Miracle-dz/UniFAR-FTUs huggingface dataset:
Vertical Excitation Energies and Lifetimes of the Two Lowest Singlet Excited States of Cytosine, 5-Aza-cytosine, and the Triazine Family: Quantum Mechanics–Molecular Mechanics Studies

A swarm of semi-classical quantum mechanics/molecular mechanics molecular-dynamics simulations where OM2/MNDO is combined with the Gromacs program for consideration of explicit water is performed, solving the time-dependent Schrödinger equation in each step of the trajectories together with the Tully’s fewest switches algorithm. Within this stochastic treatment, time dependent probabilities of the three lowest electronic states are determined. The fact that nucleobases are quickly deactivated is confirmed in the cytosine case where our best lifetime estimation is τ1=0.82 ps for the model with 100 water molecules with the SPCE force field and a time step of 0.1 fs. Lifetimes of the remaining molecules are visibly longer: 5-azacytosine, 2,4-diamino-1,3,5-triazine (DT), and 2,4,6-triamino-1,3,5-triazine (TT) molecules have an S1 → S0 de-excitation time of slightly above 10 ps. The lifetimes of the triazine family increases with the increasing number of exocyclic amino groups, that is, s-triazine < 2-amino-1,3,5-triazine < DT < TT. This can be explained by a higher mobility of the carbon-bonded hydrogen atoms in comparison with heavier amino groups since their movement is slowed down due to a substantially higher mass than hydrogen atoms, which can easier reach the out-of-plane positions required in the conical intersection structures. Moreover, bulkier NH2 ligands suffer due to greater friction caused by the surrounding water environment. These mechanical aspects caused a change in the explored lifetime dependences in comparison with our previous gas-phase study.
TURBULENT LOSS OF RING-CURRENT PROTONS.

Abstract : Ring current protons (<50 keV), which are unaffected by ion cyclotron waves outside the plasmapause, undergo strong turbulent diffusion just inside the plasmapause. Lifetimes from ion cyclotron turbulence are predicted to be of the order of one hour, as observed by Frank for 3 < or = L < or = 5. During the main phase of a geomagnetic storm, the protons rapidly diffuse across the plasmapause (probably at the Bohm rate), and are lost before reaching the noon meridian, giving rise to the asymmetric part of the ring current. During the recovery phase the ring current decays on a time scale of a day or less as the turbulent region moves outward with the expansion of the plasmapause. Further decay takes place on a charge exchange time scale. One consequence of the dissipation of ring current energy at the plasmapause should be the formation of mid-latitude red arcs, probably by the conversion of this energy into heat as the ion cyclotron waves are absorbed by electrons. (Author)
Within-Subject Variability and the Influence of Exercise Training History on the Resting Plasma Metabolome in Men.

This study investigated within-subject variability in the circulating metabolome under controlled conditions, and whether divergent exercise training backgrounds were associated with alterations in the circulating metabolome assessed in resting samples. Thirty-seven men comprising of endurance athletes (END; body mass, 71.0 ± 6.8 kg; fat-free mass index, 16.9 ± 1.1 kg/m2), strength athletes (STR; 94.5 ± 8.8 kg; 23.0 ± 1.8 kg/m2), and recreationally active controls (CON; 77.6 ± 7.7 kg; 18.1 ± 1.0 kg/m2) provided blood samples after an overnight fast on two separate occasions controlled for time of day of sampling, recent dietary intake, time since last meal, and time since last exercise training session. A targeted profile of metabolites, performed using liquid chromatography and mass spectrometry on plasma samples, identified 166 individual metabolites and metabolite features, which were analyzed with intraclass correlation coefficients, a multilevel principal component analysis, and univariate t tests adjusted for multiple comparisons. The median intraclass correlation coefficient was . 49, with 46 metabolites displaying good reliability and 31 metabolites displaying excellent reliability. No difference in the abundance of any individual metabolite was identified within groups when compared between visits, but a combined total of 44 metabolites were significantly different (false discovery rate <0.05) between groups (END vs. CON, 42 metabolites; STR vs. CON, 10 metabolites; and END vs. STR, five metabolites). Under similar measurement conditions, the reliability of resting plasma metabolite concentrations varies largely at the level of individual metabolites with ∼48% of metabolites displaying good-to-excellent reliability. However, a history of exercise training was associated with alterations in the abundance of ∼28% of metabolites in the targeted profile employed in this study.
A Blue-Enriched Light Intervention Counteracts the Alertness Decrement Among Mine Workers on Extended 12-Hour Night Shift Periods

Exposing workers who perform extended night shifts for prolonged periods of time to blue-enriched white light can alleviate the decrement in nocturnal alertness. Objective The aim of the study is to assess whether a blue-enriched light intervention improves nocturnal alertness and daytime sleep of night workers. Methods Thirteen miners performing 12-hour night shifts for 12 consecutive nights were exposed to a baseline and a blue-enriched light condition. All subjects wore an actigraph and completed a Psychomotor Vigilance Task at the beginning and at the end of each shift. Data were analyzed with linear mixed models. Results In the blue-enriched light condition, the daily increase in median reaction time (RT), mean RT, slowest 10% of RT, and fastest 10% of RT was lower than that observed in the baseline condition between day 1 and 12 (P ≤ 0.05). Conclusions The addition of blue-enriched light during a long period of extended night shifts counteracts most of the daily decline in nocturnal alertness observed in the standard lighting condition, irrespectively of sleep duration and sleep efficiency.
SWATH-MS-based proteogenomic analysis reveals the involvement of alternative splicing in poplar upon lead stress

Alternative splicing (AS) regulates gene expression and increases proteomic diversity for the fine tuning of stress responses in plants, but the exact mechanism through which AS functions in plant stress responses is not thoroughly understood. Here, we investigated how AS functions in poplar (Populus trichocarpa), a popular plant for bioremediation, in response to lead (Pb) stress. Using a proteogenomic analysis, we determine that Pb stress induced alterations in AS patterns that are characterized by an increased use of nonconventional splice sites and a higher abundance of Pb-responsive splicing factors (SFs) associated with Pb-responsive transcription factors. A strong Pb(II)-inducible chaperone protein, PtHSP70, that undergoes AS was further characterized. Overexpression of its two spliced isoforms, PtHSP70-AS1 and PtHSP70-AS2, in poplar and Arabidopsis significantly enhances the tolerance to Pb. Further characterization shows that both isoforms can directly bind to Pb(II), and PtHSP70-AS2 exhibits 10-fold higher binding capacities and a greater increase in expression under Pb stress, thereby reducing cellular toxicity through Pb(II) extrusion and conferring Pb tolerance. AS of PtHSP70 is found to be regulated by PtU1-70K, a Pb(II)-inducible core SF involved in 5′-splice site recognition. Because the same splicing pattern is also found in HSP70 orthologs in other plant species, AS of HSP70 may be a common regulatory mechanism to cope with Pb(II) toxicity. Overall, we have revealed a novel post-transcriptional machinery that mediates heavy metal tolerance in diverse plant species. Our findings offer new molecular targets and bioengineering strategies for phytoremediation and provide new insight for future directions in AS research.
Measurement of the Muon Beam Properties and Muon Neutrino Inclusive Charged-Current Cross Section in an Accelerator-produced Neutrino Experiment

In this thesis, we report two measurements: a measurement of the beam properties and a measurement of the ⌫μ-Fe CC inclusive cross section in the T2K neutrino oscillation experiment. In order to accomplish a precise measurement of the neutrino oscillation parameters and a search for the unknown parameter CP , a good control of the neutrino beam and understanding the neutrino-nucleus interaction mechanism are essential in T2K. We first describe the measurements of the direction and intensity of the muon beam, and the absolute muon flux to monitor the neutrino beam. The T2K muon monitor was installed to measure the direction and stability of the muon beam which is produced together with the muon neutrino beam. The result of the measurement of the muon beam profile center for the entire run period is (X,Y) = (0.0 ± 2.3, 1.0 ± 2.3) cm, and its root mean square (RMS) of the beam-by-beam fluctuation is (X,Y) = (1.0, 1.6) cm. The result of measurement of the total collected charge for 250 (205) kA horn operation is 32.5 (21.7) nC/10 p.o. t. , and its RMS of the beam-by-beam fluctuation is 1.2% (0.7%). Accordingly, the muon beam direction is kept within 0.3 mrad with respect to the designed beam-axis for most of the span of beam operation, and the total collected charge is also kept stable with the RMS of 1%. In order to confirm our understanding of muon beam and neutrino beam, the absolute muon flux is measured with the emulsion detector with a precision of 3%, which is in good agreement with the prediction of our beam simultion. From these results, we ensure that the detector response of the muon monitor is well understood and the validity of the beam control by the muon monitor is confirmed. All the beam measurements have guaranteed good quality beam data for the neutrino oscillation measurements and our cross section measurement. Second, we report the measurement of the ⌫μ-Fe CC inclusive cross section in neutrino energy range of 1-3 GeV. In this measurement, we develop a new method to utilize a dependence of the neutrino energy on the o↵-axis angle in addition to the event topologies. The obtained cross sections are (1.1 GeV) = 1.10 ± 0.15 (10 cm/nucleon), (2.0 GeV) = 2.07±0.27 (10 cm/nucleon), and (3.3 GeV) = 2.29±0.45 (10 cm/nucleon), at mean energies of 1.1, 2.0, and 3.3 GeV. Our results are consistent with the past measurements and predictions by the neutrino event generators of NEUT and GENIE. The measurement of the energy dependent cross section using neutrino beams with di↵erent o↵-axis angles is the first attempt in the world. Our analysis also demonstrates the feasibility of the precise CC inclusive cross section measurement which could be useful for the neutrino oscillation experiment.
Integrating multimodal information in machine learning for classifying acute myocardial infarction

Objective. Prompt identification and recognization of myocardial ischemia/infarction (MI) is the most important goal in the management of acute coronary syndrome. The 12-lead electrocardiogram (ECG) is widely used as the initial screening tool for patients with chest pain but its diagnostic accuracy remains limited. There is early evidence that machine learning (ML) algorithms applied to ECG waveforms can improve performance. Most studies are designed to classify MI from healthy controls and thus are limited due to the lack of consideration of ECG abnormalities from other cardiac conditions, leading to false positives. Moreover, clinical information beyond ECG has not yet been well leveraged in existing ML models. Approach. The present study considered downstream clinical implementation scenarios in the initial model design by dichotomizing study recordings from a public large-scale ECG dataset into a MI class and a non-MI class with the inclusion of MI-confounding conditions. Two experiments were conducted to systematically investigate the impact of two important factors entrained in the modeling process, including the duration of ECG, and the value of multimodal information for model training. A novel multimodal deep learning architecture was proposed to learn joint features from both ECG and patient demographics. Main results. The multimodal model achieved better performance than the ECG-only model, with a mean area under the receiver operating characteristic curve of 92.1% and a mean accuracy of 87.4%, which is on par with existing studies despite the increased task difficulty due to the new class definition. By investigation of model explainability, it revealed the contribution of patient information in model performance and clinical concordance of the model’s attention with existing clinical insights. Significance. The findings in this study help guide the development of ML solutions for prompt MI detection and move the models one step closer to real-world clinical applications.
One-stop assembly of adherent 3D retinal organoids from hiPSCs based on 3D-printed derived PDMS microwell platform

The three-dimensional (3D) retinal organoids (ROs) derived from human induced pluripotent stem cells (hiPSCs), mimicking the growth and development of the human retina, is a promising model for investigating inherited retinal diseases in vitro. However, the efficient generation of homogenous ROs remains a challenge. Here we introduce a novel polydimethylsiloxane (PDMS) microwell platform containing 62 V-bottom micro-cavities for the ROs differentiation from hiPSCs. The uniform adherent 3D ROs could spontaneously form using neural retina (NR) induction. Our results showed that the complex of NR (expressing VSX2), ciliary margin (CM) (expressing RDH10), and retinal pigment epithelium (RPE) (expressing ZO-1, MITF, and RPE65) developed in the PDMS microwell after the differentiation. It is important to note that ROs in PDMS microwell platforms not only enable one-stop assembly but also maintain homogeneity and mature differentiation over a period of more than 25 weeks without the use of BMP4 and Matrigel. Retinal ganglion cells (expressing BRN3a), amacrine cells (expressing AP2a), horizontal cells (expressing PROX1 and AP2α), photoreceptor cells for cone (expressing S-opsin and L/M-opsin) and rod (expressing Rod opsin), bipolar cells (expressing VSX2 and PKCα), and Müller glial cells (expressing GS and Sox9) gradually emerged. Furthermore, we replaced fetal bovine serum with human platelet lysate and established a xeno-free culture workflow that facilitates clinical application. Thus, our PDMS microwell platform for one-stop assembly and long-term culture of ROs using a xeno-free workflow is favorable for retinal disease modeling, drug screening, and manufacturing ROs for clinical translation.
Bayesian Inference for Brain Source Imaging with Joint Estimation of Structured Low-rank Noise

The inverse problem in brain source imaging is the reconstruction of brain activity from non-invasive recordings of electroencephalography (EEG) and magnetoencephalography (MEG). One key challenge is the efficient recovery of sparse brain activity when the data is corrupted by structured noise that is low-rank noise. This is often the case when there are a few active sources of environmental noise and the MEG/EEG sensor noise is highly correlated. In this paper, we propose a novel robust empirical Bayesian framework which provides us a tractable algorithm for jointly estimating a low-rank noise covariance and brain source activity. Specifically, we use a factor analysis model for the structured noise, and infer a sparse set of variance parameters for source activity, while performing Variational Bayesian inference for the noise. One key aspect of this algorithm is that it does not require any additional baseline measurements to estimate the noise covariance from the sensor data. We perform exhaustive experiments on both simulated and real datasets. Our algorithm achieves superior performance as compared to several existing benchmark algorithms.
Psidium guajava derived carbon nanoparticles: A promising red emissive cellular bioimaging agent

We report a simple, cost-effective, microwave-assisted green synthesis route of red-emitting fluorescence carbon nanoparticles (CNPs) using Psidium guajava (Guava leaves). The synthesis of CNPs is a simple, affordable, and rapid method of producing carbon nanoparticles. The CNPs were characterized by various spectroscopic and microscopic techniques. Atomic force microscopy studies showed that the average size of CNPs is approximately 50 nm. The CNPs exhibited excellent photoluminescence properties with a maximum emission at 677 nm, making them suitable for bioimaging applications. The Ionic, photostability, and thermal stability of CNPs were also checked to understand their robustness. Retinal pigment epithelium (RPE) cells were exposed to these nanoparticles and showed very efficient uptake, some fraction of it also getting targeted to the nucleus, indicating that CNPs are non-toxic and biocompatible for future biological experiments. The results indicate that guava leaves can be a promising source for the synthesis of red emissive CNPs through the very simple method of synthesis and with bioimaging applications.
Learning Perturbation-specific Cell Representations for Prediction of Transcriptional Response across Cellular Contexts

High-throughput screens (HTS) are widely utilized to profile transcriptional states across multiple cell types and perturbations, and are often the first step on the bridge to the patient. However, their representative capacity to encompass all the cellular contexts encountered in a patient is limited. Thus, we present PerturbX, a novel deep learning model that leverages the rich information obtained from HTS to predict transcriptional responses to chemical or genetic perturbations in unobserved cellular contexts, and demonstrate its effectiveness in an experimental setting. Further-more, we show that the model is able to uncover interpretable genetic signatures associated with the predicted response, which can ultimately be translated into the clinical setting.
Hepatic conversion of acetyl-CoA to acetate plays crucial roles in energy stress

Accumulating evidence indicates that acetate is increased under energy stress conditions such as those that occur in diabetes mellitus and prolonged starvation. However, how and where acetate is produced and the nature of its biological significance are largely unknown. We observed overproduction of acetate to concentrations comparable to those of ketone bodies in patients and mice with diabetes or starvation. Mechanistically, ACOT12 and ACOT8 are dramatically upregulated in the liver to convert free fatty acid-derived acetyl-CoA to acetate and CoA. This conversion not only provides a large amount of acetate, which preferentially fuels the brain rather than muscle, but also recycles CoA, which is required for sustained fatty acid oxidation and ketogenesis. We suggest that acetate is an emerging novel ‘ketone body’ that may be used as a parameter to evaluate the progression of energy stress.
Environmental variables and species traits as drivers of wild bee pollination in intensive agroecosystems -a metabarcoding approach

Wild bees are known to be efficient pollinators of wild plants and cultivated crops and they are essential ecosystem service providers. However, wild bee populations have been suffering from significant declines in the last decades mainly due to the use of agrochemicals. Within this framework, we aimed to characterize wild bees pollination spectrum (i.e. the community of pollinated flowering plants) in intensive agroecosystems, and describe the environmental variables and wild bee species traits influencing the pollination. To do this, we conducted metabarcoding analyses of pollen loads from wild bees collected in sunflower crops in the French region of Nouvelle-Aquitaine. Our study revealed that wild bees visited flowering plants corresponding to 231 different Operational Taxonomic Units, classified in 38 families of which Asteraceae, Brassicaceae and Apiaceae were the most visited and more than 90% of the visited taxa turned out to be wild flowers. We also analysed the potential effect of environmental variables and wild bee species traits in governing their choice of pollinated plants. The community composition of pollinated plants varied depending on the flowering stages of the sunflower and the farming system. Our results also show that pollination niche breadth (alpha diversity) varied depending on the flowering stages of the sunflower but was not different between organic and conventional farming systems. Regarding wild bee species traits, the community composition of pollinated plants varied in relation to wild bees body sizes and, sociality levels. Our results are consistent with previous studies, suggesting that solitary bees are more specialists when it comes to flower selection than social bees, which are more generalist. The metabarcoding of pollen loads enabled us to draw a global picture of plant-wild bee interactions in an intensive agroecosystem. Our findings support the hypothesis that a higher diversity of weeds may increase wild bee diversity in intensive agroecosystems.
Reticular Adhesion Formation is Mediated by Flat Clathrin Lattices and Opposed by Fibrillar Adhesions

Reticular adhesions (RAs) consist of integrin αvβ5 and harbor flat clathrin lattices (FCLs), long-lasting structures with similar molecular composition to clathrin mediated endocytosis (CME) carriers. Why FCLs and RAs colocalize is not known. Here, we show that FCLs assemble RAs in a process controlled by fibronectin (FN) and its receptor, integrin αvβ5. We observed that cells on FN-rich matrices displayed fewer FCLs and RAs. CME machinery inhibition abolished RAs and live-cell imaging showed that RA establishment requires FCL co-assembly. The inhibitory activity of FN was mediated by the activation of integrin α5β1 at Tensin1-positive fibrillar adhesions. Conventionally, endocytosis disassembles cellular adhesions by internalization of their components. Our results present a novel paradigm in the relationship between these two processes by showing that endocytic proteins can actively function in the assembly of cell adhesions. Furthermore, we show this novel adhesion assembly mechanism is coupled to cell migration via a unique crosstalk between cell matrix adhesions.
An Arm-to-Disarm Strategy to Overcome Phenotypic AMR in Mycobacterium tuberculosis

Most front-line tuberculosis drugs are ineffective against hypoxic non-replicating drug-tolerant Mycobacterium tuberculosis (Mtb) contributing to phenotypic antimicrobial resistance (AMR). This is largely due to the poor permeability in the thick and waxy cell wall of persister cells, leading to diminished drug accumulation and reduced drug-target engagement. Here, using an “arm-to-disarm” prodrug approach, we demonstrate that non-replicating Mtb persisters can be sensitized to Moxifloxacin (MXF), a front-line TB drug. We design and develop a series of nitroheteroaryl MXF prodrugs that are substrates for bacterial nitroreductases (NTR), a class of enzymes that are over-expressed in hypoxic Mtb. Enzymatic activation involves electron-transfer to the nitroheteroaryl compound followed by protonation via water that contributes to the rapid cleavage rate of the protective group by NTR to produce the active drug. Phenotypic and genotypic data are fully consistent with MXF-driven lethality of the prodrug in Mtb with the protective group being a relatively innocuous bystander. The prodrug increased intracellular concentrations of MXF than MXF alone and is more lethal than MXF in non-replicating persisters. Hence, arming drugs to improve permeability, accumulation and drug-target engagement is a new therapeutic paradigm to disarm phenotypic AMR.