus Maracanthus. The dichotomous key, as well as the taxonomic and geographic notes, allow users to recognise the five known species in this genus, showing that they occur in restricted distribution areas.

Abstract The present study was aimed at revealing the metabolic changes that occurred in the cellular lipid pattern of acute and chronic myeloid leukaemia cells following treatment with cannabidiol (CBD). CBD is a non-psychoactive compound present in Cannabis sativa L., which has shown an antiproliferative action in these type of cancer cells. CBD treatment reduced cell viability and initiated apoptotic and necrotic processes in both cancer cell lines in a time and dose-dependent manner, showing acute myeloid leukaemia (HL-60) cells greater sensitivity than chronic myeloid leukaemia ones (K-562), without differences in the activation of caspases 3/7. Then, control and treated cells of HL-60 and K-562 cell lines were studied through an untargeted lipidomic approach. The treatment was carried out with CBD at a concentration of 10 μM for HL-60 cells and 23 µM CBD for K-562 cells for 48 h. After the extraction of the lipid content from cell lysates, the samples were analysed by UHPLC-QTOF-MS/MS both in the positive and the negative ionization modes. The comprehensive characterization of cellular lipids unveiled several classes significantly affected by CBD treatment. Most of the differences correspond to phospholipids, including cardiolipins (CL), phosphatidylcholines (PC) and phosphosphingolipids (SM), and also triacylglycerols (TG), being many TG species increased after CBD treatment in the acute and chronic models, whereas phospholipids were found to be decreased. The results highlight some important lipid alterations related to CBD treatment, plausibly connected with different metabolic mechanisms involved in the process of cell death by apoptosis in cancer cell lines.

Abstract Symbolic anchoring is an important topic in robotics, as it enables robots to obtain symbolic knowledge from the perceptual information acquired through their sensors and maintain the link between that knowledge and the sensory data. In cognitive-based robots, this process of transforming sub-symbolic data generated by sensors to obtain and maintain symbolic knowledge is still an open problem. To address this issue, this paper presents SAILOR, a framework for symbolic anchoring integrated into ROS 2. SAILOR aims to maintain the link between symbolic data and perceptual data in real robots over time. It provides a semantic world modeling approach using two deep learning-based sub-symbolic robotic skills: object recognition and matching function. The object recognition skill allows the robot to recognize and identify objects in its environment, while the matching function enables the robot to decide if new perceptual data corresponds to existing symbolic data. This paper describes the proposed method and the development of the framework, as well as its integration in MERLIN2 (a hybrid cognitive architecture fully functional in robots running ROS 2) and the validation of SAILOR using public datasets and a real-world scenario.

Abstract Climate classification systems (CCSs) are emerging as essential tools in climate change science for mitigation and adaptation. However, their limitations are often misunderstood by non-specialists. This situation is especially acute when the CCSs are derived from Global Climate Model outputs (GCMs). We present a set of uncertainty maps of four widely used schemes -Whittaker-Ricklefs, Holdridge, Thornthwaite-Feddema and Köppen- for present (1980–2014) and future (2015–2100) climate based on 52 models from the Coupled Intercomparison Model Project Phase six (CMIP6). Together with the classification maps, the uncertainty maps provide essential guidance on where the models perform within limits, and where sources of error lie. We share a digital resource that can be readily and freely integrated into mitigation and adaptation studies and which is helpful for scientists and practitioners using climate classifications, minimizing the risk of pitfalls or unsubstantiated conclusions.

Abstract Sponges are key ecosystem engineers that shape, structure and enhance the biodiversity of marine benthic communities globally. Sponge aggregations and reefs are recognized as vulnerable marine ecosystems (or VMEs) due to their susceptibility to damage from bottom-contact fishing gears. Ensuring their long-term sustainability, preservation, and ecosystem functions requires the implementation of sound scientific conservation tools. Here, the genetic diversity, structure, and connectivity of the deep-sea glass sponge, Vazella pourtalesii (Schmidt, 1870), was investigated using 1,102 neutral SNPs obtained in RADseq. This species is distributed across the northwest Atlantic from Florida, USA to Nova Scotia, Canada and we sequenced samples covering this full distribution and provided evidence of strong genetic structure with two distinct clusters: Florida together with the Carolina Shelves and the Scotian Shelf. We estimated moderate levels of diversity with low migration across large distances (> 1000 kms) and high connectivity at smaller scales (

Social pain is emotional distress caused harm or threat to social connections that results in social exclusion, rejection, or loss. Social Pain is also a potentiator of physical pain. Supportive social relationships are widely recognized for their impact on maintaining health and well-being. The Passion of Jesus Christ serves as a quintessential example of social pain (i.e., desertion, betrayal, denial) potentiating physical pain (i.e., beatings, Crown of Thorns, crucifixion). Christ opts to forgive. Although forgiveness is one solution to reduce social pain, other interventions exist. This review seeks to identify and summarize interventions associated with reducing social pain. We conducted a systematic review using Medline (PubMed), Google Scholar, and Cochrane CENTRAL to identify relevant articles. Results: The database searches produced 548 articles. Fourteen randomized controlled trials (RCTs) were included in this systematic review. Acetaminophen, both deceptive and open-label placebos, mindfulness training, and psilocybin were found to reduce social pain. Of note, the combination of acetaminophen and forgiveness yielded superior results compared to either acetaminophen or forgiveness alone. Pharmacological interventions operate on the premise that the neural pathways responsible for physical pain also play a role in social pain. Both pharmacological and non-pharmacological interventions are available for reducing social pain.

ABSTRACT Computer graphics aim to create visual representations for screens, where depth is simulated. In contrast, Computed Generated Holograms (CGH) focus on encoding and recreating light patterns to generate a true 3D holographic image that appears as a physical object in space. Therefore, although both use digital models, the computation of CGHs necessitates additional phase‐related calculations, which in turn escalate computational demands. These calculations often result in excessively long development times or, at worst, render the process unfeasible. In order to reduce computational time, Partial Monte–Carlo Sampling (PMCS) techniques for CGH generation are presented, integrating them into the whole process of generating a CGH for a synthetic 3D scene, from design to rendering. PMCS is based on the random choice of a subset of rays used to compute the CGH and relates the computation time spent to the quality of the reconstructed scene. Quantitative analysis shows that PMCS does not significantly compromise image quality. Both simulated and in‐laboratory image reconstruction from holograms demonstrates consistent trends, showcasing improved quality with higher numbers of rays and increased resolution. Furthermore, we establish a direct relationship between image quality and computational time, which effectively addresses specific requirements.

Background: Small conjunctival incision size is desirable in strabismus surgery under topical anesthesia. Objective: To study the feasibility and tolerability of a small bulbar conjunctival incision (SB). Design: Non-randomized feasibility pilot study. Methods: After applying a 5-0 PGA (polyglycolic acid) traction suture, we did a 3–4 mm single conjunctival incision posterior and parallel to the rectus muscle insertion. A hang-back recession was done (6-0 PGA suture), and the conjunctiva closed (8-0 PGA suture). The outcome measures were feasibility, tolerability, and motor result. Results: Twenty-five patients were included. The median pain scale score was 3/10, and the satisfaction Net Promoter Score was 72. Mean duration of a recession was 12 min (range: 9–14 min). Mean duration of inflammatory signs and hemorrhage were 2.2 days (95% CI, 1.4–2.9), and 8.5 days (95% CI, 7.1–9.9), respectively. Distance deviation at 2 months was 3.1 Prism Diopters (95% CI, 1.5–4.5). Conclusion: SB is feasible and well tolerated for extraocular rectus muscle surgery.

BackgroundDifficult-to-treat rheumatoid arthritis (D2T RA) refers to a subset of patients who fail to achieve adequate disease control after the use of two or more biological or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) with different mechanisms of action, while maintaining active inflammatory disease. This presents a therapeutic challenge and highlights the need to explore contributing factors such as the potential role of the gut microbiota. Therefore, the aim of this study was to analyze the gut microbiota and inflammation in patients with D2T RA in comparison to patients with easy-to-treat RA (E2T RA).ObjectiveTo analyze the gut microbiota and inflammation in patients with D2T RA.MethodsWe performed an observational study of a prospective cohort between 2007 and 2011 and analyzed the gut microbiota. In 2022, we identified 2 extreme patient phenotypes: (1) D2T RA, which was defined as failure of ≥2 biological or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) (with different mechanisms of action) plus signs of active disease; and (2) easy-to-treat RA (E2T RA), i.e., stable disease managed with a single treatment. The gut microbiota was analyzed using 16S rRNA gene sequencing; bioinformatics analysis was performed using QIIME2, and its functionality was inferred through PICRUSt. We recorded data on clinical findings, inflammation, and cytokines. A Cox multivariate analysis was performed to identify factors related to D2T RA.ResultsThe study population comprised 39 patients: 13 (33%) with D2T RA and 26 (66%) with E2T RA. The families Lachnospiraceae and Pasteurellaceae, and their genera Coprococcus and Haemophilus were more abundant in E2T RA patients, while the genus Megasphaera was more abundant in D2T RA patients. The Firmicutes/Bacteroidetes ratio decreased in D2T RA patients. The metabolic profile of the gut microbiota was characterized by differences in Degradation/Utilization/Assimilation pathway and the Biosynthesis pathway. The factors associated with D2T RA were inflammatory activity according to DAS28-ESR (HR, 2.649; p = 0.013), prednisone (HR, 3.794; p = 0.008), and the Firmicutes/Bacteroidetes ratio (HR, 0.288; p = 0.033).ConclusionThe composition of the gut microbiota of patients with D2T RA differed from that of E2T RA patients, as did the metabolic pathways.

Although prediction models for heart transplantation outcomes have been developed previously, a comprehensive benchmarking of survival machine learning methods for mortality prognosis in the most contemporary era of heart transplants following the 2018 donor heart allocation policy change is warranted. This study assessed seven statistical and machine learning algorithms-Lasso, Ridge, Elastic Net, Cox Gradient Boost, Extreme Gradient Boost Linear, Extreme Gradient Boost Tree, and Random Survival Forests in a post-policy cohort of 7,160 adult heart-only transplant recipients in the Scientific Registry of Transplant Recipients (SRTR) database who received their first transplant on or after October 18, 2018. A cross-validation framework was designed in mlr. Model performance was also compared in a seasonally-matched pre-policy cohort. In the post-policy cohort, Random Survival Forests and Cox Gradient Boost had the highest performances with C-indices of 0.628 and 0.627. The relative importance of some predictive variables differed between the pre-policy and post-policy cohorts, such as the absence of ECMO in the post-policy cohort. Survival machine learning models provide reasonable prediction of 1-year posttransplant mortality outcomes and continual updating of prediction models is warranted in the contemporary era.

Peripheral nerve injury (PNI) is characterized by a loss of cellular and axonal integrity, often leading to limited functional recovery and pain. Many PNIs are not amenable to repair with traditional techniques; however, cell therapies, particularly Schwann cells (SCs), offer the promise of neural tissue replacement and functional improvement. Exosomes, which carry cellular signaling molecules, can be secreted by SCs and have shown promise in PNI. Our laboratory has had success using SCs in preclinical and clinical treatment settings. Transplanted cells have several known limitations, which exosomes mitigate. To that end, the current study investigated if implanted SC-derived exosomes in conduits, conduits with SCs, reverse autograft, or empty conduits comparably improve axonal regeneration and pain outcomes 16-weeks after repair of a long gap PNI in adult rats. Results show that there were no differences between groups in the von Frey filament testing or in the Hargreaves test. Electrophysiological testing showed a significant difference between the injured (ipsilateral) and uninjured (contralateral) limbs while histological assessment showed a significant difference between axonal counts in different areas of the conduit. Based on the results of the current study, more research is needed to understand the therapeutic role of exosomes in PNI.

The third edition of the IJMS World Conference of Medical Student Research (WCMSR) highlighted the significance of fostering research opportunities for medical students worldwide. Held on October 26, 2024, the event featured 35 authors from 19 countries, presenting 40 abstracts through oral and video presentations. Accessible to a global audience via YouTube Live, the conference attracted over 1,000 viewers who engaged in discussions and voting. The event emphasized the importance of affordable, inclusive participation, offering students a platform to showcase their research, gain feedback from experts, and build professional networks. With a nominal fee, IJMS removed financial barriers to entry, ensuring equitable access for junior researchers. The conference continues to empower medical students to advance their research, academic, and clinical skills, fostering a global community dedicated to the future of medical science.