Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibiotic tolerance and persistence have distinct fitness trade-offs

Genetically susceptible bacteria can escape the action of bactericidal antibiotics through antibiotic tolerance or persistence. However, one major difference between the two phenomena is their distinct penetrance within an isogenic population. While with antibiotic persistence, susceptible and persister cells co-exist, antibiotic tolerance affects the entire bacterial population. Here, we show that antibiotic tolerance can be achieved in numerous non-specific ways in vitro and during infection. More importantly, we highlight that, due to their impact on the entire bacterial population, these tolerance-inducing conditions completely mask persistence and the action of its molecular determinants. Finally, we show that even though tolerant populations display a high survival rate under bactericidal drug treatment, this feature comes at the cost of having impaired proliferation during infection. In contrast, persistence is a risk-limiting strategy that allows bacteria to survive antibiotic treatment without reducing the ability of the population to colonize their host. Altogether, our data emphasise that the distinction between these phenomena is of utmost importance to improve the design of more efficient antibiotic therapies.
INTERACTION BETWEEN THE SUPERNOVA REMNANT HB 3 AND THE NEARBY STAR-FORMING REGION W3

We performed millimeter observations of CO lines toward the supernova remnant (SNR) HB 3. Substantial molecular gas around −45 km s−1 is detected in the conjunction region between the SNR HB 3 and the nearby W3 complex. This molecular gas is distributed along the radio continuum shell of the remnant. Furthermore, the shocked molecular gas indicated by line wing broadening features is also distributed along the radio shell and inside it. By both morphological correspondence and dynamical evidence, we confirm that the SNR HB 3 interacts with the −45 km s−1 molecular cloud (MC), in essence, with the nearby H ii region/MC complex W3. The redshifted line wing broadening features indicate that the remnant is located at the nearside of the MC. With this association, we could place the remnant at the same distance as the W3/W4 complex, which is 1.95 ± 0.04 kpc. The spatial distribution of aggregated young stellar object candidates shows a correlation with the shocked molecular strip associated with the remnant. We also find a binary clump of CO at (l = 132.°94, b = 1.°12) around −51.5 km s−1 inside the projected extent of the remnant, and it is associated with significant mid-infrared emission. The binary system also has a tail structure resembling the tidal tails of interacting galaxies. According to the analysis of CO emission lines, the larger clump in this binary system is about stable, and the smaller clump is significantly disturbed.
In vitro methods to ensure absence of residual undifferentiated human induced pluripotent stem cells intermingled in induced nephron progenitor cells

Cell therapies using human induced pluripotent stem cell (hiPSC)-derived nephron progenitor cells (NPCs) are expected to ameliorate acute kidney injury (AKI). However, using hiPSC-derived NPCs clinically is a challenge because hiPSCs themselves are tumorigenic. LIN28A, ESRG, CNMD and SFRP2 transcripts have been used as a marker of residual hiPSCs for a variety of cell types undergoing clinical trials. In this study, by reanalyzing public databases, we found a baseline expression of LIN28A, ESRG, CNMD and SFRP2 in hiPSC-derived NPCs and several other cell types, suggesting LIN28A, ESRG, CNMD and SFRP2 are not always reliable markers for iPSC detection. As an alternative, we discovered a lncRNA marker gene, MIR302CHG, among many known and unknown iPSC markers, as highly differentially expressed between hiPSCs and NPCs, by RNA sequencing and quantitative RT-PCR (qRT-PCR) analyses. Using MIR302CHG as an hiPSC marker, we constructed two assay methods, a combination of magnetic bead-based enrichment and qRT-PCR and digital droplet PCR alone, to detect a small number of residual hiPSCs in NPC populations. The use of these in vitro assays could contribute to patient safety in treatments using hiPSC-derived cells.
Network diffusion of gender diversity on boards: A process of two-speed opposing forces

Network diffusion processes or how information spreads through networks have been widely examined in numerous disciplines such as epidemiology, physics, sociology, politics, or computer science. In this paper, we extend previous developments by considering a generalization of the diffusion by considering the possibility of differences in the speed of diffusion and reduction depending on the forces’ directions. In this situation, the differential speed of diffusion produces deviations from the standard solution around the average of the initial conditions in the network. In fact, this asymmetry gives rise to non-linear dynamics in which, contrary to the symmetric case, the final solution depends on the topology of the graph as well as on the distribution of the initial values. Counter-intuitively, less central nodes in the network are able to exert a higher influence on the final solution. This behavior applies also for different simulated networks such as random, small-world, and scale-free. We show an example of this kind of asymmetric diffusion process in a real case. To do so, we use a network of US Boards of Directors, where boards are the nodes and the directors working for more than one board, are the links. Changes in the proportion of women serving on each board are influenced by the gradient between adjacent boards. We also show that there is an asymmetry: the gradient is reduced at a slower (faster) rhythm if the board has less (more) women than neighboring boards. We are able to quantify the accumulated effect of this asymmetry from 2000 to 2015 in the overall proportion of women on boards, in a 4.7 percentage points (the proportion should have been an 14.61% instead of the observed 9.93% in 2015).
Vortices in a toroidal Bose-Einstein condensate with a rotating weak link

Motivated by a recent experiment [K.C. Wright et. al. Phys. Rev. Lett. 110, 025302 (2013)], we investigate deterministic discontinuous jumps between quantized circulation states in a toroidally trapped Bose-Einstein condensate. These phase slips are induced by vortex excitations created by a rotating weak link. We analyze influence of a localized condensate density depletion and atomic superflows, governed by the rotating barrier, on the energetic and dynamical stability of the vortices in the ring-shaped condensate. We simulate in a three-dimensional dissipative mean field model the dynamics of the condensate using parameters similar to the experimental conditions. Moreover, we consider the dynamics of the stirred condensate far beyond the experimentally explored region and reveal surprising manifestations of complex vortex dynamics.
Nanostructured Materials Based Optical and Electrochemical Detection of Amoxicillin Antibiotic.

The penicillin derivative amoxicillin (AMX) plays an important role in the treatment of various types of infections caused by bacteria. However, excessive use of AMX may have negative health effects. Therefore, it is of utmost importance to detect and quantify the AMX in pharmaceutical drugs, biological fluids, and environmental samples with high sensitivity. Hence, this review article provides valuable and up-to-date information on nanostructured materials-based optical and electrochemical sensors for the detection of AMX in various biological and chemical samples. The role of using different nanostructured materials on the performance of important optical sensors such as colorimetric sensors, fluorescence sensors, surface-enhanced Raman scattering sensors, chemiluminescence/electroluminescence sensors, optical immunosensors, optical-fiber sensors, and several important electrochemical sensors based on different electrode types have been discussed. Moreover, nanocomposites, polymer, and MXenes-based electrochemical sensors have also been discussed, where such materials are being used to further enhance the sensitivity of these sensors. Furthermore, nanocomposite-based photo-electrochemical sensors and the market availability of biosensors including AMX have also been discussed briefly. Finally, conclusion, challenges and future perspectives of the above-mentioned sensing techniques for the AMX detection is presented.
DEEP THERMAL INFRARED IMAGING OF HR 8799 bcde: NEW ATMOSPHERIC CONSTRAINTS AND LIMITS ON A FIFTH PLANET

We present new L′ (3.8 μm) and Brα (4.05 μm) data and reprocessed archival L′ data for the young, planet-hosting star HR 8799 obtained with Keck/NIRC2, VLT/NaCo, and Subaru/IRCS. We detect all four HR 8799 planets in each data set at a moderate to high signal-to-noise ratio (S/N ≳ 6–15). We fail to identify a fifth planet, “HR 8799 f,” at r < 15 AU at a 5σ confidence level: one suggestive, marginally significant residual at 0. ″2 is most likely a point-spread function artifact. Assuming companion ages of 30 Myr and the Baraffe planet cooling models, we rule out an HR 8799 f with a mass of 5 MJ (7 MJ), 7 MJ (10 MJ), or 12 MJ (13 MJ) at rproj ∼ 12 AU, 9 AU, and 5 AU, respectively. All four HR 8799 planets have red early T dwarf-like L′ − [4.05] colors, suggesting that their spectral energy distributions peak in between the L′ and M′ broadband filters. We find no statistically significant difference in HR 8799 cde's color. Atmosphere models assuming thick, patchy clouds appear to better match HR 8799 bcde's photometry than models assuming a uniform cloud layer. While non-equilibrium carbon chemistry is required to explain HR 8799 b and c's photometry/spectra, evidence for it from HR 8799 d and e's photometry is weaker. Future, deep-IR spectroscopy/spectrophotometry with the Gemini Planet Imager, SCExAO/CHARIS, and other facilities may clarify whether the planets are chemically similar or heterogeneous.
Holographic Noise in Interferometers

Arguments based on general principles of quantum mechanics suggest that a minimum length or time associated with Planck-scale unification may entail a new kind of observable uncertainty in the transverse position of macroscopically separated bodies. Transverse positions vary randomly about classical geodesics in space and time by about the geometric mean of the Planck scale and separation, on a timescale corresponding to their separation. An effective theory based on a Planck information flux limit, and normalized by the black hole entropy formula, is developed to predict measurable correlations, such as the statistical properties of noise in interferometer signals. A connection with holographic unification is illustrated by representing Matrix theory position operators with a Schr\"odinger wave equation, interpreted as a paraxial wave equation with a Planck frequency carrier. Solutions of this equation are used to derive formulas for the spectrum of beamsplitter position fluctuations and equivalent strain noise in a Michelson interferometer, determined by the Planck time, with no other parameters. The spectral amplitude of equivalent strain derived here is a factor of \sqrt{\pi} smaller than previously published estimates. Signals in two nearly-collocated interferometers are predicted to be highly correlated, a feature that may provide convincing evidence for or against this interpretation of holography.
Optic Flow Processing in Patients With Macular Degeneration

Purpose Optic flow processing was characterized in patients with macular degeneration (MD). Methods Twelve patients with dense bilateral scotomas and 12 age- and gender-matched control participants performed psychophysical experiments. Stimuli were dynamic random-dot kinematograms projected on a large screen. For each component of optic flow (translational, radial, and rotational), we estimated motion coherence discrimination thresholds in our participants using an adaptive Bayesian procedure. Results Thresholds for translational, rotational, and radial patterns were comparable between patients and their matched control participants. A negative correlation was observed in patients between the time since MD diagnosis and coherence thresholds for translational patterns. Conclusions Our results suggest that in patients with MD, selectivity to optic flow patterns is preserved.
Constructive completeness and non-discrete languages

We give an analysis and generalizations of some long-established constructive completeness results in terms of categorical logic and pre-sheaf and sheaf semantics. The purpose is in no small part conceptual and organizational: from a few basic ingredients arises a more unified picture connecting constructive completeness with respect to Tarski semantics, to the extent that it is available, with various completeness theorems in terms of presheaf and sheaf semantics (and thus with Kripke and Beth semantics). From this picture are obtained both ("reverse mathematical") equivalence results and new constructive completeness theorems; in particular, the basic set-up is flexible enough to obtain strong constructive completeness results for languages of arbitrary size and languages for which equality between the elements of the signature is not decidable.
Eight-Dimensional Polarization-Ring-Switching Modulation Formats

We propose two 8-dimensional (8D) modulation formats (8D-2048PRS-T1 and 8D-2048PRS-T2) with a spectral efficiency of 5.5 bit/4D-sym, where the 8 dimensions are obtained from two time slots and two polarizations. Both formats provide a higher tolerance to nonlinearity by selecting symbols with nonidentical states of polarization (SOPs) in two time slots. The performance of these novel 8D modulation formats is assessed in terms of the effective signal-to-noise ratio (SNR) and normalized generalized mutual information. 8D-2048PRS-T1 is more suitable for high SNRs, while 8D-2048PRS-T2 is shown to be more tolerant to nonlinearities. A sensitivity improvement of at least 0.25 dB is demonstrated by maximizing normalized generalized mutual information (NGMI). For a long-haul nonlinear optical fiber transmission system, the benefit of mitigating the nonlinearity is demonstrated and a reach increase of 6.7% (560 km) over time-domain hybrid four-dimensional two-amplitude eight-phase shift keying (TDH-4D-2A8PSK) is observed.
Exploring the Intrinsic Features of EEG Signals via Empirical Mode Decomposition for Depression Recognition

Depression is a severe psychiatric illness that causes emotional and cognitive impairment and has a considerable impact on patients’ thoughts, behaviors, feelings and well-being. Moreover, methods for recognizing and treating depression are lacking in clinical practice. Electroencephalogram (EEG) signals, which objectively reflect the internal workings of the brain, is a promising and objective tool for recognizing and diagnosing of depression and enhancing clinical effects. However, previous EEG feature extraction methods have not performed well when exploring the intrinsic characteristics of highly complex and nonstationary EEG signals. To address this issue, we propose a regularization parameter-based improved intrinsic feature extraction method of EEG signals via empirical mode decomposition (EMD), which mines the intrinsic patterns in EEG signals, for depression recognition. Furthermore, our method can effectively solve the problem that EMD fails to extract intrinsic features. In this method, we first select an appropriate regularization parameter to generate the regularization matrix. Next, we calculate the sum of the matrix products of the IMFs and the regularization matrix and leverage the inverse of this matrix to extract the intrinsic features. The classification results of our method on four EEG datasets reached 0.8750, 0.8850, 0.8485 and 0.7768, respectively. In addition, compared with the iEMD method, our method requires less computational costs. These results support our claim that our method can effectively strengthen the depression recognition performance, and our method outperforms state-of-the-art feature extraction approaches.
GA-Net: Guided Aggregation Net for End-To-End Stereo Matching

In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities. We propose two novel neural net layers, aimed at capturing local and the whole-image cost dependencies respectively. The first is a semi-global aggregation layer which is a differentiable approximation of the semi-global matching, the second is the local guided aggregation layer which follows a traditional cost filtering strategy to refine thin structures. These two layers can be used to replace the widely used 3D convolutional layer which is computationally costly and memory-consuming as it has cubic computational/memory complexity. In the experiments, we show that nets with a two-layer guided aggregation block easily outperform the state-of-the-art GC-Net which has nineteen 3D convolutional layers. We also train a deep guided aggregation network (GA-Net) which gets better accuracies than state-of-the-art methods on both Scene Flow dataset and KITTI benchmarks.
The Rheb GTPase promotes pheromone blindness via a TORC1-independent pathway in the phytopathogenic fungus Ustilago maydis

The target of the rapamycin (TOR) signaling pathway plays a negative role in controlling virulence in phytopathogenic fungi. However, the actual targets involved in virulence are currently unknown. Using the corn smut fungus Ustilago maydis, we tried to address the effects of the ectopic activation of TOR on virulence. We obtained gain-of-function mutations in the Rheb GTPase, one of the conserved TOR kinase regulators. We have found that unscheduled activation of Rheb resulted in the alteration of the proper localization of the pheromone receptor, Pra1, and thereby pheromone insensitivity. Since pheromone signaling triggers virulence in Ustilaginales, we believe that the Rheb-induced pheromone blindness was responsible for the associated lack of virulence. Strikingly, although these effects required the concourse of the Rsp5 ubiquitin ligase and the Art3 α-arrestin, the TOR kinase was not involved. Several eukaryotic organisms have shown that Rheb transmits environmental information through TOR-dependent and -independent pathways. Therefore, our results expand the range of signaling manners at which environmental conditions could impinge on the virulence of phytopathogenic fungi.
Fixed-point Localization for $\mathbb{RP}^{2m} \subset \mathbb{CP}^{2m}$

We derive a fixed-point formula for integrals on moduli spaces of stable maps to projective spaces of even dimension. This gives a formula for the equivariant open Gromov-Witten invariants of (RP^{2m},CP^{2m}) and the structure constants of the equivariant Fukaya A-infinity algebra of RP^2m in CP^{2m} with bulk deformations. The formula involves contributions from Givental's correlators for the closed theory and the descendent integrals of discs, and specializes to give a new expression for the Welschinger count of real rational curves in the plane passing through some real and conjugation invariant pairs of points.
Models for the clustering of far-infrared and submillimetre selected galaxies

We discuss and compare two alternative models for the two-point angular correlation function of galaxies detected through the submillimetre emission using the Herschel Space Observatory. The first, now-standard Halo Model, which represents the angular correlations as arising from one-halo and two-halo contributions, is flexible but complex and rather unwieldy. The second model is based on a much simpler approach: we incorporate a fitting function method to estimate the matter correlation function with approximate model of the bias inferred from the estimated redshift distribution to find the galaxy angular correlation function. We find that both models give a good account of the shape of the correlation functions obtained from published preliminary studies of the Herschel Multi-tiered Extragalactic Survey (HerMES) and the Herschel-Astrophysical Terahertz Large Area Survey (H-ATLAS) performed using Herschel, and yield consistent estimates of the minimum halo mass within which the submillimetre galaxies must reside. We note also that both models predict an inflection in the correlation function at intermediate angular scales, so the presence of the feature in the measured correlation function does not unambiguously indicate the presence of intra-halo correlations. The primary barrier to more detailed interpretation of these clustering measurements lies in the substantial uncertainty surrounding the redshift distribution of the sources.
Cardiac troponins – a paradigm for diagnostic biomarker identification and development

Abstract The introduction of cardiac troponins into clinical diagnostics has not only improved diagnostic pathways for myocardial infarction but also profoundly influenced the definition of myocardial infarction. The term troponin appeared in the literature almost 60 years ago, i.e. shortly after this journal was founded. The development of cardiac troponins from proteins involved in muscle contraction, which were in the focus of few specialized research groups from physiology and biochemistry, to one of the most frequently measured protein biomarkers in medicine is a paradigmatic success story which is also reflected in almost 300 publications on the topic in this journal. From the viewpoint of biomarker development the critical success factors were medical need, timely generation of medical evidence, and the rapid development of robust and precise laboratory assays.
Global models and predictions of plant diversity based on advanced machine learning techniques.

Despite the paramount role of plant diversity for ecosystem functioning, biogeochemical cycles, and human welfare, knowledge of its global distribution is still incomplete, hampering basic research and biodiversity conservation. Here, we used machine learning (random forests, extreme gradient boosting, and neural networks) and conventional statistical methods (generalized linear models and generalized additive models) to test environment-related hypotheses of broad-scale vascular plant diversity gradients and to model and predict species richness and phylogenetic richness worldwide. To this end, we used 830 regional plant inventories including c. 300 000 species and predictors of past and present environmental conditions. Machine learning showed a superior performance, explaining up to 80.9% of species richness and 83.3% of phylogenetic richness, illustrating the great potential of such techniques for disentangling complex and interacting associations between the environment and plant diversity. Current climate and environmental heterogeneity emerged as the primary drivers, while past environmental conditions left only small but detectable imprints on plant diversity. Finally, we combined predictions from multiple modeling techniques (ensemble predictions) to reveal global patterns and centers of plant diversity at multiple resolutions down to 7774 km2 . Our predictive maps provide accurate estimates of global plant diversity available at grain sizes relevant for conservation and macroecology.