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Abstract Viral oncoproteins play crucial roles in transforming normal cells into cancer cells, representing a significant factor in the etiology of various cancers. Traditionally, identifying these oncoproteins is both time-consuming and costly. With advancements in computational biology, bioinformatics tools based on machine learning have emerged as effective methods for predicting biological activities. Here, for the first time, we propose an innovative approach that combines Generative Adversarial Networks (GANs) with supervised learning methods to enhance the accuracy and generalizability of viral oncoprotein prediction. Our methodology evaluated multiple machine learning models, including Random Forest, Multilayer Perceptron, Light Gradient Boosting Machine, eXtreme Gradient Boosting, and Support Vector Machine. In ten-fold cross-validation on our training dataset, the GAN-enhanced Random Forest model demonstrated superior performance metrics: 0.976 accuracy, 0.976 F1 score, 0.977 precision, 0.976 sensitivity, and 1.0 AUC. During independent testing, this model achieved 0.982 accuracy, 0.982 F1 score, 0.982 precision, 0.982 sensitivity, and 1.0 AUC. These results establish our new tool, VirOncoTarget, accessible via a web application. We anticipate that VirOncoTarget will be a valuable resource for researchers, enabling rapid and reliable viral oncoprotein prediction and advancing our understanding of their role in cancer biology.

Abstract Viral proteins that evade the host’s innate immune response play a crucial role in pathogenesis, significantly impacting viral infections and potential therapeutic strategies. Identifying these proteins through traditional methods is challenging and time-consuming due to the complexity of virus-host interactions. Leveraging advancements in computational biology, we present VirusHound-II, a novel tool that utilizes machine learning techniques to predict viral proteins evading the innate immune response with high accuracy. We evaluated a comprehensive range of machine learning models, including ensemble methods, neural networks, and support vector machines. Using a dataset of 1337 viral proteins known to evade the innate immune response (VPEINRs) and an equal number of non-VPEINRs, we employed pseudo amino acid composition as the molecular descriptor. Our methodology involved a tenfold cross-validation strategy on 80% of the data for training, followed by testing on an independent dataset comprising the remaining 20%. The random forest model demonstrated superior performance metrics, achieving 0.9290 accuracy, 0.9283 F1 score, 0.9354 precision, and 0.9213 sensitivity in the independent testing phase. These results establish VirusHound-II as an advancement in computational virology, accessible via a user-friendly web application. We anticipate that VirusHound-II will be a crucial resource for researchers, enabling the rapid and reliable prediction of viral proteins evading the innate immune response. This tool has the potential to accelerate the identification of therapeutic targets and enhance our understanding of viral evasion mechanisms, contributing to the development of more effective antiviral strategies and advancing our knowledge of virus-host interactions.

Abstract Direct encounters, in which two or more individuals are physically close to one another, are a topic of increasing interest as more and better movement data become available. Recent progress, including the development of statistical tools for estimating robust measures of changes in animals’ space use over time, facilitates opportunities to link direct encounters between individuals with the long-term consequences of those encounters. Working with movement data for coyotes (Canis latrans) and grizzly bears (Ursus arctos horribilis), we investigate whether close intraspecific encounters were associated with spatial shifts in the animals’ range distributions, as might be expected if one or both of the individuals involved in an encounter were seeking to reduce or avoid conflict over space. We analyze the movement data of a pair of coyotes in detail, identifying how a change in home range overlap resulting from altered movement behavior was apparently a consequence of a close intraspecific encounter. With grizzly bear movement data, we approach the problem as population-level hypothesis tests of the spatial consequences of encounters. We find support for the hypotheses that (1) close intraspecific encounters between bears are, under certain circumstances, associated with subsequent changes in overlap between range distributions and (2) encounters defined at finer spatial scales are followed by greater changes in space use. Our results suggest that animals can undertake long-term, large-scale spatial changes in response to close intraspecific encounters that have the potential for conflict. Overall, we find that analyses of movement data in a pairwise context can (1) identify distances at which individuals’ proximity to one another may alter behavior and (2) facilitate testing of population-level hypotheses concerning the potential for direct encounters to alter individuals’ space use.

Abstract This paper introduces a new latent variable probabilistic framework for representing spectral data of high spatial and spectral dimensionality, such as hyperspectral images. We use a generative Bayesian model to represent the image formation process and provide interpretable and efficient inference and learning methods. Surprisingly, our approach can be implemented with simple tools and does not require extensive training data, detailed pixel-by-pixel labeling, or significant computational resources. Numerous experiments with simulated data and real benchmark scenarios show encouraging image classification performance. These results validate the unique ability of our framework to discriminate complex hyperspectral images, irrespective of the presence of highly discriminative spectral signatures.

Abstract Protein toxins are defense mechanisms and adaptations found in various organisms and microorganisms, and their use in scientific research as therapeutic candidates is gaining relevance due to their effectiveness and specificity against cellular targets. However, discovering these toxins is time-consuming and expensive. In silico tools, particularly those based on machine learning and deep learning, have emerged as valuable resources to address this challenge. Existing tools primarily focus on binary classification, determining whether a protein is a toxin or not, and occasionally identifying specific types of toxins. For the first time, we propose a novel approach capable of classifying protein toxins into 27 distinct categories based on their mode of action within cells. To accomplish this, we assessed multiple machine learning techniques and found that an ensemble model incorporating the Light Gradient Boosting Machine and Quadratic Discriminant Analysis algorithms exhibited the best performance. During the tenfold cross-validation on the training dataset, our model exhibited notable metrics: 0.840 accuracy, 0.827 F1 score, 0.836 precision, 0.840 sensitivity, and 0.989 AUC. In the testing stage, using an independent dataset, the model achieved 0.846 accuracy, 0.838 F1 score, 0.847 precision, 0.849 sensitivity, and 0.991 AUC. These results present a powerful next-generation tool called MultiToxPred 1.0, accessible through a web application. We believe that MultiToxPred 1.0 has the potential to become an indispensable resource for researchers, facilitating the efficient identification of protein toxins. By leveraging this tool, scientists can accelerate their search for these toxins and advance their understanding of their therapeutic potential.

Climate change hazards continue to pose detrimental impacts on coastal cities in the Gulf Cooperation Council (GCC) countries (Saudi Arabia, UAE, Qatar, Bahrain, Kuwait, and Oman) of the Middle East, which undermines their climate resilience. The situation is exacerbated by the rapid urban development in coastal cities in the GCC countries over the past 20 years. This review study examined the climate change hazards that are having negative impacts on the resilience of coastal cities in the GCC countries using a systematic literature review approach. It also explores the urban resilience strategies implemented towards climate change hazards mitigation and adaptation in order to build climate-resilient coastal cities in the GCC countries. A total of 48 peer-reviewed articles were included in the systematic review derived from Scopus, WoS, and Google Scholar, covering the nine coastal cities in the six GCC countries. Most of the studies were focused on the coastal cities of Jeddah (30 %) in Saudi Arabia and Doha (24 %) in Qatar, compared to the other seven coastal cities in the GCC countries. Flooding, rising temperature, sea level rise, dust storms, cyclones, and migration of sand dunes were the six most reported climate change hazards, respectively, posing significant negative impacts on coastal cities and undermining their resilience to current and future climate change impacts. The various urban resilience strategies implemented against climate change hazards were categorised under five resilience dimensions: infrastructure resilience, social resilience, environmental resilience, economic resilience, and governance and policy resilience dimensions. The infrastructure resilience dimension was reported in 50.7 % of the studies, since it is the most implemented, while far less research attention was given to the environmental (14.5 %), government and policy (8.7 %), and economic (2.9 %) resilience dimensions of coastal cities in the GCC countries. The urban resilience strategies for climate mitigation and adaptation were reported to have successfully reduced the vulnerability of coastal cities to climate change hazards over the past decade, by improving their climate resilience. The findings contribute to informing urban planning policy-making focused on coastal environmental management in the coastal cities of the GCC countries that should further enhance the climate resilience of these coastal cities.

Introduction: Sphenoidal sinus surgery and transsphenoidal approaches are commonly used by ENT surgeons and neurosurgeons to treat various pathologies. Radiological evaluation of this area is essential to identify neurovascular structures and their anatomical relationships. Objective: To propose a pre-surgical classification system for the sphenoid sinus, where risk groups are established in relation to neurovascular structures, with an alphanumeric code. Methods: Retrospective study, with simple computed tomography scans of the nose and paranasal sinuses of patients from the otolaryngology and head and neck surgery service of the General Hospital of Mexico. Classified according to the transverse diameter of the sphenoid sinus: I, < 29 mm; II, 29-39.9 mm; and III, > 40 mm. The lateralization of included elements is their light: L, left; R, right; and B, bilateral. Anatomical element involved: N, optic nerve; V, internal carotid artery; and O, another type of element. Results: 200 imaging studies were analyzed. The average age of the population studied was 36.2 years. 49.5% were men (n = 99) and 50.5% (n = 101) women. Grade III presents a higher risk by compromising neurovascular structures in 90.6%. The general lateralization presented was 13.5% to the right side and 13% to the contralateral side. Isolated optic nerve protrusion occurred in 13.5% (n = 11), protruding internal carotid was found in 40% (n = 80), and in 7.5% (n = 15) both elements were found protruding towards the lumen of the sphenoid sinus. Conclusions: The proposed classification facilitates the transmission of information to the surgical team, prior to surgery, with a simple alphanumeric code, increasing the safety of the surgical procedure.

Drought significantly impacts freshwater ecosystems, disrupting all biological levels. In particular, freshwater macroinvertebrates undergo significant changes in taxonomic and functional diversity bioassessments. The effects often synergize with other stressors, such as pollution that drought can exacerbate. Several techniques have been well-developed (traditional) or have the potential (innovative) to address this issue. This review provides a comprehensive description of the impact of drought as a primary stressor on macroinvertebrate diversity. An overview of the research and projections are presented. Three conceptual pillars drive this study: taxonomic-functional responses, simultaneous pressure dynamics, and innovative techniques. Few studies have been conducted on lentic water bodies, arid and semi-arid systems, and on multiple continents. Common research keywords across continents are observed less frequently in experimental than in field studies. Most analyzed studies examine community structure, which is more common in field-based than experimental studies. Agricultural land use effect, urbanization, and invasive species are the stressors most associated with drought. Integrating traditional with advanced/innovative techniques that have hardly been applied makes it challenging to understand ecological responses comprehensively. If innovative techniques are employed to consider the dynamics of multiple stressors and to consistently estimate taxonomic and functional diversity, promising avenues for future research could be uncovered.

Background: Tuberculum sellae meningiomas (TSM) account for 3–10% of intracranial meningiomas. Visual loss is the presenting symptom in up to 80% of cases. Surgical management poses a great challenge due to tumor proximity to neurovascular structures such as the optic nerve and the internal carotid artery (ICA); hence, there is controversy regarding the optimal approach. The aim of this study is to determine differences in visual outcomes between transcranial (TCA) and endoscopic endonasal (EEA) approaches. Methods: A retrospective study including 29 patients with TSM surgically treated by TCA or EEA between 2011 and 2023 in a single referral center was conducted. Pre-and post-operative neuro-ophthalmologic evaluations, focusing on visual acuity and campimetry, were evaluated. Results: Sixteen (55.16%) patients were intervened through a TCA and the remaining 13 (44.84%) via an EEA. The lesions in each group were similar in terms of pre- operative volume (15.12 vs 12.9 cm3, p = 0.497) and neurovascular invasion (optic canal invasion 48.26 vs 41.37%, p = 0.664; ICA 44.81 vs 31.03%, p = 0.797). There were no significant differences in visual outcomes between both approaches; TCA presented an improvement of 5.18 points in visual fields (p = 0.140), whereas EEA had an improvement of 17.39 points in visual acuity (p = 0.114). Conclusion: EEA seems to offer greater improvement in visual acuity than TCA. However, the ideal approach should be individualized; taking into account the tumor’s volume and invasiveness, as well as the patient's visual complaints.

In order to obtain Mg alloys with fine microstructures and high mechanical performances, a novel friction-based processing method, name as “constrained friction processing (CFP)”, was investigated. Via CFP, defect-free Mg-Zn-Ca rods with greatly refined grains and high mechanical properties were produced. Compared to the previous as-cast microstructure, the grain size was reduced from more than 1 mm to around 4 µm within 3 s by a single process cycle. The compressive yield strength was increased by 350% while the ultimate compressive strength by 53%. According to the established material flow behaviors by “tracer material”, the plastic material was transported by shear deformation. From the base material to the rod, the material experienced three stages, i.e. deformation by the tool, upward flow with additional tilt, followed by upward transportation. The microstructural evolution was revealed by “stop-action” technique. The microstructural development at regions adjacent to the rod is mainly controlled by twinning, dynamic recrystallization (DRX) as well as particle stimulated nucleation, while that within the rod is related to DRX combined with grain growth.

Cooperative vehicular systems require that vehicles fuse sensor data and broadcast one-hop safety messages containing their kinematic information to enable vehicular applications based on incident detection. Several congestion control mechanisms have been proposed to mitigate channel congestion resulting from the continuous transmission of safety messages. This paper investigates the effect of message rate adaptation-based congestion control from a road safety perspective by evaluating the feasibility of prominent approaches, such as PULSAR, LIMERIC, reactive ETSI DCC, and SAE J2945/1, to support lane-changing maneuvers on multi-lane highways under varying conditions. Simulation results demonstrate that message size, vehicular density, losses at the physical layer, and observation time significantly influence the lane-changing application’s capability to detect unsafe maneuvers when congestion control is in action. Specific recommendations and guidelines for congestion control are provided to improve decision-making at the application level.

Objetive: The aim of this study was to conduct an exhaustive synthesis to determine which instruments and variables are most appropriate to evaluate foster care programs (foster, kinship, and professional families). This evaluation includes the children, their foster families, their families of origin, professionals, and foster care technicians. Method: The systematic review included randomized, quasi-randomized, longitudinal, and control group studies aimed at evaluating foster care interventions. Results: A total of 86 studies, 138 assessment instruments, 18 constructs, and 73 independent research teams were identified. Conclusions: (1) although the object of the evaluations was the children, the informants were usually the people in charge of their care; therefore, effort should be made to involve the children in a more participatory way; (2) psychosocial functioning, behavior, and parenting are transversal elements in most evaluations, while quality of life and coping are not sufficiently well incorporated; (3) practical instruments (brief and easy to apply and correct) that are widely used and carry scientific guarantees should be prioritized to ensure the comparability and reliability of the conclusions; and (4) progress should be made in the study of evaluation models for all forms of foster care, including foster, extended, and specialized families.

Protamines play a critical role in DNA compaction and stabilization in sperm cells, significantly influencing male fertility and various biotechnological applications. Traditionally, identifying these proteins is a challenging and time-consuming process due to their species-specific variability and complexity. Leveraging advancements in computational biology, we present PROTA, a novel tool that combines machine learning (ML) and deep learning (DL) techniques to predict protamines with high accuracy. For the first time, we integrate Generative Adversarial Networks (GANs) with supervised learning methods to enhance the accuracy and generalizability of protamine prediction. Our methodology evaluated multiple ML models, including Light Gradient-Boosting Machine (LIGHTGBM), Multilayer Perceptron (MLP), Random Forest (RF), eXtreme Gradient Boosting (XGBOOST), k-Nearest Neighbors (KNN), Logistic Regression (LR), Naive Bayes (NB), and Radial Basis Function-Support Vector Machine (RBF-SVM). During ten-fold cross-validation on our training dataset, the MLP model with GAN-augmented data demonstrated superior performance metrics: 0.997 accuracy, 0.997 F1 score, 0.998 precision, 0.997 sensitivity, and 1.0 AUC. In the independent testing phase, this model achieved 0.999 accuracy, 0.999 F1 score, 1.0 precision, 0.999 sensitivity, and 1.0 AUC. These results establish PROTA, accessible via a user-friendly web application. We anticipate that PROTA will be a crucial resource for researchers, enabling the rapid and reliable prediction of protamines, thereby advancing our understanding of their roles in reproductive biology, biotechnology, and medicine.

Mangroves provide numerous ecological, social, and economic benefits that include carbon sequestration, habitat for biodiversity, food, recreation and leisure, income, and coastal resilience. In this regard, mangrove-based carbon market projects (MbCMP), involving mangrove conservation, protection, and restoration, are a nature-based solution (NbS) for climate change mitigation. Despite the proliferation of blue carbon projects, a highly publicized need for local community participation by developers, and existing project implementation standards, local communities are usually left out for several reasons, such as a lack of capacity to engage in business-to-business (B2B) market agreements and communication gaps. Local communities need to be engaged and supported at all stages of the MbCMP development process to enable them to protect their ecological, economic, and social interests as custodians of such a critical ecosystem. In this paper, we provided 15 strategic considerations and recommendations to engage and secure the interests of local communities in the growing mangrove carbon market trade. The 15 considerations are grouped into four recommendation categories: (i) project development and community engagement, (ii) capacity building and educational activities, (iii) transparency in resource allocation and distribution, and (iv) partnerships with local entities and long-term monitoring. We expect our study to increase local participation and community-level ecological, social, and economic benefits from MbCMP by incorporating equitable benefit-sharing mechanisms in a B2B conservation-agreement model.

Se han estudiado cinco casos de hemoglobinuria paroxística nocturna. En cuatro de ellos la enfermedad se manifiesta en su forma clásica y en uno se muestra más como "defecto" que como enfermedad. Todos nuestros pacientes se presentaron como anemia al inicio de su enfermedad, tres con leucopenia y dos con trombocitopenia. Ningún paciente recibió tratamiento a base de hierro, tres pacientes recibieron terapia androgénica siendo sólo uno de ellos beneficiado. Dos pacientes recibieron tratamiento con esteroides sin ningún beneficio.

We present CiftiStorm, an electrophysiological source imaging (ESI) pipeline incorporating recently developed methods to improve forward and inverse solutions. The CiftiStorm pipeline produces Human Connectome Project (HCP) and megconnectome-compliant outputs from dataset inputs with varying degrees of spatial resolution. The input data can range from low-sensor-density electroencephalogram (EEG) or magnetoencephalogram (MEG) recordings without structural magnetic resonance imaging (sMRI) to high-density EEG/MEG recordings with an HCP multimodal sMRI compliant protocol. CiftiStorm introduces a numerical quality control of the lead field and geometrical corrections to the head and source models for forward modeling. For the inverse modeling, we present a Bayesian estimation of the cross-spectrum of sources based on multiple priors. We facilitate ESI in the T1w/FSAverage32k high-resolution space obtained from individual sMRI. We validate this feature by comparing CiftiStorm outputs for EEG and MRI data from the Cuban Human Brain Mapping Project (CHBMP) acquired with technologies a decade before the HCP MEG and MRI standardized dataset.

Predictive coding (PC) is an influential theory in neuroscience, which suggests the existence of a cortical architecture that is constantly generating and updating predictive representations of sensory inputs. Owing to its hierarchical and generative nature, PC has inspired many computational models of perception in the literature. However, the biological plausibility of existing models has not been sufficiently explored due to their use of artificial neurons that approximate neural activity with firing rates in the continuous time domain and propagate signals synchronously. Therefore, we developed a spiking neural network for predictive coding (SNN-PC), in which neurons communicate using event-driven and asynchronous spikes. Adopting the hierarchical structure and Hebbian learning algorithms from previous PC neural network models, SNN-PC introduces two novel features: (1) a fast feedforward sweep from the input to higher areas, which generates a spatially reduced and abstract representation of input (i.e., a neural code for the gist of a scene) and provides a neurobiological alternative to an arbitrary choice of priors; and (2) a separation of positive and negative error-computing neurons, which counters the biological implausibility of a bi-directional error neuron with a very high baseline firing rate. After training with the MNIST handwritten digit dataset, SNN-PC developed hierarchical internal representations and was able to reconstruct samples it had not seen during training. SNN-PC suggests biologically plausible mechanisms by which the brain may perform perceptual inference and learning in an unsupervised manner. In addition, it may be used in neuromorphic applications that can utilize its energy-efficient, event-driven, local learning, and parallel information processing nature.

The genus Swietenia includes two mahogany species, Swietenia macrophylla (King.), commonly known as Honduran mahogany, and Swietenia mahagoni (L.) Jacq, commonly known as Cuban mahogany. There are reports of morphologically intermediate forms between Cuban and Honduran mahogany that have been localized in some Caribbean islands. The main objective of this research is to distinguish morphologically intermediate forms between the parental species S. mahagoni and S. macrophylla based on leaf morphological characters. Phenotypic data from a total of 357 mahogany trees were collected in the province of Sancti Spiritus, Cuba. Rachis length, petiole length, leaflet length, leaflet width, number of leaflets and number of nerves were evaluated. Morphological descriptor analysis revealed significant differences in the morphometric variables of the evaluated leaves, with rachis length, number of leaflets, leaflet length, petiole length, leaflet width, and number of nerves being significantly higher in S. macrophylla than in S. mahagoni. ANOVA reflected the variance between all leaf morphological parameters evaluated between the two pure species with statistically significant difference. Using the function obtained in the first DC of the two species, the individuals in the mixed stands were classified into 71 morphologically intermediate forms, 45 S. macrophylla and 64 S. mahagoni. In the second DC with the two species and the morphologically intermediate forms, Wilks’ partial lambda indicates that the variable "leaflet length" with 0.67 contributed most to the overall discrimination.

Abstract Salinity is a major abiotic stress factor that can significantly impact crop growth, and productivity. In response to salt stress, the plant Salt Overly Sensitive (SOS) signaling pathway regulates the homeostasis of intracellular sodium ion concentration. The SOS1, SOS2, and SOS3 genes play critical roles in the SOS pathway, which belongs to the members of Na+/H+ exchanger (NHX), CBL‐interacting protein kinase (CIPK), and calcineurin B‐like (CBL) gene families, respectively. In this study, we performed genome‐wide identifications and phylogenetic analyses of NHX, CIPK, and CBL genes in six Rosaceae species: Prunus persica, Prunus dulcis, Prunus mume, Prunus armeniaca, Pyrus ussuriensis × Pyrus communis, and Rosa chinensis. NHX, CIPK, and CBL genes of Arabidopsis thaliana were used as controls for phylogenetic analyses. Our analysis revealed the lineage‐specific and adaptive evolutions of Rosaceae genes. Our observations indicated the existence of two primary classes of CIPK genes: those that are intron‐rich and those that are intron‐less. Intron‐rich CIPKs in Rosaceae and Arabidopsis can be traced back to algae CIPKs and CIPKs found in early plants, suggesting that intron‐less CIPKs evolved from their intron‐rich counterparts. This study identified one gene for each member of the SOS signaling pathway in P. persica: PpSOS1, PpSOS2, and PpSOS3. Gene expression analyses indicated that all three genes of P. persica were expressed in roots and leaves. Yeast two‐hybrid‐based protein–protein interaction analyses revealed a direct interaction between PpSOS3 and PpSOS2; and between PpSOS2 and PpSOS1C‐terminus region. Our findings indicate that the SOS signaling pathway is highly conserved in P. persica.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is an inflammatory condition of the nasal and paranasal tissues, characterized by the presence of bilateral nasal polyps. While etiology and pathogenetic mechanisms are heterogeneous and complex, in most patients, disease is mediated predominantly through type 2 inflammatory processes. Clinical management is challenging, and a multidisciplinary approach is preferred. Principal treatment approaches are the use of local/systemic corticosteroids and sinonasal surgery, although outcomes can be unsatisfactory. Recent availability of biological therapies targeting underlying inflammatory processes can offer effective treatment options in uncontrolled disease. Specialist guidelines greatly assist clinical decision-making, although as these are chiefly written from a global/international perspective, they may not wholly accommodate disease patterns and clinical practice at a regional level. An expert panel of specialists from Latin America was convened to develop regional guidance on the management of CRSwNP through a consensus approach. The present article presents the chief observations and recommendations which can provide guidance for clinicians in the Latin American region.

Stainless steels are widely used in industry due to their corrosion resistance properties. Ferritic stainless steels are cheaper than austenitic steels because the former do not contain nickel, an expensive alloying element. However, when ferritic stainless steels are used in manufacturing industries, they undergo microstructure transformations that can result in corrosion. Furthermore, the conventional welding processes that are most commonly used can also cause microstructural changes, such as high grain growth, due to the high thermal inputs applied, and precipitation of deleterious phases. On the other hand, Friction Stir Welding (FSW) avoids such problems due to its intrinsic features and has, therefore, become a viable option for the welding of ferritic stainless steels. This technique imposes high deformation rates, enough heat to soften the material and provides the necessary conditions to promote dynamic recrystallisation and, consequently, prevent the grain growth that occurs in conventional welding. The current investigation is clearly justified due to the vast potential of ferritic stainless steels in the industry using FSW. The main goal of this work is to simulate the FSW process, analyse the possible structural changes in the material and provide the factors that most influence the quality of welds when using this process, such as temperature, strain rate, and changes in the viscosity of the material. The results were able to predict the regions with the smallest grain sizes due to dynamic recrystallisation. Furthermore, the calculated Zener-Hollomon values could be directly linked to the grain size: when the Zener-Hollomon parameter increases the grain size decreases.

Abstract Numerous studies are exploring the use of cell adoptive therapies to treat hematological malignancies as well as solid tumors. However, there are numerous factors that dampen the immune response, including viruses like human immunodeficiency virus. In this study, we leverage human-derived microphysiological models to reverse-engineer the HIV-immune system interaction and evaluate the potential of memory-like natural killer cells for HIV+ head and neck cancer, one of the most common tumors in patients living with human immunodeficiency virus. Here, we evaluate multiple aspects of the memory-like natural killer cell response in human-derived bioengineered environments, including immune cell extravasation, tumor penetration, tumor killing, T cell dependence, virus suppression, and compatibility with retroviral medication. Overall, these results suggest that memory-like natural killer cells are capable of operating without T cell assistance and could simultaneously destroy head and neck cancer cells as well as reduce viral latency.

Mangrove ecotourism is gaining immense popularity in the Gulf Cooperation Council (GCC) countries as a neoliberal conservation tool, and it has contributed significantly to the growth of the tourism sector in the region over the past two decades. However, there is no comprehensive review on the full extent of mangrove ecotourism activities and the contribution to mangrove conservation/restoration and economic growth in the region. A systematic literature review approach was used to examine the evolution of mangrove ecotourism in the GCC countries from 2010 to 2023. A total of 55 articles were retrieved from the Google and Google Scholar search engines, and the Scopus and Web of Science databases were incorporated. We synthesized the results and provided perspectives on the following: (1) the geographical and temporal distribution of studies in relation to mangrove extent, (2) key sites, attractions, and values for mangrove ecotourism activities, (3) the positive and negative impacts of mangrove ecotourism, and (4) existing mangrove conservation and restoration initiatives for the growth of mangrove ecotourism in the GCC countries. The findings underscore the significance of mangrove ecotourism in supporting economic development, protecting coastal ecosystems, and sustaining local livelihoods in the GCC countries. However, this study highlights the crucial need for sustainable coastal environmental management through integrated land use planning and zoning to address the negative impacts of anthropogenic pressures on mangrove ecosystems and ecotourism attractions. The use of remote sensing tools is invaluable in the monitoring of mangrove ecosystems and associated ecotourism impacts for informing evidence-based conservation and restoration management approaches. Thus, harnessing mangrove ecotourism opportunities can help the GCC countries with balancing economic growth, coastal environmental sustainability, and community well-being.

Acetate-producing Saccharomyces cerevisiae var. boulardii strains could exert improved effects on ulcerative colitis, which here, was preclinically evaluated in an acute dextran sodium sulphate induced model of colitis. Nine-week-old female mice were divided into 12 groups, receiving either drinking water or 2.75% dextran sodium sulphate for 7 days, combined with a daily gavage of various treatments with different levels of acetate accumulation: sham control (phosphate buffered saline, no acetate), non-probiotic control (Baker’s yeast, no acetate), probiotic control (Enterol®, transient acetate), and additionally several Saccharomyces cerevisiae var. boulardii strains with respectively no, high, and extra-high acetate accumulation. Disease activity was monitored daily, and feces samples were collected at different timepoints. On day 14, the mice were sacrificed, upon which blood and colonic tissue were collected for analysis. Disease activity in inflamed mice was lower when treated with the high-acetate-producing strain compared to sham and non-probiotic controls. The non-acetate-producing strain showed higher disease activity compared to the acetate-producing strains. Accordingly, higher histologic inflammation was observed in non- or transient-acetate-producing strains compared to the sham control, whereas this increase was not observed for high- and extra-high-acetate-producing strains upon induction of inflammation. These anti-inflammatory findings were confirmed by transcriptomic analysis of differentially expressed genes. Moreover, only the strain with the highest acetate production was superior in maintaining a stable gut microbial alpha-diversity upon inflammation. These findings support new possibilities for acetate-mediated management of inflammation in inflammatory bowel disease by administrating high-acetate-producing Saccharomyces cerevisae var. boulardii strains.

A central challenge in hypothesis testing (HT) lies in determining the optimal balance between Type I (false positive) and Type II (non-detection or false negative) error probabilities. Analyzing these errors’ exponential rate of convergence, known as error exponents, provides crucial insights into system performance. Error exponents offer a lens through which we can understand how operational restrictions, such as resource constraints and impairments in communications, affect the accuracy of distributed inference in networked systems. This survey presents a comprehensive review of key results in HT, from the foundational Stein’s Lemma to recent advancements in distributed HT, all unified through the framework of error exponents. We explore asymptotic and non-asymptotic results, highlighting their implications for designing robust and efficient networked systems, such as event detection through lossy wireless sensor monitoring networks, collective perception-based object detection in vehicular environments, and clock synchronization in distributed environments, among others. We show that understanding the role of error exponents provides a valuable tool for optimizing decision-making and improving the reliability of networked systems.

Saffron, obtained by dehydrating the stigmas of the Crocus sativus flower, is a spice of great importance. In saffron, the flower emerges before leaf formation, thanks to the nutritional reserves of the corm. Early knowledge of metabolite levels such as crocins, picrocrocin, safranal, anthocyanins, or kaempferols in flowers serves as a guide to evaluate the quality of the corm (coloring power, flavor, aroma, or antioxidant capacity, among others). In this study, near-infrared spectroscopy (NIR) was calibrated and validated to determine the main saffron metabolites, both in stigmas and in floral residue. To achieve this, saffron flowers from different locations of the Denomination of Origin (D.O.) “Azafrán de La Mancha” (Castilla-La Mancha, Spain) were analyzed using NIR spectroscopy. Prior to this, samples were analyzed by RP-HPLC-DAD, where the concentration of all cited metabolites was determined. The development of a predictive model through NIR calibration and validation was successful, achieving high R2 values, especially in the case of the sum of crocins and kaempferol-3-O-β-sophoroside. Using these predictive models, it is possible to determine the quality of saffron corm by analyzing the flower.

Background We have previously reported that male mice exposed to maternal separation and early weaning (MSEW), a model of early life stress, show sympathetic activation and increased blood pressure in response to a chronic high‐fat diet. The goal of this study was to investigate the contribution of the renin–angiotensin–aldosterone system to the mechanism by which MSEW increases blood pressure and vasomotor sympathetic tone in obese male mice. Methods and Results Mice were exposed to MSEW during postnatal life. Undisturbed litters served as controls. At weaning, both control and MSEW offspring were placed on a low‐fat diet or a high‐fat diet for 20 weeks. Angiotensin peptides in serum were similar in control and MSEW mice regardless of the diet. However, a high‐fat diet induced a similar increase in angiotensinogen levels in serum, renal cortex, liver, and fat in both control and MSEW mice. No evidence of renin–angiotensin system activation was found in adipose tissue and renal cortex. After chronic treatment with enalapril (2.5 mg/kg per day, drinking water, 7 days), an angiotensin‐converting enzyme inhibitor that does not cross the blood–brain barrier, induced a similar reduction in blood pressure in both groups, while the vasomotor sympathetic tone remained increased in obese MSEW mice. In addition, acute boluses of angiotensin II (1, 10, 50 μg/kg s.c.) exerted a similar pressor response in MSEW and control mice before and after enalapril treatment. Conclusions Overall, elevated blood pressure and vasomotor sympathetic tone remained exacerbated in MSEW mice compared with controls after the peripheral inhibition of angiotensin‐converting enzyme, suggesting a mechanism independent of angiotensin II.

Cellulose nanofibrils (CNFs) are particles with a high aspect ratio. Typically, chemically pre-treated CNFs (containing anionic or cationic charged groups) consist of long fibrils (up to 2 μm) with very low thickness (less than 10 nm). Derived from their high aspect ratio, CNFs form strong hydrogels with high elasticity at low concentrations. Thus, CNF suspensions appear as an interesting rheology modifier to be applied in cosmetics, paints, foods, and as a mineral suspending agent, among other applications. The high viscosity results from the strong 3D fibril network, which is related to the good fibrillation of the material, allowing the nanofibrils to overlap. The overlap concentration (c*) was found to vary from ca. 0.13 to ca. 0.60 wt.% depending on the type and intensity of the pre-treatment applied during the preparation of the CNFs. The results confirm the higher tendency for the fibres treated with (3-chloro-2-hydroxypropyl) trimethylammonium chloride (CHPTAC) and 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO) to form a 3D network, resulting in the lowest c*. For the TEMPO-oxidised CNF suspensions, it was also found that aggregation is improved at acidic pH conditions due to lower charge repulsion among fibrils, leading to an increase in the suspension viscosity as well as higher apparent yield stresses. TEMPO CNF suspensions with a low content of carboxylic groups tend to precipitate at moderately acidic pH values.

Polymers generally form incompatible mixtures that make the process of recycling difficult, especially the mechanical recycling of mixed plastic waste. One of the most commonly used films in the packaging industry is multilayer films, mainly composed of polyethylene (PE) and polyamide (PA). Recycling these materials with such different molecular structures requires the use of compatibilizers to minimize phase separation and obtain more useful recycled materials. In this work, commercial polyisoprene–graft–maleic anhydride (PI-g-MA) was tested as a compatibilizer for a blend of PE and PA derived from the mechanical recycling of PE/PA multilayer films. Different amounts of PI-g-MA were tested, and the films made with 1.5% PI-g-MA showed the best results in terms of mechanical properties and dart impact. The films were also characterized thermally via thermogravimetric analysis (TG) and differential scanning calorimetry (DSC), using Fourier-transform infrared spectroscopy (FTIR), and morphologically using a scanning electron microscope (SEM). Other parameters, such as tearing and perforation, were analyzed.

Mangrove forests in the Gulf Cooperation Council (GCC) countries are facing multiple threats from natural and anthropogenic-driven land use change stressors, contributing to altered ecosystem conditions. Remote sensing tools can be used to monitor mangroves, measure mangrove forest-and-tree-level attributes and vegetation indices at different spatial and temporal scales that allow a detailed and comprehensive understanding of these important ecosystems. Using a systematic literature approach, we reviewed 58 remote sensing-based mangrove assessment articles published from 2010 through 2022. The main objectives of the study were to examine the extent of mangrove distribution and cover, and the remotely sensed data sources used to assess mangrove forest/tree attributes. The key importance of and threats to mangroves that were specific to the region were also examined. Mangrove distribution and cover were mainly estimated from satellite images (75.2%), using NDVI (Normalized Difference Vegetation Index) derived from Landsat (73.3%), IKONOS (15%), Sentinel (11.7%), WorldView (10%), QuickBird (8.3%), SPOT-5 (6.7%), MODIS (5%) and others (5%) such as PlanetScope. Remotely sensed data from aerial photographs/images (6.7%), LiDAR (Light Detection and Ranging) (5%) and UAV (Unmanned Aerial Vehicles)/Drones (3.3%) were the least used. Mangrove cover decreased in Saudi Arabia, Oman, Bahrain, and Kuwait between 1996 and 2020. However, mangrove cover increased appreciably in Qatar and remained relatively stable for the United Arab Emirates (UAE) over the same period, which was attributed to government conservation initiatives toward expanding mangrove afforestation and restoration through direct seeding and seedling planting. The reported country-level mangrove distribution and cover change results varied between studies due to the lack of a standardized methodology, differences in satellite imagery resolution and classification approaches used. There is a need for UAV-LiDAR ground truthing to validate country-and-local-level satellite data. Urban development-driven coastal land reclamation and pollution, climate change-driven temperature and sea level rise, drought and hypersalinity from extreme evaporation are serious threats to mangrove ecosystems. Thus, we encourage the prioritization of mangrove conservation and restoration schemes to support the achievement of related UN Sustainable Development Goals (13 climate action, 14 life below water, and 15 life on land) in the GCC countries.

Background The phase 3 QUEST (NCT02414854) and TRAVERSE (NCT02134028) studies demonstrated the efficacy of dupilumab 200/300 mg versus placebo every 2 weeks for 52 weeks (QUEST) and dupilumab 300 mg up to an additional 96 weeks (TRAVERSE) in patients ≥12 years of age with uncontrolled, moderate-to-severe asthma. Overall, safety was consistent with the known dupilumab safety profile. This post hoc analysis assessed long-term dupilumab efficacy for up to 3 years by exacerbation history. Patients and methods Unadjusted annualised severe exacerbation rates (AER) and change from parent study baseline (PSBL) in pre-bronchodilator forced expiratory volume in 1 s (FEV1) and 5-item Asthma Control Questionnaire (ACQ-5) score were assessed in patients with PSBL eosinophils ≥150 cells·µL−1 or fractional exhaled nitric oxide ≥20 ppb and 1 (n=624), 2 (n=344), or ≥3 (n=311) exacerbations in the year before enrolment in QUEST. Results In all three groups, dupilumab treatment progressively reduced AER range to 0.17–0.30 during TRAVERSE (Weeks 48–96), increased pre-bronchodilator FEV1 range by 0.28–0.49 L by Week 96 and improved asthma control (reduced ACQ-5 score range by 1.51–2.03 by Week 48). For patients who first received dupilumab upon TRAVERSE enrolment, AER decreased, and lung function and asthma control improved rapidly, as was observed upon initiation of dupilumab in QUEST. Dupilumab was efficacious regardless of exacerbation history. Conclusion For patients with uncontrolled, moderate-to-severe asthma with elevation of at least one type 2 biomarker, dupilumab treatment provides sustained, long-term reduction of exacerbation rates and improvements in lung function and asthma control irrespective of exacerbation history.

La infección de vías urinarias se encuentra dentro de las complicaciones infecciosas más frecuentes para el grupo etario mayor de 65 años. Esto tiene gran relevancia, ya que durante los últimos años se ha presentado un crecimiento significativo de este grupo poblacional, en comparación con los demás grupos. Se tiene conocimiento de que el principal mecanismo patológico es por vía ascendente, exacerbada por otros factores inherentes a los ancianos, como pH alcalino, reducción del flujo urinario e inmunosenescencia. Los agentes etiológicos más relevantes son las bacterias pertenecientes a la familia de gramnegativos, principalmente Escherichia coli. Debido a su alta frecuencia y el limitado conocimiento acerca de esta patología en la persona mayor, representa un reto diagnóstico para todo el personal de urgencias debido a su alta morbilidad y aparición junto a diferentes comorbilidades que impiden un adecuado enfoque clínico. Por tal motivo continúa siendo necesario un abordaje integral desde el triaje del servicio de urgencias de forma temprana e individualizada.

Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health.

The ventral visual processing hierarchy of the cortex needs to fulfill at least two key functions: perceived objects must be mapped to high-level representations invariantly of the precise viewing conditions, and a generative model must be learned that allows, for instance, to fill in occluded information guided by visual experience. Here, we show how a multilayered predictive coding network can learn to recognize objects from the bottom up and to generate specific representations via a top-down pathway through a single learning rule: the local minimization of prediction errors. Trained on sequences of continuously transformed objects, neurons in the highest network area become tuned to object identity invariant of precise position, comparable to inferotemporal neurons in macaques. Drawing on this, the dynamic properties of invariant object representations reproduce experimentally observed hierarchies of timescales from low to high levels of the ventral processing stream. The predicted faster decorrelation of error-neuron activity compared to representation neurons is of relevance for the experimental search for neural correlates of prediction errors. Lastly, the generative capacity of the network is confirmed by reconstructing specific object images, robust to partial occlusion of the inputs. By learning invariance from temporal continuity within a generative model, the approach generalizes the predictive coding framework to dynamic inputs in a more biologically plausible way than self-supervised networks with non-local error-backpropagation. This was achieved simply by shifting the training paradigm to dynamic inputs, with little change in architecture and learning rule from static input-reconstructing Hebbian predictive coding networks.

Successful restoration measures need a good understanding of how the composition, structure, and functioning of ecosystems change with degradation and what the best indicators of these changes are. To answer these questions, we worked on four ecosystem types in the Mediterranean Andes mountains in central Chile (from sclerophyllous forest to Andean shrublands), which represent an elevational gradient from 700 to 3,250 m. We sampled three plots on each of the three degradation levels (low, medium, and high) for each ecosystem at increasing distances from goat corrals. We measured 35 indicators that describe vegetation (14), soil (15), and ecosystem processes (6) for one growing season. Degradation caused a decrease in shrub cover, shrub productivity, the Normalized Community Structure Integrity Index (CSIIn), litter depth, total soil nitrogen and C/N ratio, and an increase in clay content. Plant species indicating low degradation were consistently native woody species. When comparing ecosystems (i.e., at different elevations) against the type of variable, process-based indicators showed more statistically significant differences. Based on their consistency across ecosystems and ease of measurement, we recommend using shrub cover and litter depth as indicators of degradation. Finally, we concluded that ecosystems are highly degraded when vegetation- and process-based indicators change ∼ 60% or when soil indicators change ∼ 25%. These results could also be used to set goals for restoration projects in these mountain ecosystems.

Several studies have evidenced that children in out-of-home care (OOHC), including foster family care and residential care, reveal high levels of mental health disorders (ranging from 40% to 88%). This study examines the outcomes in mental health reported by key residential workers in a group of children and youth (N = 492) between 8-17 years old who were in residential child care (RCC) in Spain. The research also aims to explore the relationship between mental health outcomes and the provision of mental health services (i.e., receiving any mental health treatment) as well as the influence of child, family, and placement factors. The design of this study includes two measures: a baseline (T1) and a follow-up two years later (T2). The results indicated that 29.9% of young people enjoyed sustained mental health; 26% meaningful improvement in their mental health; 23.5% meaningful deterioration; and the remaining 20.5% showed no meaningful change. One of the main findings was that receiving mental health treatment had a significant impact on mental health outcomes. It is crucial to establish protocols and systematic detection tools to assess mental health and ensure detection and referral to proper treatment.

Refill Friction Stir Spot Welding (refill FSSW) is a method for joining similar and dissimilar lightweight metallic materials or thermoplastic polymers. The technique produces welds that feature suitable mechanical properties with advantages such as the possibility of industrial scalability and automation. Still, some challenges need to be overcome in order to increase the adoption of this technique in industry. Tool wear is a key issue for friction-based processes, since it impacts the process costs and quality of the welds. In this study, a total of 2350 welds of AA2198-T8 sheets were performed and the effect of wear on probe and shoulder was investigated. While the probe did not suffer any considerable wear after this number of welds, the shoulder underwent wear in different areas, with distinct wear mechanisms. Adhesive wear and plastic deformation were determined as the primary damage mechanisms affecting different areas of the shoulder. Mechanical testing of selected welds has shown a trend towards reduction in the lap shear strength (LSS) as a function of tool wear. Macrostructural analysis of welds' geometrical features shows that profile changes at the shoulder due to wear led to a trend of reduction in stirred zone area and, consequently, joints’ LSS. Modifications in the worn shoulder profile were suggested as possible causes for changes in hook height, which was identified as a further determining factor to the observed reduction in LSS. Still, all tested welds surpassed the minimum lap shear strength standard requirements for aeronautical applications.

Time-Of-Flight (TOF) computations are needed in all ultrasound imaging methods. In Non Destructive Testing (NDT), where ultrasound inspections are frequently done using a coupling medium between the transducer and the test piece, wave refraction complicates TOF computations and iterative methods are needed, which hinders frame rate. For fast imaging simple approximation methods are needed. In this work we propose a TOF fast approximation method for the particular case of sub-surface imaging.

Background: Intravascular venous (VUC) or arterial (AUC) umbilical catheter placement is the most frequent invasive procedure in the neonatal intensive care unit (NICU). Either Wright’s or Shukla’s formula is used to introduce the catheters. However, Shukla’s formula is associated with incorrect insertion, especially for newborns < 1500 g. This study aimed to determine by chest X-ray if Wright’s formula is better than Shukla’s formula for the correct placement of umbilical catheters in newborns ≤ 1500 g. Methods: We included patients admitted to the NICU of a secondary-level hospital between 2021- 2022 who received VUC or AUC through the Wright or Shukla formulas. Results: A total of 129 newborns were included: 78 with VUC and 51 with AUC. In VUC, 50% with Wright and 36.8% with Shukla formulas had the correct location, (p = 0.24). In AUC, 56.6 % with Wright and 52.4% with Shukla formulas were placed correctly placed, (p = 0.76). VUC with weight < 1000 g were correctly placed in 36.4% with Wright and 33.3% with Shukla formulas (p = 0.58). VUC in newborns > 1000 g were correctly placed in 66.6% with Wright and 38.4% with Shukla formulas (p = 0.065). AUC in newborns < 1000 g were correctly placed in 45% using Wright and 42.9% Shukla formulas (p = 0.63). AUC in newborns > 1000 g were correctly placed in 80% using Wright and 57.1% Shukla formulas (p = 0.23). Conclusions: We found 13% more correctly placed VUC using Wright’s formula. Moreover, Wright’s formula was 29% above Shukla’s VUC placement in neonates > 1000 g, although there was no significant difference due to the sample size.

Heterologous expression of L-asparaginase (L-ASNase) has become an important area of research due to its clinical and food industry applications. This review provides a comprehensive overview of the molecular and metabolic strategies that can be used to optimize the expression of L-ASNase in heterologous systems. This article describes various approaches that have been employed to increase enzyme production, including the use of molecular tools, strain engineering, and in silico optimization. The review article highlights the critical role that rational design plays in achieving successful heterologous expression and underscores the challenges of large-scale production of L-ASNase, such as inadequate protein folding and the metabolic burden on host cells. Improved gene expression is shown to be achievable through the optimization of codon usage, synthetic promoters, transcription and translation regulation, and host strain improvement, among others. Additionally, this review provides a deep understanding of the enzymatic properties of L-ASNase and how this knowledge has been employed to enhance its properties and production. Finally, future trends in L-ASNase production, including the integration of CRISPR and machine learning tools are discussed. This work serves as a valuable resource for researchers looking to design effective heterologous expression systems for L-ASNase production as well as for enzymes production in general.

Background: Tarlov cysts (TC), also known as perineural cysts are meningeal dilations of the posterior nerve root sheath that typically affect sacral nerve roots. TC are usually asymptomatic and found incidentally. We present the case of a patient with an enlarging sacral TC causing pain from spinopelvic instability secondary to extensive bone erosion. Such illustrative case is intended to increase awareness of the potential need for complex spinopelvic reconstruction in atypical instances of large TC. Case Description: A 29-year-old female presented to clinic reporting progressive bilateral sacroiliac joint pain that was essentially mechanical in nature. The patient had a normal neurological exam except for a known left drop foot with numbness in the left sural nerve distribution, both attributed to a previously resected peripheral nerve sheath tumor. Magnetic resonance imaging revealed a large multilobulated lesion with imaging characteristics consistent with TC adjacent to the left side of the sacrum, extending outward from the left S1 and S2 neural foramina and measuring 6.7 × 3.7 cm in the axial plane and and 5.6 cm in the sagittal plane. Six weeks of conservative management consisting of physical therapy and pain management was unsuccessful, and the patient reported worsening pain. Surgical reconstruction consisting of L5–S1 transforaminal lumbar interbody fusion, L4 to pelvis navigation-guided instrumentation and posterolateral fusion, and bilateral sacroiliac joint fusion was successfully performed. Outcomes: At 12 weeks follow-up appointment after surgery, the patient reported resolution of sacroiliac mechanical pain. Conclusions: Sacral TC are asymptomatic in their vast majority of cases but may occasionally cause neurological deficits secondary to mass effect. Rarely, however, giant TC can also lead to significant bone erosion or the sacrum with secondary spinopelvic instability. In this brief report, we describe a giant TC generating significant spinopelvic instability, which was successfully treated with complex spinopelvic reconstruction, leading to complete resolution of the reported axial mechanical pain.

In recent years, legged quadruped robots have proved to be a valuable support to humans in dealing with search and rescue operations. These robots can move with great ability in complex terrains, unstructured environments or regions with many obstacles. This work employs the quadruped robot A1 Rescue Tasks UPM Robot (ARTU-R) by Unitree, equipped with an RGB-D camera and a lidar, to perform victim searches in post-disaster scenarios. Exploration is done not by following a pre-planned path (as common methods) but by prioritising the areas most likely to harbour victims. To accomplish that task, both indirect search and next best view techniques have been used. When ARTU-R gets inside an unstructured and unknown environment, it selects the next exploration point from a series of candidates. This operation is performed by comparing, for each candidate, the distance to reach it, the unexplored space around it and the probability of a victim being in its vicinity. This probability value is obtained using a Random Forest, which processes the information provided by a convolutional neural network. Unlike other AI techniques, random forests are not black box models; humans can understand their decision-making processes. The system, once integrated, achieves speeds comparable to other state-of-the-art algorithms in terms of exploration, but concerning victim detection, the tests show that the resulting smart exploration generates logical paths—from a human point of view—and that ARTU-R tends to move first to the regions where victims are present.

Quantum key distribution (QKD) for information-theoretic secure distribution of cryptographic keys is one of the best known applications that will be enabled by the Quantum Internet. Here, the authors deploy the protocol of measurement-device-independent quantum key distribution into a realistic network environment, testing its field performances and showing the co-existing of this QKD protocol and the classical network infrastructure.

Abstract A promising new treatment approach for major depressive disorder (MDD) targets the microbiota-gut-brain (MGB) axis, which is linked to physiological and behavioral functions affected in MDD. This is the first randomized controlled trial to determine whether short-term, high-dose probiotic supplementation reduces depressive symptoms along with gut microbial and neural changes in depressed patients. Patients with current depressive episodes took either a multi-strain probiotic supplement or placebo over 31 days additionally to treatment-as-usual. Assessments took place before, immediately after and again four weeks after the intervention. The Hamilton Depression Rating Sale (HAM-D) was assessed as primary outcome. Quantitative microbiome profiling and neuroimaging was used to detect changes along the MGB axis. In the sample that completed the intervention (probiotics N = 21, placebo N = 26), HAM-D scores decreased over time and interactions between time and group indicated a stronger decrease in the probiotics relative to the placebo group. Probiotics maintained microbial diversity and increased the abundance of the genus Lactobacillus, indicating the effectivity of the probiotics to increase specific taxa. The increase of the Lactobacillus was associated with decreased depressive symptoms in the probiotics group. Finally, putamen activation in response to neutral faces was significantly decreased after the probiotic intervention. Our data imply that an add-on probiotic treatment ameliorates depressive symptoms (HAM-D) along with changes in the gut microbiota and brain, which highlights the role of the MGB axis in MDD and emphasizes the potential of microbiota-related treatment approaches as accessible, pragmatic, and non-stigmatizing therapies in MDD. Trial Registration: www.clinicaltrials.gov , identifier: NCT02957591.

Introduction: Endothelial cells (ECs), being located at the interface between flowing blood and vessel wall, maintain cardiovascular homeostasis by virtue of their ability to integrate chemical and physical cues through a spatio-temporally coordinated increase in their intracellular Ca2+ concentration ([Ca2+]i). Endothelial heterogeneity suggests the existence of spatially distributed functional clusters of ECs that display different patterns of intracellular Ca2+ response to extracellular inputs. Characterizing the overall Ca2+ activity of the endothelial monolayer in situ requires the meticulous analysis of hundreds of ECs. This complex analysis consists in detecting and quantifying the true Ca2+ events associated to extracellular stimulation and classifying their intracellular Ca2+ profiles (ICPs). The injury assay technique allows exploring the Ca2+-dependent molecular mechanisms involved in angiogenesis and endothelial regeneration. However, there are true Ca2+ events of nearly undetectable magnitude that are almost comparable with inherent instrumental noise. Moreover, undesirable artifacts added to the signal by mechanical injury stimulation complicate the analysis of intracellular Ca2+ activity. In general, the study of ICPs lacks uniform criteria and reliable approaches for assessing these highly heterogeneous spatial and temporal events.Methods: Herein, we present an approach to classify ICPs that consists in three stages: 1) identification of Ca2+ candidate events through thresholding of a feature termed left-prominence; 2) identification of non-true events, known as artifacts; and 3) ICP classification based upon event temporal location.Results: The performance assessment of true-events identification showed competitive sensitivity = [0.9995, 0.9831], specificity = [0.9946, 0.7818] and accuracy = [0.9978, 0.9579] improvements of 2x and 14x, respectively, compared with other methods. The ICP classifier enhanced by artifact detection showed 0.9252 average accuracy with the ground-truth sets provided for validation.Discussion: Results indicate that our approach ensures sturdiness to experimental protocol maneuvers, besides it is effective, simple, and configurable for different studies that use unidimensional time dependent signals as data. Furthermore, our approach would also be effective to analyze the ICPs generated by other cell types, other dyes, chemical stimulation or even signals recorded at higher frequency.

The stepwise treatment approach recommended by the Global Initiative for Asthma (GINA) includes systemic corticosteroids (SCS) suggested as a final step if asthma is severe and/or difficult to treat. Yet, despite the effectiveness of SCS, they are also associated with potentially irreversible adverse outcomes such as type 2 diabetes, adrenal suppression, and cardiovascular disease. Based on recent data indicating that the risk of developing these conditions can increase after as few as 4 short-term (burst) courses of SCS, even patients with mild asthma who receive SCS occasionally for exacerbations are also at risk of these events. As a result, recent updates by GINA and the Latin American Thoracic Society recommend decreasing SCS use by optimizing administration of non-SCS therapies and/or increasing the use of alternatives, such as biologic agents. Recent and ongoing studies characterizing treatment patterns among patients with asthma have revealed alarming trends suggesting the widespread overuse of SCS around the world. In Latin America, asthma prevalence is approximately 17%, and data suggest that the majority of patients have uncontrolled disease. In this review, we summarize currently available data on asthma treatment patterns in Latin America, which indicate that SCS are prescribed to 20–40% of patients with asthma considered to be well controlled and over 50% of patients with uncontrolled disease. We also offer potential strategies to help reduce SCS use for asthma in everyday clinical practice.

Background: Cobia (Rachycentron canadum) is a species of fish with high commercial potential particularly due to fast growth rates. The evidence of sexual size dimorphism favoring females indicate potential benefits in having a monosex culture. However, the involvement of genetic factors responsible for sexual development and gonadal maintenance that produces phenotypic sex in cobia is largely unknown.Methods: In the present study, we performed transcriptome sequencing of cobia to identify sex-biased significantly differentially expressed genes (DEGs) in testes and ovaries. The reliability of the gonad transcriptome data was validated by qPCR analysis of eight selected significantly differential expressed sex-related candidate genes.Results: This comparative gonad transcriptomic analysis revealed that 7,120 and 4,628 DEGs are up-regulated in testes or ovaries, respectively. Further functional annotation analyses identified 76 important candidate genes involved in sex determination cascades or sex differentiation, including 42 known testis-biased DEGs (dmrt1, amh and sox9 etc.), and 34 known ovary-biased DEGs (foxl2, sox3 and cyp19a etc.). Moreover, eleven significantly enriched pathways functionally related to sex determination and sex differentiation were identified, including Wnt signaling pathway, oocyte meiosis, the TGF-beta signaling pathway and MAPK signaling pathway.Conclusion: This work represents the first comparative gonad transcriptome study in cobia. The putative sex-associated DEGs and pathways provide an important molecular basis for further investigation of cobia’s sex determination, gonadal development as well as potential control breeding of monosex female populations for a possible aquaculture setting.

Keeping cover crops to reduce nitrogen leaching often conflicts with timing tillage operations before the soil becomes un-trafficable during winter, while leaving cover crops in the field until spring raises concerns over pre-emptive competition with the following crop. Therefore, farmers may resort to tilling their fields in autumn after letting cover crops remain in the fields for only a short period of time. We explore the effects of this practice in a laboratory lysimeter setting by analyzing the leaching of nitrate from intact topsoil cores. Cores were extracted from no-till (NT) plots and plots tilled in autumn (AuT), in areas kept bare (B) and with volunteer winter rye plant cover (V) after harvest. Nitrate breakthrough curves show that V significantly reduced N leaching by 61% relative to B in NT, but did not have a significant effect in AuT. Dissection of leached cores and undisturbed reference cores indicated a significant removal of mineral N from the soil during the lysimeter experiment for all treatments except V in NT. This indicates that volunteer cover removed a crucial amount of leachable N and suggests that tillage counteracted the effect of V in AuT, likely due to a combination of reduced uptake and re-mineralization of N in cover crop residue.

(1) Background: Nanocellulose is an innovative engineered nanomaterial with an enormous potential for use in a wide array of industrial and biomedical applications and with fast growing economic value. The expanding production of nanocellulose is leading to an increased human exposure, raising concerns about their potential health effects. This study was aimed at assessing the potential toxic and genotoxic effects of different nanocelluloses in two mammalian cell lines; (2) Methods: Two micro/nanocelluloses, produced with a TEMPO oxidation pre-treatment (CNFs) and an enzymatic pre-treatment (CMFs), and cellulose nanocrystals (CNCs) were tested in osteoblastic-like human cells (MG-63) and Chinese hamster lung fibroblasts (V79) using the MTT and clonogenic assays to analyse cytotoxicity, and the micronucleus assay to test genotoxicity; (3) Results: cytotoxicity was observed by the clonogenic assay in V79 cells, particularly for CNCs, but not by the MTT assay; CNF induced micronuclei in both cell lines and nucleoplasmic bridges in MG-63 cells; CMF and CNC induced micronuclei and nucleoplasmic bridges in MG-63 cells, but not in V79 cells; (4) Conclusions: All nanocelluloses revealed cytotoxicity and genotoxicity, although at different concentrations, that may be related to their physicochemical differences and availability for cell uptake, and to differences in the DNA damage response of the cell model.