Visceral larva migrans syndrome (VLM) is caused by L2 Toxocara canis. This parasitic disease is difficult to diagnose in humans, but specific antigen identification could allow for parasite detection. The aim of this study was to analyse antigens of different parasite developmental stages and observe their cross-reactions with antigens from other parasites to determine their importance in the diagnosis of VLM caused by T. canis. Sera from 14 children with cryptogenic epilepsy previously positive for T. canis were analysed via Western blot (WB) using T. canis excretion-secretion antigens (TESs) from distinct morphological parasite stages; cross-reactivity of these antigens with antigens from other parasites were evaluated. Children sera recognized antigens from L2 T. canis TES, mainly a protein of 24 kDa. Proteins in the medium- and high-molecular-weight ranges were also detected in the egg phase. In the adult phase, only 42.9% of analysed sera recognized a protein of high-molecular weight. Cross-reaction tests identified medium and high-molecular weight proteins, mainly from L2 of Ascaris lumbricoides and Gnathostoma binucleatum and adults of Ancylostoma caninum, but none of the proteins found had crossover with low-molecular weight proteins from Toxocara canis. Antigens in the larval morphological stage of T. canis TES were recognized in the highest percentage of the analysed sera; these antigens could be used to diagnose VLM.

Next-generation X-ray satellite telescopes such as XRISM, NewAthena and Lynx will enable observations of exotic astrophysical sources at unprecedented spectral and spatial resolution. Proper interpretation of these data demands that the accuracy of the models is at least within the uncertainty of the observations. One set of quantities that might not currently meet this requirement is transition energies of various astrophysically relevant ions. Current databases are populated with many untested theoretical calculations. Accurate laboratory benchmarks are required to better understand the coming data. We obtained laboratory spectra of X-ray lines from a silicon plasma at an average spectral resolving power of $\sim$7500 with a spherically bent crystal spectrometer on the Z facility at Sandia National Laboratories. Many of the lines in the data are measured here for the first time. We report measurements of 53 transitions originating from the K-shells of He-like to B-like silicon in the energy range between $\sim$1795 and 1880 eV (6.6–6.9 Å). The lines were identified by qualitative comparison against a full synthetic spectrum calculated with ATOMIC. The average fractional uncertainty (uncertainty/energy) for all reported lines is ${\sim}5.4 \times 10^{-5}$. We compare the measured quantities against transition energies calculated with RATS and FAC as well as those reported in the NIST ASD and XSTAR’s uaDB. Average absolute differences relative to experimentally measured values are 0.20, 0.32, 0.17 and 0.38 eV, respectively. All calculations/databases show good agreement with the experimental values; NIST ASD shows the closest match overall.

Static analysis is an essential component of many modern software development tools. Unfortunately, the ever-increasing complexity of static analyzers makes their coding error-prone. Even analysis tools based on rigorous mathematical techniques, such as abstract interpretation, are not immune to bugs. Ensuring the correctness and reliability of software analyzers is critical if they are to be inserted in production compilers and development environments. While compiler validation has seen notable success, formal validation of static analysis tools remains relatively unexplored. In this paper we present checkification, a simple, automatic method for testing static analyzers. Broadly, it consists in checking, over a suite of benchmarks, that the properties inferred statically are satisfied dynamically. The main advantage of our approach lies in its simplicity, which stems directly from framing it within the Ciao assertion-based validation framework, and its blended static/dynamic assertion checking approach. We demonstrate that in this setting, the analysis can be tested with little effort by combining the following components already present in the framework: 1) the static analyzer, which outputs its results as the original program source with assertions interspersed; 2) the assertion run-time checking mechanism, which instruments a program to ensure that no assertion is violated at run time; 3) the random test case generator, which generates random test cases satisfying the properties present in assertion preconditions; and 4) the unit-test framework, which executes those test cases. We have applied our approach to the CiaoPP static analyzer, resulting in the identification of many bugs with reasonable overhead. Most of these bugs have been either fixed or confirmed, helping us detect a range of errors not only related to analysis soundness but also within other aspects of the framework.

Stroke is a prevalent neurological event that often induces significant motor impairments in the upper extremities, such as hemiplegia, which impacts bimanual coordination and fine motor skills. Robotic-assisted therapy has gained prominence as a contemporary rehabilitation modality, providing augmented motor repetitions and proprioceptive feedback, thereby potentiating neuroplasticity and functional recovery. This pilot study aimed to examine the therapeutic efficacy of a robotic intervention for wrist rehabilitation in two post-stroke adults aged 50–70 years. The intervention protocol, implemented biweekly over four weeks, encompassed 45-minute sessions consisting of passive muscle elongation (5 min) and robotic-facilitated exercises targeting pronation-supination (10 min), flexion-extension (10 min), and radial-ulnar deviation (10 min). Outcome measures included pre- and post-intervention assessments utilizing the motor activity log, Fugl-Meyer Scale, and robotic metrics for muscular strength. Results indicated enhancements in joint range of motion, motor precision, and neuromuscular control, with patient “B” demonstrating superior improvements, particularly in complex motor patterns. In contrast, patient “A” exhibited attenuated progress, attributable to pronounced baseline deficits and fatigue. Specific gains were observed in flexion-extension for patient “A” and pronation-supination for patient “B,” with minimal advancements in radial-ulnar deviation across both subjects. These findings provide preliminary evidence supporting the efficacy of robotic-assisted therapy in motor rehabilitation post-stroke with the novel proposed wrist rehabilitation device.

Portable medical equipment (PME) is inconsistently cleaned and disinfected, resulting in contamination that increases the risk of healthcare-associated infections. A virtual reality PME cleaning and disinfection training module was designed and tested at multiple healthcare facilities. Barriers identified during an initial phase led to improvements in the second phase.

To understand the potential human health effects of exposure to hazardous substances among first responders from the East Palestine train derailment, an electronic self-administered Assessment of Chemical Exposures (ACE) survey was created and available to first responders between February-March 2023. Among the 339 completed responder surveys analyzed, most reported working at least 1 day during the incident between February 3-8, 2023. Most (79%) reported inhaling, touching, or swallowing potentially harmful substances and did not report using a face mask or respirator while working (75%). Nearly half reported at least 1 new or worsening physical symptom after incident response. These findings support several recommendations to mitigate exposure to hazardous substances among first responders during future incidents, including using a hierarchy of controls framework to reduce exposure to hazards, timely communication of possible hazardous substances involved in the event, and using the Emergency Responder Health Monitoring Surveillance (ERHMS) framework.

With the increasing volume of scientific literature, there is a need to streamline the screening process for titles and abstracts in systematic reviews, reduce the workload for reviewers, and minimize errors. This study validated artificial intelligence (AI) tools, specifically Llama 3 70B via Groq’s application programming interface (API) and ChatGPT-4o mini via OpenAI’s API, for automating this process in biomedical research. It compared these AI tools with human reviewers using 1,081 articles after duplicate removal. Each AI model was tested in three configurations to assess sensitivity, specificity, predictive values, and likelihood ratios. The Llama 3 model’s LLA_2 configuration achieved 77.5% sensitivity and 91.4% specificity, with 90.2% accuracy, a positive predictive value (PPV) of 44.3%, and a negative predictive value (NPV) of 97.9%. The ChatGPT-4o mini model’s CHAT_2 configuration showed 56.2% sensitivity, 95.1% specificity, 92.0% accuracy, a PPV of 50.6%, and an NPV of 96.1%. Both models demonstrated strong specificity, with CHAT_2 having higher overall accuracy. Despite these promising results, manual validation remains necessary to address false positives and negatives, ensuring that no important studies are overlooked. This study suggests that AI can significantly enhance efficiency and accuracy in systematic reviews, potentially revolutionizing not only biomedical research but also other fields requiring extensive literature reviews.

Quantum field theory predicts a nonlinear response of the vacuum to strong electromagnetic fields of macroscopic extent. This fundamental tenet has remained experimentally challenging and is yet to be tested in the laboratory. A particularly distinct signature of the resulting optical activity of the quantum vacuum is vacuum birefringence. This offers an excellent opportunity for a precision test of nonlinear quantum electrodynamics in an uncharted parameter regime. Recently, the operation of the high-intensity Relativistic Laser at the X-ray Free Electron Laser provided by the Helmholtz International Beamline for Extreme Fields has been inaugurated at the High Energy Density scientific instrument of the European X-ray Free Electron Laser. We make the case that this worldwide unique combination of an X-ray free-electron laser and an ultra-intense near-infrared laser together with recent advances in high-precision X-ray polarimetry, refinements of prospective discovery scenarios and progress in their accurate theoretical modelling have set the stage for performing an actual discovery experiment of quantum vacuum nonlinearity.

This study aims to empirically test whether family has a unique significance for the self that cannot be captured by the social self alone. Specifically, it examines whether family self-concept, compared to social self-concept, is more closely related to family-specific indicators (i.e., parent–child communication and family functioning) as well as to indicators of emotional maladjustment like mental health deterioration (i.e., psychological distress and depressive symptoms). The sample comprised 4,953 Mexican adolescents, including 2,551 men (51.5%) and 2,402 women, aged 14–17 years (M = 15.60, SD = 0.92). Confirmatory factor analysis was applied to evaluate the proposed big five-dimensional self-concept model. Cohen’s d confidence intervals, derived from the shared variance of Pearson’s r correlations, were analyzed to relate self-concept dimensions to parent–child communication, family functioning, and mental health deterioration. Results from factorial confirmatory analysis showed that the five-dimensional oblique model (i.e., academic, social, emotional, physical, and family, as different from social) provided a better fit than competing unidimensional and orthogonal models. Correlation analyses showed that family self-concept was significantly associated with both parent–child communication and family functioning, as well as with psychological distress (d = −1.10, confidence interval [CI] −1.21 to −1.02) and depressive symptoms (d = −1.24, CI −1.31 to −1.22). These findings add evidence that family is not accurately represented within the social self-concept. Furthermore, perceiving oneself as unloved and undervalued at home (i.e., low family self-concept) is strongly associated not only with dysfunctional family processes but also with mental health deterioration.

Members of Sinistroporomonorchis Wee, Cutmore, Pérez-del-Olmo & Cribb, 2020 represent a small group of trematodes belonging to the Monorchiidae Odhner, 1911 with 5 species described from mugilid hosts. Specimens consistent with the generic concept of Sinistroporomonorchis were obtained from Floridichthys polyommus (Cyprinodontidae); most of them were juveniles from 4 localities within the Yucatán Peninsula. After a detailed morphological examination including scanning electron microscopy images and a principal component analysis, the specimens collected represented a new species, Sinistroporomonorchis bolini n. sp. The new species can be differentiated by the presence of an overall large pharynx including the proportion of pharynx width to oral sucker width, a uterus arranged in 2 main lateral fields, and by presenting robust caeca. In addition, sequences of the 28S of large subunit of nuclear ribosomal RNA and cox1 of the mitochondrial DNA were obtained. Phylogenetic trees inferred from each dataset, placed all the specimens in a monophyletic clade, confirming that the isolates belonged to the same species. The new species is the sixth described for the genus Sinistroporomonorchis, the fifth described from the Yucatán Peninsula and the first described from a non-mugilid host.

Variable sharing is a fundamental property in the static analysis of logic programs, since it is instrumental for ensuring correctness and increasing precision while inferring many useful program properties. Such properties include modes, determinacy, non-failure, cost, etc. This has motivated significant work on developing abstract domains to improve the precision and performance of sharing analyses. Much of this work has centered around the family of set-sharing domains, because of the high precision they offer. However, this comes at a price: their scalability to a wide set of realistic programs remains challenging and this hinders their wider adoption. In this work, rather than defining new sharing abstract domains, we focus instead on developing techniques which can be incorporated in the analyzers to address aspects that are known to affect the efficiency of these domains, such as the number of variables, without affecting precision. These techniques are inspired in others used in the context of compiler optimizations, such as expression reassociation and variable trimming. We present several such techniques and provide an extensive experimental evaluation of over 1100 program modules taken from both production code and classical benchmarks. This includes the Spectector cache analyzer, the s(CASP) system, the libraries of the Ciao system, the LPdoc documenter, the PLAI analyzer itself, etc. The experimental results are quite encouraging: we have obtained significant speedups, and, more importantly, the number of modules that require a timeout was cut in half. As a result, many more programs can be analyzed precisely in reasonable times.

Trematodes are one of the most abundant and diverse groups of platyhelminths. They parasitize all major groups of vertebrates as definitive hosts and therefore play an important role in ecosystem composition. It is estimated that 18,000 to 25,000 species of trematodes exist worldwide, of which 685 have been reported in Mexico. Although this group is an integral part of ecosystems, there are still no studies that highlight the importance of parasites, especially in conservation approaches. Here, we recompiled information on the occurrence and available genetic data of trematodes in Mexico to estimate the specific richness of their representation across the Protected Areas (PAs) and provinces of Mexico. We consulted national and international databases (e.g., GBIF, CONABIO, CNHE-UNAM) and genetic repositories (e.g., GenBank) to generate curated datasets. We obtained 6,780 records that represent 99% of species reported in Mexico (680 species), of which only 10.2% are included in PAs. For genetic data, we found information from five nuclear regions (28S, 18S, ITS1, ITS2 and 5.8S) and two mitochondrial genes (COI and NAD1) for 118 species, of which only 3.5% were associated with PAs. With these results, we provide a spatial distribution of records (occurrence and genetic data) of trematodes present in Mexico and its PAs and identify poorly represented biogeographic provinces (e.g., Sierra Madre del Sur). We also highlight that this is the first study in Mexico to include this group in a conservation approach, and we record valuable information for future studies.

Contrary to the common perception of hyperarid drylands as barren and lifeless, these regions are home to some of the planet’s most unique biodiversity and support over 100 million people. Despite their ecological and human significance, hyperarid drylands remain among the least studied biomes in the world. In this article, we explore how improving our understanding of hyperarid ecosystems in the Middle East can yield valuable insights applicable to other hyperarid regions. We examine how ongoing greening initiatives in the Middle East offer a unique opportunity to deepen our knowledge of dryland ecology and advocate for the establishment of a comprehensive research program in the region. This program would focus on ecosystem functionality across spatial and temporal scales, setting the stage for a global monitoring network for hyperarid drylands. Such efforts would inform conservation strategies and climate change mitigation, while also shedding light on the resilience and adaptability of hyperarid ecosystems to environmental change. Ultimately, this monitoring would guide management practices to preserve biodiversity, enhance ecosystem services and promote sustainable development in hyperarid regions worldwide.

Drosophila suzukii is a pest of global concern due to its great impact on several crops. The entomopathogenic nematode Steinernema carpocapsae was highly virulent to the larvae of the fly although some immune mechanisms were triggered along the infection course. Thus, to understand the gene activation profile we performed a comparative transcriptome of D. suzukii larvae infected with S. carpocapsae and Xenorhabdus nematophila to map the differentially expressed genes involved in the defence response. The analysis exposed the induction of genes involved in the humoral response such as the antimicrobial peptides and pattern-recognition receptors while there was a suppression of the cellular defence. Besides, genes involved in melanisation, and clot formation were downregulated hindering the encapsulation response and wound healing. After the infection, larvae were in a stress condition with an enrichment of metabolic and transport functionalities. Concerning the stress response, we observed variations of the heat-shock proteins, detoxification, and peroxidase enzymes. These findings set a genetical comprehensive knowledge of the host-pathogen relation of D. suzukii challenged with S. carpocapsae which could support further comparative studies with entomopathogenic nematodes.