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Abstract We studied how the South American sea lion (SASL, Otaria flavescens) interacts with the operation of an artisanal fishery of Chinook salmon, a non-native species in Chile, using a combination of biological and social approaches, including a valuation by fishers about this interaction. During austral summer of 2019, an observer onboard artisanal fishing boats characterized the attack behavior of SASLs to gillnet-captured Chinook salmon during 33 hauls and analyzed which factors may affect the intensity of attacks. To analyze the relationship between fishers and SASLs, a Likert scale about the perception and views about nature was applied. A total of 23 interviews—including 35 open and 16 closed questions—with fishers were conducted to describe how they perceived the interactions with SASLs. Interactions with SASLs were recorded in 35% of the fishing events and varied depending on both operational factors, such as the number of boats, as well as environmental factors, such as moon’s luminosity. Even though SASL interactions resulted in seven fish (~ 70 kg) damaged of a total catch of 2815 kg (2.5%) during the survey, boats with a damaged catch by SASL lost up to 11% of their revenue. This is consistent with 87% of the interviewed fishers who considered that the conflict with the SASL negatively impacts their activity and results in economic losses. A negative perception towards SASLs likely results from personal experience and revenue loss, even though impacts of SASL interactions at the scale of the entire fishery may be less important. While older fishers with less formal education have a productivist and instrumental focus, younger fishers with a more sustainable and conservationist view of fishing offer an opportunity to lead an improved local understanding of the relationship between salmon, SASLs, and humans.

Adverse pregnancy outcomes (APOs) affect a large proportion of pregnancies and represent an important cause of morbidity and mortality worldwide. Yet the pathophysiology of APOs is poorly understood, limiting our ability to prevent and treat these conditions. To search for genetic markers of maternal risk for four APOs, we performed multi-ancestry genome-wide association studies (GWAS) for pregnancy loss, gestational length, gestational diabetes, and preeclampsia. We clustered participants by their genetic ancestry and focused our analyses on three sub-cohorts with the largest sample sizes: European, African, and Admixed American. Association tests were carried out separately for each sub-cohort and then meta-analyzed together. Two novel loci were significantly associated with an increased risk of pregnancy loss: a cluster of SNPs located downstream of the TRMU gene (top SNP: rs142795512), and the SNP rs62021480 near RGMA. In the GWAS of gestational length we identified two new variants, rs2550487 and rs58548906 near WFDC1 and AC005052.1, respectively. Lastly, three new loci were significantly associated with gestational diabetes (top SNPs: rs72956265, rs10890563, rs79596863), located on or near ZBTB20, GUCY1A2, and RPL7P20, respectively. Fourteen loci previously correlated with preterm birth, gestational diabetes, and preeclampsia were found to be associated with these outcomes as well.

Abstract In this work, we use mass quadrupole spectroscopy to analyze the ion energy distribution function for C+ ions from different gas composition discharges (20, 40, 60, 80, and 90% Ne) + Ar in a plasma sputtering process. Carbon films were obtained for each gas composition discharge. The carbon bonding structure of films was analyzed by Raman spectroscopy using deconvolution fitting of the G and D Raman peaks. The C-sp3 content was correlated with the electrical and tribological properties of the carbon films. Our results further corroborate the enhancement of carbon ionization in HiPIMS processes by adding neon in conventional argon gas during the deposition process. Furthermore, we found that excessive levels of carbon ionization were detrimental in the formation of C-sp3 decreasing the resistivity, and indicating the decrement of the elastic modulus of the samples. In addition, the use of neon in the gas working mixture increased the deposition rate significantly compared to argon-only processes from 1.7 to 3.22 nm/min for the highest deposition rate cases. Tribology showed that an intermediate C-sp3 content in the carbon films developed desirable tribological behaviors with lower friction coefficients and wear rates, revealing that higher values of C-sp3 content are not necessarily for robust solid lubricious and wear resistance.

Abstract Power electronic converters are widely implemented in many types of power applications such as microgrids. Power converters can make a physical connection between the power resources and the power application. To control a power converter, required data such as the voltage and the current of that should be measured to be used in a control application. Therefore, a communication-based structure including sensors and communication links can be used to measure the desired data and transmit that to the controllers. So, a power converter-based system can be considered as a type of cyber-physical system, and it can be vulnerable to cyber-attacks. Then, it can strongly be recommended to use a strategy for a power converter-based system to monitor the system and identify the existence of cyber-attack in the system. In this study, artificial intelligence (AI) is deployed to calculate the value of the false data (i.e., constant false data, and time-varying false data) and detect false data injection cyber-attacks on power converters. Besides, to have a precise technical evaluation of the proposed methodology, that is evaluated under other issues, i.e., noise, and communication link delay. In the case of noise, the proposed strategy is examined under noises with different signal-to-noise ratios . Further, for the case of the communication delay, the system is examined under both symmetrical (i.e., same communication delay on all inputs) and unsymmetrical communication delays (i.e., different communication delay/delays on the inputs). In this work, artificial neural networks are implemented as the AI-based application, and two types of the networks, i.e., feedforward (as a basic type) and long short-term memory (LSTM)-based network as a more complex network are tested. Finally, three important AI-based techniques (regression, classification, and clustering) are examined. Based on the obtained results, this work can properly identify and calculate the false data in the system.

Abstract Prematurity has been related to altered brain structure and cognition, and so our aim was to describe them in the absence of major structural brain injury following low-risk preterm birth during adolescence and young adulthood. The sample consisted of 250 participants, 132 of whom were low-risk preterm (30–36 weeks’ gestational age) and 118 were full-term individuals (37–42 weeks’ gestational age), aged between 16 and 38 years old. All participants underwent an extensive neuropsychological assessment. T1- and diffusion-weighted MRI images of 33 low-risk preterm and 31 full-term young adults (20–32 years old) were analyzed. No differences were found in terms of general cognitive functioning score or current socioeconomic status; however, the low-risk preterm group obtained lower scores in phonetic and semantic fluencies, and theory of mind. Significant reductions were identified in the thalamus volume as well as thicker cortex in the inferior temporal gyrus in the low-risk preterm group. Low-risk preterm young adults evidenced greater regional AD and MD compared to the full-term sample; while low-risk preterm group showed lower mean NDI and ODI (FWE-corrected, p

Abstract Tick-borne rickettsioses, caused by Gram-negative bacteria of the Rickettsia genus, pose a growing global threat, with various arthropod vectors contributing to their transmission. Understanding the complex interactions within tick microbiota, including the role of Rickettsia species, is crucial for elucidating the dynamics of rickettsial diseases. Here, we investigate the taxonomic profiles and co-occurrence networks of Rickettsia in Rh. sanguineus sensus lato (s.l.) and Rh. turanicus ticks, revealing significant differences in community composition and local connectivity of Rickettsia species. While the microbiota of both tick species share common taxa, distinct differences in relative abundance and network topology suggest unique ecological niches. Moreover, robustness analysis demonstrates varying resilience to perturbations, indicating different strategies for network organization. Our findings also highlight metabolic differences between tick species, suggesting potential implications for Rickettsia interactions. Overall, this study provides insights into the intricate microbial landscape within ticks, shedding light on the functional redundancy and metabolic pathways associated with Rickettsia, thus advancing our understanding of tick-borne diseases.

Abstract Spoken lessons (lectures) are commonly used in schools as a medium for conveying educational content. In adolescence, experience-expectant maturation of language and cognitive systems supports learning; however, little is known about whether or how learners' language experiences interact with this integration process during learning. We examined functional connectivity using fMRI in 38 Spanish–English bilingual (L1-Spanish) and English monolingual (L1-English) adolescents during a naturalistic science video lesson in English. Seed analyses including the left inferior frontal gyrus (pars opercularis) and posterior middle temporal gyrus showed that L1-Spanish adolescents, when learning in their second language (L2), displayed widespread bilateral functional connectivity throughout the cortex while L1-English adolescents displayed mostly left-lateralized connectivity with core language regions over the course of the science lesson. Furthermore, we identified functional seed connectivity associated with better learning outcomes for adolescents with diverse language backgrounds. Importantly, functional connectivity patterns in L1-Spanish adolescents while learning in English also correlate with their Spanish cloze reading. Findings suggest that functional networks associated with higher-order language processing and cognitive control are differentially engaged for L1 vs. L2 speakers while learning new information through spoken language.

Abstract Over 125 million years of ant-plant interactions have culminated in one of the most intriguing evolutionary outcomes in life history. The myrmecophyte Duroia hirsuta (Rubiaceae) is known for its mutualistic association with the ant Myrmelachista schumanni and several other species, mainly Azteca, in the north-western Amazon. While both ants provide indirect defences to plants, only M. schumanni nests in plant domatia and has the unique behaviour of clearing the surroundings of its host tree from heterospecific plants, potentially increasing resource availability to its host. Using a 12-year survey, we asked how the continuous presence of either only M. schumanni or only Azteca spp. benefits the growth and defence traits of host trees. We found that the continuous presence of M. schumanni improved relative growth rates and leaf shearing resistance of Duroia better than trees with Azteca. However, leaf herbivory, dry matter content, trichome density, and secondary metabolite production were the same in all trees. Survival depended directly on ant association (> 94% of trees died when ants were absent). This study extends our understanding of the long-term effects of strict ant-plant mutualism on host plant traits in the field and reinforces the use of D. hirsuta–M. schumanni as a model system suitable for eco-co-evolutionary research on plant–animal interactions.

Abstract The SARS-CoV-2 outbreak has provoked more than 6 million deaths worldwide. The scarcity of effective treatments and its virulence converted the vaccines into an essential tool to face it. The most used vaccines were the mRNA, adenovirus vector, and inactivated whole-virus. However, nowadays, infants aged

Abstract This work introduces a quantum subroutine for computing the distance between two patterns and integrates it into two quantum versions of the kNN classifier algorithm: one proposed by Schuld et al. and the other proposed by Quezada et al. Notably, our proposed subroutine is tailored to be memory-efficient, requiring fewer qubits for data encoding, while maintaining the overall complexity for both QkNN versions. This research focuses on comparing the performance of the two quantum kNN algorithms using the original Hamming distance with qubit-encoded features and our proposed subroutine, which computes the distance using amplitude-encoded features. Results obtained from analyzing thirteen different datasets (Iris, Seeds, Raisin, Mine, Cryotherapy, Data Bank Authentication, Caesarian, Wine, Haberman, Transfusion, Immunotherapy, Balance Scale, and Glass) show that both algorithms benefit from the proposed subroutine, achieving at least a 50% reduction in the number of required qubits, while maintaining a similar overall performance. For Shuld’s algorithm, the performance improved in Cryotherapy (68.89% accuracy compared to 64.44%) and Balance Scale (85.33% F1 score compared to 78.89%), was worse in Iris (86.0% accuracy compared to 95.33%) and Raisin (77.67% accuracy compared to 81.56%), and remained similar in the remaining nine datasets. While for Quezada’s algorithm, the performance improved in Caesarian (68.89% F1 score compared to 58.22%), Haberman (69.94% F1 score compared to 62.31%) and Immunotherapy (76.88% F1 score compared to 69.67%), was worse in Iris (82.67% accuracy compared to 95.33%), Balance Scale (77.97% F1 score compared to 69.21%) and Glass (40.04% F1 score compared to 28.79%), and remained similar in the remaining seven datasets.

Abstract Optical resonators are fundamental building blocks of photonic systems, enabling meta-surfaces, sensors, and transmission filters to be developed for a range of applications. Sub-wavelength size (

Abstract Pancreatic ductal adenocarcinoma represents one of the solid tumors showing the worst prognosis worldwide, with a high recurrence rate after adjuvant or neoadjuvant therapy. Circulating tumor DNA analysis raised as a promising non-invasive tool to characterize tumor genomics and to assess treatment response. In this study, surgical tumor tissue and sequential blood samples were analyzed by next-generation sequencing and were correlated with clinical and pathological characteristics. Thirty resectable/borderline pancreatic ductal adenocarcinoma patients treated at the Hospital Universitario de Navarra were included. Circulating tumoral DNA sequencing identified pathogenic variants in KRAS and TP53, and in other cancer-associated genes. Pathogenic variants at diagnosis were detected in patients with a poorer outcome, and were correlated with response to neoadjuvant therapy in borderline pancreatic ductal adneocarcinoma patients. Higher variant allele frequency at diagnosis was associated with worse prognosis, and thesum of variant allele frequency was greater in samples at progression. Our results build on the potential value of circulating tumor DNA for non-metastatic pancreatic ductal adenocarcinoma patients, by complementing tissue genetic information and as a non-invasive tool for treatment decision. Confirmatory studies are needed to corroborate these findings.

Abstract Whether, and how, cardioprotective effects of antiretroviral treatment (ART) in adolescents with perinatal HIV infection (APHIV) vary with age at treatment initiation is unknown. We used magnetic resonance imaging to compare cardiac status between APHIV initiated on ART at

Abstract Breast cancer (BRCA) is a prevalent malignancy with the highest incidence among females. BRCA can be categorized into five intrinsic molecular subtypes (LumA, LumB, HER2, Basal, and Normal), each characterized by varying molecular and clinical features determined by the expression of intrinsic genes (PAM50). The Heat Shock Protein (HSP) family is composed of 95 genes evolutionary conservated, they have critical roles in proteostasis in both normal and cancerous processes. Many studies have linked HSP to the development and spread of cancer. They modulate the activity of multiple proteins expressed by oncogenes and anti-oncogenes through a range of interactions. In this study, we evaluate the mutational changes that HSP undergoes in BRCA mainly from the TCGA database. We observe that Copy Number Variations (CNV) are the more frequent events analyzed surpassing the occurrence of point mutations, indels, and translation start site mutations. The Basal subtype showcased the highest count of amplified CNV, including subtype-specific changes, whereas the Luminals tumors accumulated the greatest number of deletion CNV. Meanwhile, the HER2 subtype exhibited a comparatively lower frequency of CNV alterations when compared to the other subtypes. This study integrates CNV and expression data, finding associations between these two variables and the influence of CNV on the deregulation of HSP expression. To enhance the role of HSP as a risk predictor in BRCA, we succeeded in identifying CNV profiles as a prognostic marker. We included Artificial Intelligence to improve the clustering of patients, and we achieved a molecular CNV signature as a significant risk factor independent of known classic markers, including molecular subtypes PAM50. This research enhances the comprehension of HSP DNA alterations in BRCA and its relation with predicting the risk of affected individuals providing insights to develop guide personalized treatment strategies.

Abstract There is a worrying scarcity of drug options for patients with severe COVID-19. Glycine possesses anti-inflammatory, cytoprotective, endothelium-protective, and platelet-antiaggregant properties, so its use in these patients seems promising. In this open label, controlled clinical trial, inpatients with severe COVID-19 requiring mechanical ventilation randomly received usual care (control group) or usual care plus 0.5 g/kg/day glycine by the enteral route (experimental group). Major outcomes included mortality, time to weaning from mechanical ventilation, total time on mechanical ventilation, and time from study recruitment to death. Secondary outcomes included laboratory tests and serum cytokines. Patients from experimental (n = 33) and control groups (n = 23) did not differ in basal characteristics. There were no differences in mortality (glycine group, 63.6% vs control group, 52.2%, p = 0.60) nor in any other major outcome. Glycine intake was associated with lower fibrinogen levels, either evaluated per week of follow-up (p

Abstract Most advanced medical imaging techniques, such as positron-emission tomography (PET), require tracers that are produced in conventional particle accelerators. This paper focuses on the evaluation of a potential alternative technology based on laser-driven ion acceleration for the production of radioisotopes for PET imaging. We report for the first time the use of a high-repetition rate, ultra-intense laser system for the production of carbon-11 in multi-shot operation. Proton bunches with energies up to 10–14 MeV were systematically accelerated in long series at pulse rates between 0.1 and 1 Hz using a PW-class laser. These protons were used to activate a boron target via the $$^{11}$$ 11 B(p,n) $$^{11}$$ 11 C nuclear reaction. A peak activity of 234 kBq was obtained in multi-shot operation with laser pulses with an energy of 25 J. Significant carbon-11 production was also achieved for lower pulse energies. The experimental carbon-11 activities measured in this work are comparable to the levels required for preclinical PET, which would be feasible by operating at the repetition rate of current state-of-the-art technology (10 Hz). The scalability of next-generation laser-driven accelerators in terms of this parameter for sustained operation over time could increase these overall levels into the clinical PET range.

Abstract We propose a distributed rewiring model which starts with a planar graph embedded into the Euclidean space and then behaves as a distributed system, where each node is provided with a set of dynamic links. The proposed rewiring evolves through cycles, where nodes explore the network to identify possible shortcuts and rewire their dynamic links. The rewiring decisions are subject to Euclidean and geodesic distance constrains. The emerging networks were assessed through topological and robustness analyses. We found that the networks display a variety of characteristics observed in complex networks encompassing phenomena such as preferential attachment, the distinctive traits of small-world networks, the presence of community structures, and robustness against degradation process. We consider that our proposal can be applied in the design of those self-managed systems in which there is a limitation on communication resources that can be represented by the Euclidean distance and, however, the components themselves can deploy strategies to optimize the transport of information and develop tolerance before contingencies.

Abstract Adverse pregnancy outcomes (APOs) affect a large proportion of pregnancies and represent an important cause of morbidity and mortality worldwide. Yet the pathophysiology of APOs is poorly understood, limiting our ability to prevent and treat these conditions. To search for genetic markers of maternal risk for four APOs, we performed multi-ancestry genome-wide association studies (GWAS) for pregnancy loss, gestational length, gestational diabetes, and preeclampsia. We clustered participants by their genetic ancestry and focused our analyses on three sub-cohorts with the largest sample sizes: European, African, and Admixed American. Association tests were carried out separately for each sub-cohort and then meta-analyzed together. Two novel loci were significantly associated with an increased risk of pregnancy loss: a cluster of SNPs located downstream of the TRMU gene (top SNP: rs142795512), and the SNP rs62021480 near RGMA. In the GWAS of gestational length we identified two new variants, rs2550487 and rs58548906 near WFDC1 and AC005052.1, respectively. Lastly, three new loci were significantly associated with gestational diabetes (top SNPs: rs72956265, rs10890563, rs79596863), located on or near ZBTB20, GUCY1A2, and RPL7P20, respectively. Fourteen loci previously correlated with preterm birth, gestational diabetes, and preeclampsia were found to be associated with these outcomes as well.

Abstract The transition to sustainable power infrastructure necessitates integrating various renewable energy sources efficiently. Our study introduces the deterministic balanced method (DBM) for optimizing hybrid energy systems, with a particular focus on using hydrogen for energy balance. The DBM translates the sizing optimization problem into a deterministic one, significantly reducing the number of iterations compared to state-of-the-art methods. Comparative analysis with HOMER Pro demonstrates a strong alignment of results, with deviations limited to a 5% margin, confirming the precision of our method in sizing determinations. Utilizing solar and wind data, our research includes a case study of Cairo International Airport, applying the DBM to actual energy demands.

Abstract Environmental niche modeling (ENM) has emerged as a promising tool for identifying grass species with potential for rangeland restoration. This approach can detect suitable areas and environments where these species can be planted. In this study, we employed ENM to estimate the potential distribution range of 50 grass species of the grasslands and shrublands of northern Mexico. The outcome of the ENM served to identify grass species with potential for restoration in Mexico, especially those not commonly used for that purpose in the past. Results suggested the possibility of selecting seven grass species with the potential for revegetating degraded grasslands, nine for shrublands, and six for alkaline soils. This research provides insights into the environmental adaptations of different grass species distributed in the rangelands of northern Mexico. Ecologists, conservation planners, researchers, and range managers could use these outcomes and the maps of the potential distribution ranges as supportive information to conduct effective restoration efforts. In turn, this can assist in increasing the probability of success of future rangelands restoration programs, which are often costly in terms of financial investments and labor.

Abstract This study examined the interplay between bacterial and fungal communities in the human gut microbiota, impacting on nutritional status and body weight. Cohorts of 10 participants of healthy weight, 10 overweight, and 10 obese individuals, underwent comprehensive analysis, including dietary, anthropometric, and biochemical evaluations. Microbial composition was studied via gene sequencing of 16S and ITS rDNA regions, revealing bacterial (bacteriota) and fungal (mycobiota) profiles. Bacterial diversity exceeded fungal diversity. Statistically significant differences in bacterial communities were found within healthy-weight, overweight, and obese groups. The Bacillota/Bacteroidota ratio (previously known as the Firmicutes/Bacteroidetes ratio) correlated positively with body mass index. The predominant fungal phyla were Ascomycota and Basidiomycota, with the genera Nakaseomyces, Kazachstania, Kluyveromyces, and Hanseniaspora, inversely correlating with weight gain; while Saccharomyces, Debaryomyces, and Pichia correlated positively with body mass index. Overweight and obese individuals who harbored a higher abundance of Akkermansia muciniphila, demonstrated a favorable lipid and glucose profiles in contrast to those with lower abundance. The overweight group had elevated Candida, positively linked to simple carbohydrate consumption. The study underscores the role of microbial taxa in body mass index and metabolic health. An imbalanced gut bacteriota/mycobiota may contribute to obesity/metabolic disorders, highlighting the significance of investigating both communities.

Abstract There is an increasing need to implement neuromorphic systems that are both energetically and computationally efficient. There is also great interest in using electric elements with memory, memelements, that can implement complex neuronal functions intrinsically. A feature not widely incorporated in neuromorphic systems is history-dependent action potential time adaptation which is widely seen in real cells. Previous theoretical work shows that power-law history dependent spike time adaptation, seen in several brain areas and species, can be modeled with fractional order differential equations. Here, we show that fractional order spiking neurons can be implemented using super-capacitors. The super-capacitors have fractional order derivative and memcapacitive properties. We implemented two circuits, a leaky integrate and fire and a Hodgkin–Huxley. Both circuits show power-law spiking time adaptation and optimal coding properties. The spiking dynamics reproduced previously published computer simulations. However, the fractional order Hodgkin–Huxley circuit showed novel dynamics consistent with criticality. We compared the responses of this circuit to recordings from neurons in the weakly-electric fish that have previously been shown to perform fractional order differentiation of their sensory input. The criticality seen in the circuit was confirmed in spontaneous recordings in the live fish. Furthermore, the circuit also predicted long-lasting stimulation that was also corroborated experimentally. Our work shows that fractional order memcapacitors provide intrinsic memory dependence that could allow implementation of computationally efficient neuromorphic devices. Memcapacitors are static elements that consume less energy than the most widely studied memristors, thus allowing the realization of energetically efficient neuromorphic devices.

Abstract Salmonella enterica serovar Typhimurium causes gastroenteritis and systemic infections in humans. For this bacterium the expression of a type III secretion system (T3SS) and effector proteins encoded in the Salmonella pathogenicity island-1 (SPI-1), is keystone for the virulence of this bacterium. Expression of these is controlled by a regulatory cascade starting with the transcriptional regulators HilD, HilC and RtsA that induce the expression of HilA, which then activates expression of the regulator InvF, a transcriptional regulator of the AraC/XylS family. InvF needs to interact with the chaperone SicA to activate transcription of SPI-1 genes including sicA, sopB, sptP, sopE, sopE2, and STM1239. InvF very likely acts as a classical activator; however, whether InvF interacts with the RNA polymerase alpha subunit RpoA has not been determined. Results from this study confirm the interaction between InvF with SicA and reveal that both proteins interact with the RNAP alpha subunit. Thus, our study further supports that the InvF/SicA complex acts as a classical activator. Additionally, we showed for the first time an interaction between a chaperone of T3SS effectors (SicA) and the RNAP.

Abstract Planning for palliative radiotherapy is performed without the advantage of MR or PET imaging in many clinics. Here, we investigated CT-only GTV delineation for palliative treatment of head and neck cancer. Two multi-institutional datasets of palliative-intent treatment plans were retrospectively acquired: a set of 102 non-contrast-enhanced CTs and a set of 96 contrast-enhanced CTs. The nnU-Net auto-segmentation network was chosen for its strength in medical image segmentation, and five approaches separately trained: (1) heuristic-cropped, non-contrast images with a single GTV channel, (2) cropping around a manually-placed point in the tumor center for non-contrast images with a single GTV channel, (3) contrast-enhanced images with a single GTV channel, (4) contrast-enhanced images with separate primary and nodal GTV channels, and (5) contrast-enhanced images along with synthetic MR images with separate primary and nodal GTV channels. Median Dice similarity coefficient ranged from 0.6 to 0.7, surface Dice from 0.30 to 0.56, and 95th Hausdorff distance from 14.7 to 19.7 mm across the five approaches. Only surface Dice exhibited statistically-significant difference across these five approaches using a two-tailed Wilcoxon Rank-Sum test (p ≤ 0.05). Our CT-only results met or exceeded published values for head and neck GTV autocontouring using multi-modality images. However, significant edits would be necessary before clinical use in palliative radiotherapy.