Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of elevated atmospheric CO₂ concentration on symbiotic N₂ fixation and availability of nitrogen in grassland ecosystems

Gross rates of nitrogen (N) mineralisation were examined in grass¬ land soils exposed to ambient (36 Pa) and elevated (60 Pa) atmospheric CO2 partial pressure (pCO^) for seven years in the Swiss Free Air Carbon Diox¬ ide Enrichment (FACE) experiment. It was hypothesized that the increased translocation of photoassimilates below-ground at elevated pC02 would lead to a temporary increase in immobilisation of N due to an excess supply of energy to the roots. Intact soil cores were sampled from Lolium perenne and Trifolium repens swards in May and September, 2000. The rates of gross N mineralisation (to) and NH4 consumption (c) were determined us¬ ing 15N isotopic dilution during a 51-hour period of incubation. The rate of N immobilisation was estimated either as the difference between to and the net rate of N mineralisation after 51 hours or as the amount of 15N released from the microbial biomass after chloroform fumigation. Soil samples from both swards showed that the rates of gross N mineralisation and NH4 con¬ sumption and the portion of microbial N and 15N released by the chloroform fumigation did not change significantly under elevated pC02Gross rates of N mineralisation, NH4 consumption and microbial 15N did not differ sig¬ nificantly between the two swards. A considerably larger amount of NO^" was recovered at the end of incubation in the soils taken from the T. repens swards compared to soils taken from the L. perenne swards. Ten percent of the added 15N were recovered in the roots in the cores sampled under L perenne, while only 5 % were recovered in the cores sampled under T. repens. These results show that the calculation of N immobilisation from gross and net rates of mineralisation in soils with a high root biomass does not reflect the actual immobilisation of N in the microbial biomass. The results of this study suggest that the mineralisation and immobilisation of N, measured in grassland soils in short-term experiments, are not affected by long-term exposure to elevated pC02* Institute of Plant Sciences, ETH Zürich, 8092 Zürich, Switzerland. ^Imperial College London, Department of Agricultural Sciences, Wye, Ashford, Kent TN25 5AH, UK
Differential temporal release and lipoprotein loading in B. thetaiotaomicron bacterial extracellular vesicles

Abstract Bacterial extracellular vesicles (BEVs) contribute to stress responses, quorum sensing, biofilm formation and interspecies and interkingdom communication. However, the factors that regulate their release and heterogeneity are not well understood. We set out to investigate these factors in the common gut commensal Bacteroides thetaiotaomicron by studying BEV release throughout their growth cycle. Utilising a range of methods, we demonstrate that vesicles released at different stages of growth have significantly different composition, with early vesicles enriched in specifically released outer membrane vesicles (OMVs) containing a larger proportion of lipoproteins, while late phase BEVs primarily contain lytic vesicles with enrichment of cytoplasmic proteins. Furthermore, we demonstrate that lipoproteins containing a negatively charged signal peptide are preferentially incorporated in OMVs. We use this observation to predict all Bacteroides thetaiotaomicron OMV enriched lipoproteins and analyse their function. Overall, our findings highlight the need to understand media composition and BEV release dynamics prior to functional characterisation and define the theoretical functional capacity of Bacteroides thetaiotaomicron OMVs.
Development and validation of multicentre study on novel Artificial Intelligence-based Cardiovascular Risk Score (AICVD)

Objective Cardiovascular diseases (CVD) are one of the most prevalent diseases in India amounting for nearly 30% of total deaths. A dearth of research on CVD risk scores in Indian population, limited performance of conventional risk scores and inability to reproduce the initial accuracies in randomised clinical trials has led to this study on large-scale patient data. The objective is to develop an Artificial Intelligence-based Risk Score (AICVD) to predict CVD event (eg, acute myocardial infarction/acute coronary syndrome) in the next 10 years and compare the model with the Framingham Heart Risk Score (FHRS) and QRisk3. Methods Our study included 31 599 participants aged 18–91 years from 2009 to 2018 in six Apollo Hospitals in India. A multistep risk factors selection process using Spearman correlation coefficient and propensity score matching yielded 21 risk factors. A deep learning hazards model was built on risk factors to predict event occurrence (classification) and time to event (hazards model) using multilayered neural network. Further, the model was validated with independent retrospective cohorts of participants from India and the Netherlands and compared with FHRS and QRisk3. Results The deep learning hazards model had a good performance (area under the curve (AUC) 0.853). Validation and comparative results showed AUCs between 0.84 and 0.92 with better positive likelihood ratio (AICVD −6.16 to FHRS −2.24 and QRisk3 −1.16) and accuracy (AICVD −80.15% to FHRS 59.71% and QRisk3 51.57%). In the Netherlands cohort, AICVD also outperformed the Framingham Heart Risk Model (AUC −0.737 vs 0.707). Conclusions This study concludes that the novel AI-based CVD Risk Score has a higher predictive performance for cardiac events than conventional risk scores in Indian population. Trial registration number CTRI/2019/07/020471.
Rapid classification of a novel ALS-causing I149S variant in superoxide dismutase-1

Variants of the oxygen free radical scavenging enzyme superoxide dismutase-1 (SOD1) are associated with the neurodegenerative disease amyotrophic lateral sclerosis (ALS). These variants occur in roughly 20% of familial ALS cases, and 1% of sporadic ALS cases. Here, we identified a novel SOD1 variant in a patient in their 50s who presented with movement deficiencies and neuropsychiatric features. The variant was heterozygous and resulted in the isoleucine at position 149 being substituted with a serine (I149S). In silico analysis predicted the variant to be destabilising to the SOD1 protein structure. Expression of the SOD1 I149S variant with a C-terminal EGFP tag in neuronal-like NSC-34 cells resulted in extensive inclusion formation and reduced cell viability. Immunoblotting revealed that the intramolecular disulphide between Cys57 and Cys146 was fully reduced for SOD1 I149S . Furthermore, SOD1 I149S was highly susceptible to proteolytic digestion, suggesting a large degree of instability to the protein fold. Finally, fluorescence correlation spectroscopy and native-PAGE of cell lysates showed that SOD1 I149S was monomeric in solution in comparison to the dimeric SOD1 WT . This experimental data was obtained within 3 months and resulted in the rapid re-classification of the variant from a variant of unknown significance to a clinically actionable likely pathogenic variant.
Noxious stimulation induces self-protective behaviour in bumblebees

Self-grooming directed towards a noxiously-stimulated body part is one indicator that an animal may feel pain. In insects, the lack of evidence for such behaviour has been widely argued to reflect the absence of pain experiences. Here, we tested whether bumblebees (Bombus terrestris) selectively groom one of their antennae that was touched with a noxiously-heated (65 □C) probe. In the first two minutes after being touched with the noxiously-heated probe, bees groomed their touched antenna a) more than their untouched antenna, b) more than bees that were touched on the antenna with an unheated probe, and c) more than control (untouched) bees groomed either of their antennae. Our results clearly show that bumblebees can direct grooming towards a site of noxious stimulation. Our findings thus refute arguments that claim that insects do not feel pain because of their lack of displaying this behaviour.
Mouse Auditory Cortex Undergoes Asynchronous Maturation in the Right and Left Hemispheres

Despite the significance of lateralized auditory processing in human cognition, there are limited studies in animal models exploring the developmental mechanisms of this cortical specialization. Here, we find that cellular and network signs of maturity in the Auditory Cortex (ACx) appear earlier in the right hemisphere in male mice. We further demonstrate that persistent, experience dependent map reorganization is confined to the hemisphere that is actively maturing and can be differentially engaged by temporally limited manipulations of the sensory environment. Our data suggests that differential timing in hemisphere development could lead to lateralized auditory functioning.
The blobulator: a webtool for identification and visual exploration of hydrophobic modularity in protein sequences

Motivation Clusters of hydrophobic residues are known to promote structured protein stability and drive protein aggregation. Recent work has shown that identifying contiguous hydrophobic residue clusters (termed “blobs”) has proven useful in both intrinsically disordered protein (IDP) simulation and human genome studies. However, a graphical interface was unavailable. Results Here, we present the blobulator: an interactive and intuitive web interface to detect intrinsic modularity in any protein sequence based on hydrophobicity. We demonstrate three use cases of the blobulator and show how identifying blobs with biologically relevant parameters provides useful information about a globular protein, two orthologous membrane proteins, and an IDP. Other potential applications are discussed, including: predicting protein segments with critical roles in tertiary interactions, providing a definition of local order and disorder with clear edges, and aiding in predicting protein features from sequence. Availability The blobulator GUI can be found at www.blobulator. branniganlab.org, and the source code with pip installable command line tool can be found on GitHub at www.GitHub. com/BranniganLab/blobulator.
A Distributed Computing Solution for Privacy-Preserving Genome-Wide Association Studies

Breakthroughs in sequencing technologies led to an exponential growth of genomic data, providing unprecedented biological in-sights and new therapeutic applications. However, analyzing such large amounts of sensitive data raises key concerns regarding data privacy, specifically when the information is outsourced to third-party infrastructures for data storage and processing (e.g., cloud computing). Current solutions for data privacy protection resort to centralized designs or cryptographic primitives that impose considerable computational overheads, limiting their applicability to large-scale genomic analysis. We introduce Gyosa, a secure and privacy-preserving distributed genomic analysis solution. Unlike in previous work, Gyosa follows a distributed processing design that enables handling larger amounts of genomic data in a scalable and efficient fashion. Further, by leveraging trusted execution environments (TEEs), namely Intel SGX, Gyosa allows users to confidentially delegate their GWAS analysis to untrusted third-party infrastructures. To overcome the memory limitations of SGX, we implement a computation partitioning scheme within Gyosa. This scheme reduces the number of operations done inside the TEEs while safeguarding the users’ genomic data privacy. By integrating this security scheme in Glow, Gyosa provides a secure and distributed environment that facilitates diverse GWAS studies. The experimental evaluation validates the applicability and scalability of Gyosa, reinforcing its ability to provide enhanced security guarantees. Further, the results show that, by distributing GWASes computations, one can achieve a practical and usable privacy-preserving solution.
Unraveling principles of thermodynamics for genome-scale metabolic networks using graph neural networks

The fundamental laws of thermodynamics determine the feasibility of all natural processes including metabolism. Although several algorithms have been developed to predict the most important thermodynamic parameter, the standard Gibbs free energy, for metabolic reactions and metabolites, their application to genome-scale metabolic networks (GEMs) with thousands of metabolites and reactions is still limited. Here, we develop a graph neural network (GNN)- based model dGbyG for predicting Gibbs energy for metabolites and metabolic reactions which outperforms all existing methods in accuracy, versatility, robustness, and generalization ability. By applying dGbyG to the human GEM, Recon3D, we identify a critical subset of reactions with substantial negative values of the standard Gibbs free energy change, which we name thermodynamic driver reactions. These reactions exhibit distinctive network topological characteristics akin to driver nodes defined in control theory and remarkable heterogeneity in enzyme abundance, implying evolutionary constraints on the selection of thermodynamic parameters of metabolic networks. We also develop a thermodynamics-based flux balance analysis (TFBA) approach to integrate reaction thermodynamics with GEMs to curate these models. Our work not only transcends the augmentation of accessible thermodynamic data to facilitate an enriched understanding of metabolism, but also enables refinement of metabolic reconstructions from a thermodynamic perspective, thereby underscoring the critical role of thermodynamics in the accurate modeling of biological systems.
Forecasting EEG time series with WaveNet

Objective Forecasting electroencephalography (EEG) signals, i.e., estimating future values of the time series based on the past ones, is essential in many real-time EEG-based applications, such as brain– computer interfaces and closed-loop brain stimulation. As these applications are becoming more and more common, the importance of a good prediction model has increased. Previously, mainly the autoregressive model (AR) has been employed for this task — however, its prediction accuracy tends to fade quickly as multiple steps are predicted. We aim to improve on this by applying deep learning to make robust long-range forecasts. Methods We applied the deep neural network model WaveNet to forecast resting-state EEG in theta- (4–7.5 Hz) and alpha-frequency (8–13 Hz) bands. We also compared WaveNet to the AR model, which has previously been widely used in real-time EEG applications. Results WaveNet reliably forecasted EEG signals in both theta and alpha frequencies. It outperformed the AR model in estimating the signal amplitude and phase. Conclusion We demonstrate for the first time that deep learning can be utilised to forecast resting-state EEG time series over 100 ms ahead. Significance In the future, the developed model can enhance the real-time estimation of brain states in brain–computer interfaces and brain stimulation protocols. It may also be useful for answering neuroscientific questions and for diagnostic purposes.
Liming pasture soils in the Amazon region promotes low-affinity methane oxidation by type I and II methanotrophs

In the Amazon Forest region, cattle pastures are the main land use subsequent to deforestation. This land-use change affects the soil microbial community and methane fluxes, shifting the soil from a methane sink to a source. Soil physical and chemical attributes are changed due to slash-and-burn processes, including an increased soil pH after forest-to-pasture conversion. Without amendments, the pasture soils can become acidic again resulting in many cases in soil degradation. Liming is a standard management practice to increase soil pH while decreasing Al3+ availability. Liming is important to recover these degraded lands and increase soil fertility, but its impact on soil methane cycling in tropical soils is unknown. Here we investigated the role of soil pH on methane uptake under high concentrations of the gas. The top layer of forest (pH 4.1) and adjacent pasture soils (pH 4.8) from the Eastern Amazon were subjected to liming treatment (final pH 5.8) and incubated with ∼10,000 ppm of 13CH4 for 24 days to label DNA with 13C. Soil DNA was evaluated with Stable Isotopic Probing (SIP-DNA), methanotrophic abundance was quantified (pmoA gene), and high throughput sequencing of 16S rRNA was performed. Liming increased the methane uptake in both forest (∼10%) and pasture (∼25%) soils. Methanotrophs Methylocaldum sp. (type I) and Beijerinckaceae (type II) were identified to actively incorporate carbon from methane in limed pasture soils. In limed forest soils, Nitrososphaeraceae, Lysobacter sp. , and Acidothermus sp. were identified as 13C-enriched taxa. The enrichment of the archaeal family Nitrososphaeraceae, known as ammonia oxidizers, is correlated with an increase of ammonia monooxygenase genes, which code for an enzyme complex with wide substrate specificity that can also perform methane oxidation. In conclusion, liming Amazonian pasture soils not only contributes to the fertility and recovery of degraded areas but also has the potential to improve the oxidation of methane at high concentrations of this gas.
Assessing the relationship between neural entrainment and altered states of consciousness induced by electronic music

In electronic music events, the driving four-on-the-floor music appears pivotal for inducing altered states of consciousness (ASCs). While various physiological mechanisms link repetitive auditory stimuli to ASCs, entrainment—a brainwave synchronization through periodic external stimuli— has garnered primary focus. However, there are no studies systematically exploring the relationship between entrainment and ASCs. In the present study, we depart from the finding that entrainment to auditory stimuli peaks for stimulation rates around 2 Hz compared to others. Twenty participants listened to six one-minute electronic music excerpts at different tempos (1.65 Hz, 2.25 Hz, and 2.85 Hz). For each excerpt, they performed cognitive tasks and reported phenomenological experiences related to ASCs through questionnaires. Brain activity was recorded with electroencephalography to assess whether a modulation in entrainment by the beat of electronic music affected objective and subjective proxies of ASCs. Our results revealed a tempo-driven entrainment modulation, peaking at 1.65 Hz. Similarly, participants’ experience of unity during listening to the music was higher for the excerpts at 1.65 Hz, yet no relationship with entrainment was found. Critically, a correlation was found between entrainment and participants’ reaction time. Further studies are granted to explore how individual traits, such as musical training, modulate the relationship.
Changes in Northern Hemisphere Winter Storm Tracks under the Background of Arctic Amplification

AbstractAn interdecadal weakening in the North Atlantic storm track (NAST) and a poleward shift of the North Pacific storm track (NPST) are found during October–March for the period 1979–2015. A significant warming of surface air temperature (Ts) over northeastern North America and a La Nina–like change in the North Pacific under the background of Arctic amplification are found to be the contributors to the observed changes in the NAST and the NPST, respectively, via modulation of local baroclinicity. The interdecadal change in baroclinic energy conversion is consistent with changes in storm tracks with an energy loss from eddies to mean flow over the North Atlantic and an energy gain over the North Pacific. The analysis of simulations from the Community Earth System Model Large Ensemble project, although with some biases in storm-track and Ts simulations, supports the observed relationship between the NAST and Ts over northeastern North America, as well as the link between the NPST and El Nino–Southern O.
Morphological Similarity of Channels: From Linear Erosional Features (Rill, Gully) to Alpine Rivers

The geometric characteristics of incised features such as channels, rills, ephemeral gully, gully, represent the erosional transport regime and the fluvial dynamic equilibrium, and thus it is critical for the understanding of the long‐term evolution of natural, agricultural, and anthropogenic landscapes. This paper examines the morphological similarity of channelized erosion in two different environments such as Alpine landscapes and cultivated hillslopes. The first dataset comprises six rivers in the Italian Alps, three in the Carnia region and three in the Dolomites, where erosion is mainly the effect of discharges with high sediment loads or landslides and debris flows. The agricultural areas dataset includes rills, ephemeral gullies, and gullies surveyed in literature. This research highlights that the eroded volume in Alpine rivers is in line with that of agricultural landscapes or badlands around the world. Dolomites rivers of colluvial origin, flowing on soils that are not particularly deep and subject to natural disaggregation, tend to behave similarly to ephemeral gullies. Contrarily, channels that exhibit evident alluvial morphologies and coarse grain sizes are more similar to gully erosion. At different spatial scales, the results demonstrated that length–volume equations calibrated on rills, ephemeral gullies, gullies and badlands, might be feasible also for Alpine channels. The research areas present soils and bedrock lithology that differs from those in literature, thus suggesting that the morphology of linear erosion is independent of the intrinsic soil characteristics. Differences emerged between Dolomites and Carnia rivers: this highlights the importance of taking into account in future analyses other forcing factors (e.g. climate) on land degradation processes. Copyright © 2017 John Wiley & Sons, Ltd.
Biotechnology and Bioengineering

Funding information National Key R&D Program of China, Grant/Award Number: 2017YFE0114300; National Natural Science Foundation of China, Grant/Award Number: 51622813 and 51878675; Science and Technology Planning Project of Guangdong Province, Grant/Award Number: 2017B020216006 and 2015A020215014 Abstract Interspecies interactions and phylogenetic distances were studied to reveal the underlying evolutionary adaptations of biofilms sourced from wastewater treatment processes. Based on 380 pairwise cocultures of 40 strains from two microbial aggregates (surface‐attached and mobile aggregates [flocs]) at two substrate concentrations (LB broth and 0.1× LB broth), interspecies interactions were explored using biofilm classification schemes. There was a strong source‐dependence of biofilm development formed by the monocultures, that is, a higher biofilm formation potential for strains from attached aggregates than for those from sludge flocs at both substrate concentrations. Interestingly, the results showed that total biofilm reduction was dominant in the dual‐species biofilm sourced from flocs in both LB broth (67.37%) and 0.1× LB broth (64.21%), indicating high interspecific competition in mobile aggregates and the independence of substrate concentrations. However, biofilm reduction was higher (33.68%) than induction (19.37%) for the biofilms formed by surface‐attached aggregates in LB broth, while the opposite trend was apparent in 0.1× LB broth, suggesting the occurrence of indeterministic processes for biofilm formation and important roles of substrate concentrations. In addition, the more closely related phylogenetic relationships of cocultures from mobile aggregates were consistent with higher competition compared with those from surface‐attached aggregates. Overall, the underlying evolutionary patterns of biofilms formed from mobile aggregates consistently followed the essence of the “Red Queen Hypothesis,” while biofilms developed from surface‐ attached aggregates were not deterministic. This study advanced our understanding of biofilm‐related treatment processes using the principles of microbial ecology.