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In the human genome, heterozygous sites refer to genomic positions with a different allele or nucleotide variant on the maternal and paternal chromosomes. Resolving these allelic differences by chromosomal copy, also known as phasing, is achievable on a short-read sequencer when using a library preparation method that captures long-range genomic information. TELL-Seq is a library preparation that captures long-range genomic information with the aid of molecular identifiers (barcodes). The same barcode is used to tag the reads derived from the same long DNA fragment within a range of up to 200 kilobases (kb), generating linked-reads. This strategy can be used to phase an entire genome. Here, we introduce a TELL-Seq protocol developed for targeted applications, enabling the phasing of enriched loci of varying sizes, purity levels, and heterozygosity. To validate this protocol, we phased 2-200 kb loci enriched with different methods: CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis for the longest fragments, CRISPR/Cas9-mediated protection from exonuclease digestion for mid-size fragments, and long PCR for the shortest fragments. All selected loci have known clinical relevance: BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA. Collectively, the analyses show that TELL-Seq can accurately phase 2-200 kb targets using a short-read sequencer.

Malaria sterile immunity has been reproducibly induced by immunization with Plasmodium radiation-attenuated sporozoites (RAS). Analyses of sera from RAS-immunized individuals allowed the identification of P. falciparum antigens, such as the circumsporozoite protein (CSP), the basis for the RTS, S and R21Matrix-M vaccines. Similar advances in P. vivax (Pv) vaccination have been elusive. We previously reported 42% (5/12) of sterile protection in malaria-unexposed, Duffy-positive (Fy +) volunteers immunized with PvRAS followed by a controlled human malaria infection (CHMI). Using a custom protein microarray displaying 515 Pv antigens, we found a significantly higher reactivity to PvCSP and one hypothetical protein (PVX_089630) in volunteers protected against P. vivax infection. In mock-vaccinated Fy + volunteers, a strong antibody response to CHMI was also observed. Although the Fy- volunteers immunized with non-irradiated Pv-infected mosquitoes (live sporozoites) did not develop malaria after CHMI, they recognized a high number of antigens, indicating the temporary presence of asexual parasites in peripheral blood. Together, our findings contribute to the understanding of the antibody response to P. vivax infection and allow the identification of novel parasite antigens as vaccine candidates.Trial registration: ClinicalTrials.gov number: NCT01082341.

Abstract The present study aims to investigate the low-energy consumption and high-efficiency removal of arsenic from aqueous solutions. The designed adsorbent Fe/TBC was synthesized by impregnating iron on torrefaction henequen fibers. Isothermal adsorption experiments indicated maximum adsorption capacities of 7.30 mg/g and 8.98 mg/g for arsenic(V) at 25.0 °C and 40.0 °C, respectively. The interference testing showed that elevated levels of pH, HCO3 − concentration, and humic acid content in the solution could inhibit the adsorption of arsenic by Fe/TBC. Characterization of the adsorbent before and after adsorption using FTIR and SEM–EDS techniques confirmed arsenic adsorption mechanisms, including pore filling, electrostatic interaction, surface complexation, and H-bond adhesion. Column experiments were conducted to treat arsenic-spiked water and natural groundwater, with effective treatment volumes of 550 mL and 8792 mL, respectively. Lastly, the life cycle assessment (LCA) using OpenLCA 2.0.3 software was performed to treat 1 m3 of natural groundwater as the functional unit. The results indicated relatively significant environmental impacts during the Fe/TBC synthesis stage. The global warming potential resulting from the entire life cycle process was determined to be 0.8 kg CO2-eq. The results from batch and column experiments, regeneration studies, and LCA analysis indicate that Fe/TBC could be a promising adsorbent for arsenic(V).

Abstract The first therapeutical goal followed by neurooncological surgeons dealing with prefrontal gliomas is attempting supramarginal tumor resection preserving relevant neurological function. Therefore, advanced knowledge of the frontal aslant tract (FAT) functional neuroanatomy in high-order cognitive domains beyond language and speech processing would help refine neurosurgeries, predicting possible relevant cognitive adverse events and maximizing the surgical efficacy. To this aim we performed the recently developed correlational tractography analyses to evaluate the possible relationship between FAT’s microstructural properties and cognitive functions in 27 healthy subjects having ultra-high-field (7-Tesla) diffusion MRI. We independently assessed FAT segments innervating the dorsolateral prefrontal cortices (dlPFC-FAT) and the supplementary motor area (SMA-FAT). FAT microstructural robustness, measured by the tract’s quantitative anisotropy (QA), was associated with a better performance in episodic memory, visuospatial orientation, cognitive processing speed and fluid intelligence but not sustained selective attention tests. Overall, the percentual tract volume showing an association between QA-index and improved cognitive scores (pQACV) was higher in the SMA-FAT compared to the dlPFC-FAT segment. This effect was right-lateralized for verbal episodic memory and fluid intelligence and bilateralized for visuospatial orientation and cognitive processing speed. Our results provide novel evidence for a functional specialization of the FAT beyond the known in language and speech processing, particularly its involvement in several higher-order cognitive domains. In light of these findings, further research should be encouraged to focus on neurocognitive deficits and their impact on patient outcomes after FAT damage, especially in the context of glioma surgery.

Abstract The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of clinical interest. Currently, the most common VAT measurement methods include mathematical formulae based on anthropometric dimensions, often biased by human measurement errors, bio-impedance, and image techniques such as X-ray absorptiometry (DXA) analysis, which requires specialized equipment. However, previous studies showed the possibility of classifying people living with obesity according to their VAT through blood chemical concentrations by applying machine learning techniques. In addition, most of the efforts were spent on men living with obesity while little was done for women. Therefore, this study aims to compare the performance of the multilinear regression model (MLR) in estimating VAT and six different supervised machine learning classifiers, including logistic regression (LR), support vector machine and decision tree-based models, to categorize 149 women living with obesity. For clustering, the study population was categorized into classes 0, 1, and 2 according to their VAT and the accuracy of each MLR and classification model was evaluated using DXA-data (DXAdata), blood chemical concentrations (BLDdata), and both DXAdata and BLDdata together (ALLdata). Estimation error and $$\hbox {R}^{2}$$ R 2 were computed for MLR, while receiver operating characteristic (ROC) and precision-recall curves (PR) area under the curve (AUC) were used to assess the performance of every classification model. MLR models showed a poor ability to estimate VAT with mean absolute error $$\ge 401.40$$ ≥ 401.40 and $$\hbox {R}^{2} \le 0.62$$ R 2 ≤ 0.62 in all the datasets. The highest accuracy was found for LR with values of 0.57, 0.63, and 0.53 for ALLdata, DXAdata, and BLDdata, respectively. The ROC AUC showed a poor ability of both ALLdata and DXAdata to distinguish class 1 from classes 0 and 2 (AUC = 0.31, 0.71, and 0.85, respectively) as also confirmed by PR (AUC = 0.24, 0.57, and 0.73, respectively). However, improved performances were obtained when applying LR model to BLDdata (ROC AUC $$\ge $$ ≥ 0.61 and PR AUC $$\ge $$ ≥ 0.42), especially for class 1. These results seem to suggest that, while a direct and reliable estimation of VAT was not possible in our cohort, blood sample-derived information can robustly classify women living with obesity by machine learning-based classifiers, a fact that could benefit the clinical practice, especially in those health centres where medical imaging devices are not available. Nonetheless, these promising findings should be further validated over a larger population.

Abstract Monometallic and bimetallic Cu:Ni catalysts with different Cu:Ni molar ratios (3:1, 2:1, 1:1, 1:2, 1:3) were synthesized by wetness impregnation on activated carbon and characterized by TPR (temperature programmed reduction), XRD (X-ray diffraction) and XPS (X-ray photoelectron spectroscopy). The synthesized catalysts were evaluated in the gas phase production of diethyl carbonate from ethanol and carbon dioxide. The largest catalytic activity was obtained over the bimetallic catalyst with a Cu:Ni molar ratio of 3:1. Its improved activity was attributed to the formation of a Cu–Ni alloy on the surface of the catalyst, evidenced by XPS and in agreement with a previous assignment based on Vegard law and TPR analysis. During the reaction rate experiments, it observed the presence of a maximum of the reaction rate as a function of temperature, a tendency also reported for other carbon dioxide–alcohol reactions. It showed that the reaction rate-temperature data can be adjusted with a reversible rate equation. The initial rate as a function of reactant partial pressure data was satisfactorily adjusted using the forward power law rate equation and it was found that the reaction rate is first order in CO2 and second order in ethanol.

Abstract Although asexuality became a growing research subject over the last decade, data on the mental health of individuals identifying as asexual is still rare. The key objective of the present study was to examine depressive symptoms among individuals identifying as asexual. Data of LGBTQIA+ (Lesbian, Gay, Bi-sexual, Trans*, Queer, Inter*, Asexual and/or + indicating others within the community) and cisgender heterosexual individuals was collected through an online survey during the COVID-19 lockdowns in Germany. The survey included questions about sexual and gender identity, depressive symptoms, and asexual identity. An analysis of N = 6601 participants was conducted. A total of n = 445 individuals identified as asexual. Regression results indicated identifying as asexual being significantly associated with higher depressive symptoms. Results suggest that individuals identifying as asexual represent a vulnerable group within the group of sexual minorities, one that fundamentally requires special psychosocial support, especially in times of pandemics.

Abstract Age-related changes in emotional processing are complex, with a bias toward positive information. However, the impact of aging on emotional responses in positive everyday situations remains unclear. Virtual Reality (VR) has emerged as a promising tool for investigating emotional processing, offering a unique balance between ecological validity and experimental control. Yet, limited evidence exists regarding its efficacy to elicit positive emotions in older adults. Our study aimed to explore age-related differences in positive emotional responses to immersion in both social and nonsocial virtual emotional environments. We exposed 34 younger adults and 24 older adults to natural and social 360-degree video content through a low immersive computer screen and a highly immersive Head-Mounted Display, while recording participants' physiological reactions. Participants also provided self-report of their emotions and sense of presence. The findings support VR’s efficacy in eliciting positive emotions in both younger and older adults, with age-related differences in emotional responses influenced by the specific video content rather than immersion level. These findings underscore the potential of VR as a valuable tool for examining age-related differences in emotional responses and developing VR applications to enhance emotional wellbeing across diverse user populations.

Abstract Diabetes mellitus (DM) is a risk factor for the development of ulnar nerve entrapment (UNE). Differences in surgical outcomes for UNE between patients with and without DM have been reported, but studies on presurgical management are scarce. This study aimed to evaluate the presurgical management of UNE in patients with (DM diagnosis

Abstract No-take marine protected areas (MPAs) can mitigate the effects of overfishing, climate change and habitat degradation, which are leading causes of an unprecedented global biodiversity crisis. However, assessing the effectiveness of MPAs, especially in remote oceanic islands, can be logistically challenging and often restricted to relatively shallow and accessible environments. Here, we used a long-term dataset (2010–2019) collected by the DeepSee submersible of the Undersea Hunter Group that operates in Isla del Coco National Park, Costa Rica, to (1) determine the frequency of occurrence of elasmobranch species at two depth intervals (50–100 m; 300–400 m), and (2) investigate temporal trends in the occurrence of common elasmobranch species between 2010 and 2019, as well as potential drivers of the observed changes. Overall, we observed 17 elasmobranch species, 15 of which were recorded on shallow dives (50–100 m) and 11 on deep dives (300–400 m). We found a decreasing trend in the probability of occurrence of Carcharhinus falciformis over time (2010–2019), while other species (e.g. Taeniurops meyeni, Sphyrna lewini, Carcharhinus galapagensis, Triaenodon obesus, and Galeocerdo cuvier) showed an increasing trend. Our study suggests that some species like S. lewini may be shifting their distributions towards deeper waters in response to ocean warming but may also be sensitive to low oxygen levels at greater depths. These findings highlight the need for regional 3D environmental information and long-term deepwater surveys to understand the extent of shark and ray population declines in the ETP and other regions, as most fishery-independent surveys from data-poor countries have been limited to relatively shallow waters.

Abstract Plant biostimulants are widely applied in agriculture for their ability to improve plant fitness. In the present work, the impact of Graminaceae-derived protein hydrolysate (P) and its lighter molecular fraction F3 (

Abstract Inflammatory bowel diseases (IBD) are a group of chronic inflammatory conditions of the gastrointestinal tract associated with multiple pathogenic factors, including dysregulation of the immune response. Effector CD4+ T cells and regulatory CD4+ T cells (Treg) are central players in maintaining the balance between tolerance and inflammation. Interestingly, genetic modifications in these cells have been implicated in regulating the commitment of specific phenotypes and immune functions. However, the transcriptional program controlling the pathogenic behavior of T helper cells in IBD progression is still unknown. In this study, we aimed to find master transcription regulators controlling the pathogenic behavior of effector CD4+ T cells upon gut inflammation. To achieve this goal, we used an animal model of IBD induced by the transfer of naïve CD4+ T cells into recombination-activating gene 1 (Rag1) deficient mice, which are devoid of lymphocytes. As a control, a group of Rag1 −/− mice received the transfer of the whole CD4+ T cells population, which includes both effector T cells and Treg. When gut inflammation progressed, we isolated CD4+ T cells from the colonic lamina propria and spleen tissue, and performed bulk RNA-seq. We identified differentially up- and down-regulated genes by comparing samples from both experimental groups. We found 532 differentially expressed genes (DEGs) in the colon and 30 DEGs in the spleen, mostly related to Th1 response, leukocyte migration, and response to cytokines in lamina propria T-cells. We integrated these data into Gene Regulatory Networks to identify Master Regulators, identifying four up-regulated master gene regulators (Lef1, Dnmt1, Mybl2, and Jup) and only one down-regulated master regulator (Foxo3). The altered expression of master regulators observed in the transcriptomic analysis was confirmed by qRT-PCR analysis and found an up-regulation of Lef1 and Mybl2, but without differences on Dnmt1, Jup, and Foxo3. These two master regulators have been involved in T cells function and cell cycle progression, respectively. We identified two master regulator genes associated with the pathogenic behavior of effector CD4+ T cells in an animal model of IBD. These findings provide two new potential molecular targets for treating IBD.

People vary both in their embrace of their society's traditions, and in their perception of hazards as salient and necessitating a response. Over evolutionary time, traditions have offered avenues for addressing hazards, plausibly resulting in linkages between orientations toward tradition and orientations toward danger. Emerging research documents connections between traditionalism and threat responsivity, including pathogen-avoidance motivations. Additionally, because hazard-mitigating behaviors can conflict with competing priorities, associations between traditionalism and pathogen avoidance may hinge on contextually contingent tradeoffs. The COVID-19 pandemic provides a real-world test of the posited relationship between traditionalism and hazard avoidance. Across 27 societies (N = 7844), we find that, in a majority of countries, individuals' endorsement of tradition positively correlates with their adherence to costly COVID-19-avoidance behaviors; accounting for some of the conflicts that arise between public health precautions and other objectives further strengthens this evidence that traditionalism is associated with greater attention to hazards.

Abstract The cladoceran crustacean Daphnia exhibits phenotypic plasticity, a phenomenon that leads to diverse phenotypes from one genome. Alternative usage of gene isoforms has been considered a key gene regulation mechanism for controlling different phenotypes. However, to understand the phenotypic plasticity of Daphnia, gene isoforms have not been comprehensively analyzed. Here we identified 25,654 transcripts derived from the 9710 genes expressed during environmental sex determination of Daphnia magna using the long-read RNA-Seq with PacBio Iso-Seq. We found that 14,924 transcripts were previously unidentified and 5713 genes produced two or more isoforms. By a combination of Illumina short-read RNA-Seq, we detected 824 genes that implemented switching of the highest expressed isoform between females and males. Among the 824 genes, we found isoform switching of an ortholog of CREB-regulated transcription coactivator, a major regulator of carbohydrate metabolism in animals, and a correlation of this switching event with the sexually dimorphic expression of carbohydrate metabolic genes. These results suggest that a comprehensive catalog of isoforms may lead to understanding the molecular basis for environmental sex determination of Daphnia. We also infer the applicability of the full-length isoform analyses to the elucidation of phenotypic plasticity in Daphnia.

Abstract Direct human-caused mortality accounts for about half of all large mammal mortality in North America. For social species like gray wolves (Canis lupus), the death of pack members can disrupt pack structure and cause pack dissolution, and mortality of breeding adults or wolves during reproduction and pup-rearing can decrease pup recruitment. We estimated minimum and maximum probability of wolf pack persistence in Wisconsin, USA, during biological years (15 April–14 April) 2011–2019 and evaluated the influence of pack size and legal harvest mortality on pack persistence during 2012–2014. Harvests comprised 75–161 mortalities within 194 monitored packs during 2012–2014, with 56–74% of packs having no wolves harvested each year. As an index of reproduction during 2013–2019, we also estimated the proportion of packs where pups responded to howl surveys. We evaluated the influence of pack size, legal harvest, and agency removal on reproduction during 2013–2015. Annual maximum pack persistence probability was uniformly high (0.95–1.00), and annual minimum pack persistence probability ranged from 0.86–0.98 with a possible decline during years of harvest. Reproduction was similar in years following harvest and agency removal (2013–2015, pup response = 0.27–0.40), and years without harvest or agency removal the year prior (2016–2019, pup response = 0.28–0.66). Pack size had a positive effect on pack persistence and reproduction. Total number of wolf mortalities and number of adult male and females removed did not influence pack persistence or reproduction. We suggest that low per-pack mortality, timing of harvest and agency removal, and harvest characteristics during 2012–2014 supported stable pack persistence and reproduction.

Abstract Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classifying a diversity of inputs. In bioinformatics, DLMs have been used to predict protein structures, transcription factor-binding sites, and promoters. In this work, we propose a hybrid model to identify transcription factors (TFs) among prokaryotic and eukaryotic protein sequences, named Deep Regulation (DeepReg) model. Two architectures were used in the DL model: a convolutional neural network (CNN), and a bidirectional long-short-term memory (BiLSTM). DeepReg reached a precision of 0.99, a recall of 0.97, and an F1-score of 0.98. The quality of our predictions, the bias-variance trade-off approach, and the characterization of new TF predictions were evaluated and compared against those produced by DeepTFactor, as well as against experimental data from three model organisms. Predictions based on our DLM tended to exhibit less variance and bias than those from DeepTFactor, thus increasing reliability and decreasing overfitting.

Abstract Fluorinated graphene, a two-dimensional nanomaterial composed of three atomic layers, a central carbon layer sandwiched between two layers of fluorine atoms, has attracted considerable attention across various fields, particularly for its potential use in biomedical applications. Nonetheless, scant effort has been devoted to assessing the potential toxicological implications of this nanomaterial. In this study, we scrutinize the potential impact of fluorinated graphene on a protein model, HP35 by utilizing extensive molecular dynamics (MD) simulation methods. Our MD results elucidate that upon adsorption to the nanomaterial, HP35 undergoes a denaturation process initiated by the unraveling of the second helix of the protein and the loss of the proteins hydrophobic core. In detail, substantial alterations in various structural features of HP35 ensue, including alterations in hydrogen bonding, Q value, and RMSD. Subsequent analyses underscore that hydrophobic and van der Waals interactions (predominant), alongside electrostatic energy (subordinate), exert influence over the adsorption of HP35 on the fluorinated graphene surface. Mechanistic scrutiny attests that the unrestrained lateral mobility of HP35 on the fluorinated graphene nanomaterial primarily causes the exposure of HP35's hydrophobic core, resulting in the eventual structural denaturation of HP35. A trend in the features of 2D nanostructures is proposed that may facilitate the denaturation process. Our findings not only substantiate the potential toxicity of fluorinated graphene but also unveil the underlying molecular mechanism, which thereby holds significance for the prospective utilization of such nanomaterials in the field of biomedicine.

Abstract This research aimed to determine whether accomplished surfers could accurately perceive how changes to surfboard fin design affected their surfing performance. Four different surfboard fins, including conventional, single-grooved, and double-grooved fins, were developed using computer-aided design combined with additive manufacturing (3D printing). We systematically installed these 3D-printed fins into instrumented surfboards, which six accomplished surfers rode on waves in the ocean in a random order while blinded to the fin condition. We quantified the surfers’ wave-riding performance during each surfing bout using a sport-specific tracking device embedded in each instrumented surfboard. After each fin condition, the surfers rated their perceptions of the Drive, Feel, Hold, Speed, Stiffness, and Turnability they experienced while performing turns using a visual analogue scale. Relationships between the surfer’s perceptions of the fins and their surfing performance data collected from the tracking devices were then examined. The results revealed that participants preferred the single-grooved fins for Speed and Feel, followed by double-grooved fins, commercially available fins, and conventional fins without grooves. Crucially, the surfers’ perceptions of their performance matched the objective data from the embedded sensors. Our findings demonstrate that accomplished surfers can perceive how changes to surfboard fins influence their surfing performance.

Abstract Rib fractures are highly predictive of non-accidental trauma in children under 3 years old. Rib fracture detection in pediatric radiographs is challenging because fractures can be obliquely oriented to the imaging detector, obfuscated by other structures, incomplete, and non-displaced. Prior studies have shown up to two-thirds of rib fractures may be missed during initial interpretation. In this paper, we implemented methods for improving the sensitivity (i.e. recall) performance for detecting and localizing rib fractures in pediatric chest radiographs to help augment performance of radiology interpretation. These methods adapted two convolutional neural network (CNN) architectures, RetinaNet and YOLOv5, and our previously proposed decision scheme, “avalanche decision”, that dynamically reduces the acceptance threshold for proposed regions in each image. Additionally, we present contributions of using multiple image pre-processing and model ensembling techniques. Using a custom dataset of 1109 pediatric chest radiographs manually labeled by seven pediatric radiologists, we performed 10-fold cross-validation and reported detection performance using several metrics, including F2 score which summarizes precision and recall for high-sensitivity tasks. Our best performing model used three ensembled YOLOv5 models with varied input processing and an avalanche decision scheme, achieving an F2 score of 0.725 ± 0.012. Expert inter-reader performance yielded an F2 score of 0.732. Results demonstrate that our combination of sensitivity-driving methods provides object detector performance approaching the capabilities of expert human readers, suggesting that these methods may provide a viable approach to identify all rib fractures.

Abstract In the human genome, heterozygous sites refer to genomic positions with a different allele or nucleotide variant on the maternal and paternal chromosomes. Resolving these allelic differences by chromosomal copy, also known as phasing, is achievable on a short-read sequencer when using a library preparation method that captures long-range genomic information. TELL-Seq is a library preparation that captures long-range genomic information with the aid of molecular identifiers (barcodes). The same barcode is used to tag the reads derived from the same long DNA fragment within a range of up to 200 kilobases (kb), generating linked-reads. This strategy can be used to phase an entire genome. Here, we introduce a TELL-Seq protocol developed for targeted applications, enabling the phasing of enriched loci of varying sizes, purity levels, and heterozygosity. To validate this protocol, we phased 2–200 kb loci enriched with different methods: CRISPR/Cas9-mediated excision coupled with pulse-field electrophoresis for the longest fragments, CRISPR/Cas9-mediated protection from exonuclease digestion for mid-size fragments, and long PCR for the shortest fragments. All selected loci have known clinical relevance: BRCA1, BRCA2, MLH1, MSH2, MSH6, APC, PMS2, SCN5A-SCN10A, and PKI3CA. Collectively, the analyses show that TELL-Seq can accurately phase 2–200 kb targets using a short-read sequencer.