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Insights into a water-mediated catalytic triad architecture in CE20 carbohydrate esterases

Abstract Carbohydrate esterases modify polysaccharides by removing different ester moieties thereby affecting their physicochemical properties and their accessibility by glycoside hydrolases. We determined the full-length structures of two members (Fl8CE20_II and PpCE20_II) from the carbohydrate esterase family 20 (CE20) by X-ray crystallography that feature an ancillary domain, inserted into the catalytic SGNH-hydrolase domain. Detailed structural analysis identifies a so far undescribed catalytic triad architecture which lacks the typical aspartate for polarization of the histidine but instead reveals a precisely coordinated water molecule mediating contact between the His and Asp. This coordinated water in the Ser-His-(H2O-Asp/Asn) motif, as further confirmed by mutational studies and by determination of kinetic constants, is crucial for catalytic activity. We therefore term this active site architecture a water-mediated catalytic triad.

Characterization of a Drosophila model to study functions of guarana seeds

The seeds of the Amazonian fruit, guarana (Paullinia cupana), have been used as traditional medicine and, in recent years, as an ingredient in commercial energy beverages. However, mechanisms underlying the beneficial effects of guarana are not well understood. To establish a model system to study molecular mechanisms underlying the beneficial effects of guarana, we investigated how its ingestion affects physiology in the fruit fly, Drosophila melanogaster. We found that guarana enhanced oxidative stress resistance, longevity, physical activity, and fecundity of flies. To deepen our understanding of guarana function, we performed transcriptomic, metabolomic, and fecal microbiome analyses. Transcriptomic analysis identified 58 upregulated and eight downregulated genes in guarana-fed flies. Highly upregulated genes included those encoding detoxification enzymes, such as cytochromes P450 (CYPs), glutathione S-transferases (GSTs), and Juvenile hormone epoxide hydrolase 1 (Jheh1). Metabolomic analysis identified glutathione metabolism, an antioxidant system, as being promoted by guarana ingestion. These findings likely represent the molecular basis for enhanced oxidative stress resistance and longevity in guarana-fed flies. We also analyzed fecal microbiota composition and found significant changes: guarana increased the proportion of probiotic Lactobacillus species, some species known to extend longevity. At the same time, it decreased the proportion of Enterococcus faecalis, a species known to reduce longevity. These changes might have contributed to the beneficial effects of dietary guarana. Thus, we demonstrate that guarana exerts beneficial effects in flies and provide fundamental data for further investigation of its biological mechanisms in Drosophila.

vPro-MS enables identification of human-pathogenic viruses from patient samples by untargeted proteomics

Abstract Viral infections are commonly diagnosed by the detection of viral genome fragments or proteins using targeted methods such as PCR and immunoassays. In contrast, metagenomics enables the untargeted identification of viral genomes, expanding its applicability across a broader spectrum. In this study, we introduce proteomics as a complementary approach for the untargeted identification of human-pathogenic viruses from patient samples. The viral proteomics workflow (vPro-MS) is based on an in-silico derived peptide library covering the human virome in UniProtKB (331 viruses, 20,386 genomes, 121,977 peptides). A scoring algorithm (vProID score) is developed to assess the confidence of virus identification from proteomics data (https://github.com/RKI-ZBS/vPro-MS). In combination with diaPASEF-based data acquisition, this workflow enables the analysis of up to 60 samples per day. The specificity is determined to be >99,9% in an analysis of 221 plasma, swab and cell culture samples covering 17 different viruses. The sensitivity of this approach for the detection of SARS-CoV-2 in nasopharyngeal swabs corresponds to a PCR cycle threshold of 27 with comparable quantitative accuracy to metagenomics. vPro-MS enables the integration of untargeted virus identification in large-scale proteomic studies of biofluids such as human plasma to detect previously undiscovered virus infections in patient specimens.

Prenatal developmental toxicity of Urtica simensis essential oil in rat embryos and rat fetuses

Pregnant women inhaled fresh U. simensis steam vapor to fumigate their bodies, and boiled it for tea. However, the safety of this practice during pregnancy has not yet been reported. This study aimed to evaluate the prenatal developmental toxicity of U.simensis essential oil in rat embryos and fetuses. The essential oil was extracted through hydrodistillation from aerial parts of U.simensis. One hundred pregnant rats were randomly assigned to five groups (20 rats per group). Groups I to III were administered oral doses of 250, 500, and 1000 mg/kg of U.simensis essential oil. Groups IV and V were used as pair-fed and ad libitum controls, respectively. The developing embryos and fetuses were retrieved on 12 and 20 days of gestation, respectively. Embryos were evaluated for growth and developmental delays. Fetuses were evaluated for external, skeletal, and visceral abnormalities. Oral doses of 250 and 500 mg/kg of U.simensis essential oil had no observed adverse effects in both rat embryos and rat fetuses. However, somite numbers and morphological scores were significantly decreased in gravid rats treated with 1000 mg/kg of essential oil. Embryonic developments of the caudal neural tube and forebrain were significantly delayed in pregnant dams administered 1000 mg/kg of essential oil. Crown-rump length and fetal weight were significantly decreased in gravid rats given 1000 mg/kg of essential oil. Gravid rats received 1000 mg/kg of essential oil also revealed a significant increase in fetal resorption. In conclusion, high-dose oral administration of U.simensis essential oil revealed detrimental effects in both rat embryos and fetuses. Therefore, pregnant women should be informed the potential risks associated with the nutraceutical use of U.simensis during pregnancy.

A cytokine-based designer enzyme with an abiological multinuclear metal center exhibits intrinsic and extrinsic catalysis

Detecting outbreaks using a spatial latent field

In this paper, we present a method for estimating the infection-rate of a disease as a spatial-temporal field. Our data comprises time-series case-counts of symptomatic patients in various areal units of a region. We extend an epidemiological model, originally designed for a single areal unit, to accommodate multiple units. The field estimation is framed within a Bayesian context, utilizing a parameterized Gaussian random field as a spatial prior. We apply an adaptive Markov chain Monte Carlo method to sample the posterior distribution of the model parameters condition on COVID-19 case-count data from three adjacent counties in New Mexico, USA. Our results suggest that the correlation between epidemiological dynamics in neighboring regions helps regularize estimations in areas with high variance (i.e., poor quality) data. Using the calibrated epidemic model, we forecast the infection-rate over each areal unit and develop a simple anomaly detector to signal new epidemic waves. Our findings show that anomaly detector based on estimated infection-rates outperforms a conventional algorithm that relies solely on case-counts.

A transcription factor ensemble orchestrates bundle sheath expression in rice

Abstract C4 photosynthesis has evolved in over sixty plant lineages and improves photosynthetic efficiency by ~50%. One unifying character of C4 plants is photosynthetic activation of a compartment such as the bundle sheath, but gene regulatory networks controlling this cell type are poorly understood. In Arabidopsis, a bipartite MYC-MYB transcription factor module restricts gene expression to these cells, but in grasses the regulatory logic allowing bundle sheath gene expression has not been defined. Using the global staple and C3 crop rice, we find that the SULFITE REDUCTASE promoter is sufficient for strong bundle sheath expression. This promoter encodes an intricate cis-regulatory logic with multiple activators and repressors acting combinatorially. Within this landscape we identify a distal cis-regulatory module (CRM) activated by an ensemble of transcription factors from the WRKY, G2-like, MYB-related, DOF, IDD and bZIP families. This module is necessary and sufficient to pattern gene expression to the rice bundle sheath. Oligomerisation of the CRM and fusion to core promoters containing Y-patches allow activity to be increased 220-fold. This CRM generates bundle sheath-specific expression in Arabidopsis indicating deep conservation in function between monocotyledons and dicotyledons. In summary, we identify an ancient, short, and tuneable CRM patterning expression to the bundle sheath that we anticipate will be useful for engineering this cell type in various crop species.

Small target detection algorithm based on the fusion attention mechanism and multi-layer convolution

In the realm of unmanned aerial vehicles, we proposed an enhanced small target detection algorithm, MGAC-YOLO, to address the challenges of missed detections and low accuracy associated with small target identification. Initially, we designed the MConv (Multi-layer Convolution) module to replace the conventional Conv module within the backbone network, thereby augmenting the dimensionality of information capture and enhancing the detection performance for small targets. Subsequently, we harnessed the advantages of both attention mechanisms—GAM (Global Attention Mechanism) and CloAttention (Contextualized Local and Global Attention)—to create a GACAttention module that extracts small target features from both global and local perspectives, thereby enriching the network’s focus on small target feature information and further enhancing its feature processing capabilities. Finally, we incorporated an additional small target detection layer to capture feature information at a shallower level, thereby reducing the likelihood of missed detections and bolstering the detection capabilities for small targets. Experimental results on the VisDrone2019 dataset demonstrate that the Precision, mAP50, and mAP50-95 of the MGAC-YOLO algorithm have improved by 5.3%, 6.3%, and 4.4%, respectively, in comparison to the baseline model YOLOv8s. Furthermore, when compared to other leading algorithms, the MGAC-YOLO algorithm has exhibited notable superiority.

A framework for complex signal processing via synthetic biological operational amplifiers

Exploration of short-term predictions and long-term projections of Barents Sea cod biomass using statistical methods on data from dynamical models

This study aims to explore how well simple statistical modeling can generate short-term predictions and long-term projections of the total biomass of the Northeast Arctic stock of Atlantic cod (Gadus Morhua) inhabiting the Barents Sea. We examine the predictability of statistical models only based on hydrographic and lower trophic level biological variables from dynamical modeling. Simple and multiple linear regression models are developed based on gridded variables from the regional ocean model NEMO-NAA10km and the ecosystem model NORWECOM.E2E. This includes the essential environmental variables temperature, salinity, sea ice concentration, primary production and secondary production. The regression models are statistically evaluated to find variables that can capture variability in Barents Sea cod biomass. Finally, future total cod stock biomass is projected by applying the best found regression models to the range of downscaled IPCC climate scenarios from the coupled Intercomparison Project Phase 6 (CMIP6 Shared Socioeconomic Pathways; SSP1–2.6, SSP2–4.5, SSP5–8.5). Our prediction models are based on variables that affect cod both directly and indirectly. We find that several regression models have high prediction skill and capture the variations in total stock biomass of the Northeast Arctic cod well. Our results suggest that increased ocean temperature and abundant zooplankton may lead to a large cod stock. However, even if total stock biomass has a positive trend with an increase in copepods in the highest warming scenario SSP5–8.5, we found that it has a negative trend in the low emission scenario SSP1–2.6 when the regional ocean and ecosystem models show weak cooling and reduced zooplankton. We show that variability in essential environmental variables can provide a remarkably good first approximation to cod dynamics. However, to resolve the full picture other factors like fishing and natural mortality also need to be addressed explicitly.

Local structural distortions drive magnetic molecular field in compositionally complex spinel oxide

Reassessment of public awareness and prevention strategies for HIV and COVID-19 co-infections through epidemic modeling

A co–infection model between HIV and COVID-19 that takes into account COVID-19 vaccination and public awareness is discussed in this article. Rigorous analysis of the model is conducted to establish the existence and local stability conditions of the single-infection models. We discover that when the corresponding reproduction number for COVID-19 and HIV exceeds one, the disease continues to exist in both single-infection models. Furthermore, HIV will always be eradicated if its reproduction number is less than one. Nevertheless, this does not apply to the single-infection COVID-19 model. Even when the fundamental reproduction number is less than one, an endemic equilibrium point may exist due to the potential for a backward bifurcation phenomenon. Consequently, in the single-infection COVID-19 model, bistability between the endemic and disease-free equilibrium may arise when the basic reproduction number is less than one. From the co–infection model, we find that the reproduction number of the co–infection model is the maximum value between the reproduction number of HIV and COVID-19. Our numerical continuation experiments on the co–infection model reveal a threshold indicating that both HIV and COVID-19 may coexist within the population. The disease-free equilibrium for both HIV and COVID-19 is stable only if the reproduction numbers are less than one. Additionally, our two-parameter continuation analysis of the bifurcation diagram shows that the condition where both reproduction numbers equal one serves as an organizing center for the dynamic behavior of the co-infection model. An extended version of our model incorporates four different interventions: face mask usage, vaccination, and public awareness for COVID-19, as well as condom use for HIV, formulated as an optimal control problem. The Pontryagin’s Maximum Principle is employed to characterize the optimal control problem, which is solved using a forward-backward iterative method. Numerical investigations of the optimal control model highlight the critical role of a well-designed combination of interventions to achieve optimal reductions in the spread of both HIV and COVID-19.

Cholesterol modulates membrane elasticity via unified biophysical laws

Factors influencing the adoption of the BYOD policy in teaching hospitals: A cross-sectional study from Southeastern Iran

Introduction Clinicians are increasingly using their devices for work at hospitals, a practice known as Bring-your-own-device (BYOD), to enhance productivity and mobility. This study aimed to determine the affecting factors of intention to adoption of BYOD policy in public hospitals from the healthcare staff’s perspective. Methods A cross-sectional analytical study was done in 2024. The study population comprised 1130 healthcare workers from five teaching hospitals. A researcher-made and validated questionnaire was distributed among 620 samples. Data were analyzed by SPSS software using descriptive (mean and standard deviation) and analytical (Pearson and Spearman correlation test) statistics. Results The mean score of facilitating conditions, perceived cost-effectiveness, perceived trust, perceived usefulness, perceived ease of use, and intention to adoption BYOD was 3.90 ± 0.87, 3.87 ± 0.97, 3.83 ± 0.93, 3.76 ± 1.01, 3.07 ± 0.48 and 3.62 ± 1.16, respectively. There was a positive significant correlation between factors of perceived usefulness, perceived ease of use, perceived cost effectiveness, perceived trust, and facilitating conditions with an intention to adoption the BYOD policy (P < 0.05). Conclusion Healthcare workers have partially intended to adopt the BYOD policy. Ensuring the security of access to healthcare information, provision, support and maintenance of devices used by staff in the workplace for job-related activities can play a significant role in promoting the intention to adoption the BYOD. The results of the present study can be useful for planning and policy-making to increase the adoption and acceptance of the BYOD method in hospitals.

mRNA trafficking directs cell-size-scaling of mitochondria distribution and function

Abstract The subcellular positioning of organelles is critical to their function and is dynamically adapted to changes in cell morphology. Yet, how cells sense shifts in their dimensions and redistribute organelles accordingly remains unclear. Here we reveal that cell-size-scaling of mitochondria distribution and function is directed by polarised trafficking of mRNAs. We identify a 29 bp 3’UTR motif in mRNA encoding TRAK2, a key determinant of mitochondria retrograde transport, that promotes cell-size-dependent targeting of TRAK2 mRNA to distal sites of cell protrusions. Cell-size-scaled mRNA polarisation in turn scales mitochondria distribution by defining the precise site of TRAK2-MIRO1 retrograde transport complex assembly. Consequently, 3’UTR motif excision perturbs size-regulated transport and eradicates scaling of mitochondria positioning, triggering distal accumulation of mitochondria and progressive hypermotility as cells increase size. Together, our results reveal an RNA-driven mechanistic basis for the cell-size-scaling of organelle distribution and function that is critical to homeostatic control of motile cell behaviour.

A multi-biomarker approach to risk stratification and detection of early cardiac disease in systemic sclerosis

Objective We sought to investigate the relationship between serum biomarkers of cardiac dysfunction, longitudinal strain on echocardiography, and all-cause mortality in patients with systemic sclerosis. Methods This was an observational study using a biorepository of serum samples of patients with systemic sclerosis who underwent echocardiography. We investigated 3 biomarkers: periostin, galectin-3, and N-terminal prohormone brain natriuretic peptide and applied a K-means clustering resulting in 3 patient clusters. We subsequently measured left ventricular and right ventricular free wall longitudinal strain in each cluster. We then determined the association between each cluster and time to all-cause mortality compared to N-terminal prohormone brain natriuretic peptide, alone. Results The 125 patients with systemic sclerosis included in the study were divided into 3 clusters based on biomarker levels (Cluster 1: N = 75; Cluster 2: N = 39; Cluster 3: N = 11). Compared to Cluster 1, Cluster 2 had only elevated periostin levels whereas Cluster 3 had elevated levels of all 3 serum biomarkers and was characterized by reduced left ventricular and right ventricular free wall longitudinal strain, regionally and globally. When adjusted for age, sex, systemic sclerosis disease duration, and forced vital capacity, patients in Cluster 3 had a HR of 14.42 (95% CI: 4.82, 43.18) for all-cause mortality compared to those in Cluster 1. Conclusion In conclusion, combining N-terminal prohormone brain natriuretic peptide, periostin, and galectin-3 as serum biomarkers enhances risk stratification and sensitivity in detection of cardiac disease in patients with systemic sclerosis. However, before implementation in routine care, further prospective studies must refine biomarker sensitivity, specificity, and accuracy together with optimizing detection strategies and establishing clinical protocols for integration.

Differential impacts of social isolation and enriched environment on multi-sensory brain-wide functionality and network segregation

Correction: Identification of a disulfide bridge important for transport function of SNAT4 neutral amino acid transporter

PCSK9 drives sterol-dependent metastatic organ choice in pancreatic cancer

Non-equilibrium anti-Stokes Raman spectroscopy for investigating Higgs modes in superconductors

Abstract Even before its role in electroweak symmetry breaking, the Anderson-Higgs mechanism was introduced to explain the Meissner effect in superconductors. Spontaneous symmetry-breaking yields massless phase modes representing the low-energy excitations of the Mexican-Hat potential. Only in superconductors the phase mode is shifted towards higher energies owing to the gauge field of the charged condensate. This results in a low-energy excitation spectrum governed by the Higgs mode. Consequently, the Bardeen-Cooper-Schrieffer-like Meissner effect signifies a macroscopic quantum condensate in which a photon acquires mass, representing a one-to-one analogy to high-energy physics. We report on an innovative spectroscopic technique to study symmetries and energies of the Higgs modes in the high-temperature superconductor Bi2Sr2CaCu2O8 after a soft quench of the Mexican-Hat potential. Population inversion induced by an initial laser pulse leads to an additional anti-Stokes Raman-scattering signal, which is consistent with polarization-dependent Higgs modes. Within Ginzburg-Landau theory, the Higgs-mode energy is connected to the Cooper-pair coherence length. Within a Bardeen-Cooper-Schrieffer weak-coupling model we develop a quantitative and coherent description of single-particle and two-particle channels. This opens the avenue for Higgs Spectroscopy in quantum condensates and provides a unique pathway to control and explore Higgs physics.