Miracle-dz/UniFAR-FTUs huggingface dataset:
Profiling DNA Ligase Substrate Specificity with a Pacific Biosciences Single‐Molecule Real‐Time Sequencing Assay

DNA ligases catalyze the joining of breaks in nucleic acid backbones and are essential enzymes for in vivo genome replication and repair across all domains of life. These enzymes are also critically important to in vitro manipulation of DNA in applications such as cloning, sequencing, and molecular diagnostics. DNA ligases generally catalyze the formation of a phosphodiester bond between an adjacent 5′‐phosphate and 3′‐hydroxyl in DNA, but they exhibit different substrate structure preferences, sequence‐dependent biases in reaction kinetics, and variable tolerance for mismatched base pairs. Information on substrate structure and sequence specificity can inform both biological roles and molecular biology applications of these enzymes. Given the high complexity of DNA sequence space, testing DNA ligase substrate specificity on individual nucleic acid sequences in parallel rapidly becomes impractical when a large sequence space is investigated. Here, we describe methods for investigating DNA ligase sequence bias and mismatch discrimination using Pacific Biosciences Single‐Molecule Real‐Time (PacBio SMRT) sequencing technology. Through its rolling‐circle amplification methodology, SMRT sequencing can give multiple reads of the same insert. This feature permits high‐quality top‐ and bottom‐strand consensus sequences to be determined while preserving information on top‐bottom strand mismatches that can be obfuscated or lost when using other sequencing methods. Thus, PacBio SMRT sequencing is uniquely suited to measuring substrate bias and enzyme fidelity through multiplexing a diverse set of sequences in a single reaction. The protocols describe substrate synthesis, library preparation, and data analysis methods suitable for measuring fidelity and bias of DNA ligases. The methods are easily adapted to different nucleic acid substrate structures and can be used to characterize many enzymes under a variety of reaction conditions and sequence contexts in a rapid and high‐throughput manner. © 2023 New England Biolabs and The Authors. Current Protocols published by Wiley Periodicals LLC.
p16INK4A flow cytometry of exfoliated cervical cells: Its role in quantitative pathology and clinical diagnosis of squamous intraepithelial lesions

Abstract Background P16INK4A is a surrogate signature compensating for the specificity and/or sensitivity deficiencies of the human papillomavirus (HPV) DNA and Papanicolaou smear (Pap) co‐test for detecting high‐grade cervical squamous intraepithelial lesions or worse (HSIL+). However, traditional p16INK4A immunostaining is labour intensive and skill demanding, and subjective biases cannot be avoided. Herein, we created a high‐throughput, quantitative diagnostic device, p16INK4A flow cytometry (FCM) and assessed its performances in cervical cancer screening and prevention. Methods P16INK4A FCM was built upon a novel antibody clone and a series of positive and negative (p16INK4A‐knockout) standards. Since 2018, 24 100‐women (HPV‐positive/‐negative, Pap‐normal/‐abnormal) have been enrolled nationwide for two‐tier validation work. In cross‐sectional studies, age‐ and viral genotype‐dependent expression of p16INK4A was investigated, and optimal diagnostic parameter cut‐offs (using colposcopy and biopsy as a gold standard) were obtained. In cohort studies, the 2‐year prognostic values of p16INK4A were investigated with other risk factors by multivariate regression analyses in three cervicopathological conditions: HPV‐positive Pap‐normal, Pap‐abnormal biopsy‐negative and biopsy‐confirmed LSIL. Results P16INK4A FCM detected a minimal ratio of 0.01% positive cells. The p16INK4A‐positive ratio was 13.9 ± 1.8% among HPV‐negative NILM women and peaked at the ages of 40–49 years; after HPV infection, the ratio increased to 15.1 ± 1.6%, varying with the carcinogenesis of the viral genotype. Further increments were found in women with neoplastic lesions (HPV‐negative: 17.7 ± 5.0–21.4 ± 7.2%; HPV‐positive: 18.0 ± 5.2–20.0 ± 9.9%). Extremely low expression of p16INK4A was observed in women with HSILs. As the HPV‐combined double‐cut‐off‐ratio criterion was adopted, a Youden's index of 0.78 was obtained, which was significantly higher than that (0.72) of the HPV and Pap co‐test. The p16INK4A‐abnormal situation was an independent HSIL+ risk factor for 2‐year outcomes in all three cervicopathological conditions investigated (hazard ratios: 4.3–7.2). Conclusions FCM‐based p16INK4A quantification offers a better choice for conveniently and precisely monitoring the occurrence of HSIL+ and directing risk‐stratification‐based interventions.
Exact solutions of the field equations: twist-free pure radiation fields

This note is intended to give a rough survey of the results obtained in the study of twist-free pure radiation fields in general relativity theory. Here we are using the following Definition. A space-time (V4 of signature +2) is called a pure radiation field if it contains a distortion-free geodetic null congruence (a so-called ray congruence), and if it satisfies certain field equations which we will specify below (e.g. Einstein’s vacuum-field equations). A (null) congruence is called twist-free if it is hypersurface-orthogonal (or ‘normal’). The results listed below were obtained by introducing special (‘canonical’) co-ordinates adapted to the ray congruence. Detailed proofs were given by Robinson & Trautman (1962) and by Jordan, Kundt & Ehlers (1961) (see also Kundt 1961). For the sake of completeness we include in our survey the subclass of expanding fields, and make use of some formulae first obtained by Robinson & Trautman.
Exploration of California School Nurse perspectives on the impact of COVID-19.

OBJECTIVE To explore in a sample of school nurses (SN) in California the impact of the COVID-19 pandemic on school nurse health services, how school nurses mitigated the impact of COVID-19, and moral distress levels among school nurses. DESIGN AND METHODS Nineteen (N = 19) school nurses who work in K-12 schools in California, USA participated in a mixed-methods approach involving qualitative descriptive design, inductive content analysis, and descriptive statistics. Interviews were conducted in August and September 2021. RESULTS Five themes emerged: (1) role of the SN during the COVID-19 pandemic, (2) coordination with school administration, (3) COVID-19 related challenges and disruptions to care, (4) moral distress, and (5) coping during the pandemic. CONCLUSION The pandemic had a profound impact on school nurses. This study provides school nurse perspectives of the impact of COVID-19 on services they delivered, the unique skills of school nurses essential to mitigation strategies, and moral distress school nurses encountered during the pandemic. Understanding the important role school nurses had during the pandemic is paramount to fully contextualize the contributions they made within public health nursing practice and inform preparedness for future pandemics.
Cortical oscillations and interareal synchronization as a preparatory activity for postural response

Neural mechanisms of human standing are expected to be elucidated for preventing fallings. Postural response evoked by sudden external perturbation originates from various areas in the central nervous system. Recent studies have revealed that the corticospinal pathway is one of the key nodes for an appropriate postural response. The corticospinal pathway that mediates the early part of the electromyographic response is modulated with prediction before a perturbation occurs. Temporal prediction explicitly exhibiting an onset timing contributes to enhancing corticospinal excitability. However, how the cortical activities in the sensorimotor area with temporal prediction are processed before the corticospinal pathway enhancement remains unclear. In this study, using electroencephalography, we investigated how temporal prediction affects both neural oscillations and synchronization between sensorimotor and distal areas. Our results revealed that desynchronization of cortical oscillation at α‐ and β‐bands was observed in the sensorimotor and parietooccipital areas (Cz, CPz, Pz and POz), and those are nested in the phase at θ‐band frequency. Furthermore, a reduction in the interareal phase synchrony in the α‐band was induced after the timing cue for the perturbation onset. The phase synchrony at the low frequency can relay the temporal prediction among the distant areas and initiate the modulation of the local cortical activities. Such modulations contribute to the preparation for sensory processing and motor execution that are necessary for optimal responses.
Weaponising microbes for peace

There is much human disadvantage and unmet need in the world, including deficits in basic resources and services considered to be human rights, such as drinking water, sanitation and hygiene, healthy nutrition, access to basic healthcare, and a clean environment. Furthermore, there are substantive asymmetries in the distribution of key resources among peoples. These deficits and asymmetries can lead to local and regional crises among peoples competing for limited resources, which, in turn, can become sources of discontent and conflict. Such conflicts have the potential to escalate into regional wars and even lead to global instability. Ergo: in addition to moral and ethical imperatives to level up, to ensure that all peoples have basic resources and services essential for healthy living and to reduce inequalities, all nations have a self‐interest to pursue with determination all available avenues to promote peace through reducing sources of conflicts in the world. Microorganisms and pertinent microbial technologies have unique and exceptional abilities to provide, or contribute to the provision of, basic resources and services that are lacking in many parts of the world, and thereby address key deficits that might constitute sources of conflict. However, the deployment of such technologies to this end is seriously underexploited. Here, we highlight some of the key available and emerging technologies that demand greater consideration and exploitation in endeavours to eliminate unnecessary deprivations, enable healthy lives of all and remove preventable grounds for competition over limited resources that can escalate into conflicts in the world. We exhort central actors: microbiologists, funding agencies and philanthropic organisations, politicians worldwide and international governmental and non‐governmental organisations, to engage – in full partnership – with all relevant stakeholders, to ‘weaponise’ microbes and microbial technologies to fight resource deficits and asymmetries, in particular among the most vulnerable populations, and thereby create humanitarian conditions more conducive to harmony and peace.
Sample-Efficient Real-Time Planning with Curiosity Cross-Entropy Method and Contrastive Learning

Model-based reinforcement learning (MBRL) with real-time planning has shown great potential in locomotion and manipulation control tasks. However, the existing planning methods, such as the Cross-Entropy Method (CEM), do not scale well to complex high-dimensional environments. One of the key reasons for underperformance is the lack of exploration, as these planning methods only aim to maximize the cumulative extrinsic reward over the planning horizon. Furthermore, planning inside the compact latent space in the absence of observations makes it challenging to use curiosity-based intrinsic motivation. We propose Curiosity CEM (CCEM), an improved version of the CEM algorithm for encouraging exploration via curiosity. Our proposed method maximizes the sum of state-action $Q$ values over the planning horizon, in which these $Q$ values estimate the future extrinsic and intrinsic reward, hence encouraging to reach novel observations. In addition, our model uses contrastive representation learning to efficiently learn latent representations. Experiments on image-based continuous control tasks from the DeepMind Control suite show that CCEM is by a large margin more sample-efficient than previous MBRL algorithms and compares favorably with the best model-free RL methods.
Multi-Dimensional and Multi-Scale Modeling for Speech Separation Optimized by Discriminative Learning

Transformer has shown advanced performance in speech separation, benefiting from its ability to capture global features. However, capturing local features and channel information of audio sequences in speech separation is equally important. In this paper, we present a novel approach named Intra-SE-Conformer and Inter-Transformer (ISCIT) for speech separation. Specifically, we design a new network SE-Conformer that can model audio sequences in multiple dimensions and scales, and apply it to the dual-path speech separation framework. Furthermore, we propose Multi-Block Feature Aggregation to improve the separation effect by selectively utilizing information from the intermediate blocks of the separation network. Meanwhile, we propose a speaker similarity discriminative loss to optimize the speech separation model to address the problem of poor performance when speakers have similar voices. Experimental results on the bench-mark datasets WSJ0-2mix and WHAM! show that ISCIT can achieve state-of-the-art results.
Completeness for categories of generalized automata

We present a slick proof of completeness and cocompleteness for categories of $F$-automata, where the span of maps $E\leftarrow E\otimes I \to O$ that usually defines a deterministic automaton of input $I$ and output $O$ in a monoidal category $(\mathcal K,\otimes)$ is replaced by a span $E\leftarrow F E \to O$ for a generic endofunctor $F : \mathcal K\to \mathcal K$ of a generic category $\mathcal K$: these automata exist in their `Mealy' and `Moore' version and form categories $F\text{-}\mathsf{Mly}$ and $F\text{-}\mathsf{Mre}$; such categories can be presented as strict 2-pullbacks in $\mathsf{Cat}$ and whenever $F$ is a left adjoint, both $F\text{-}\mathsf{Mly}$ and $F\text{-}\mathsf{Mre}$ admit all limits and colimits that $\mathcal K$ admits. We mechanize some of of our main results using the proof assistant Agda and the library `agda-categories`.
Fixed-domain curve counts for blow-ups of projective space

We study the problem of counting pointed curves of fixed complex structure in blow-ups of projective space at general points. The geometric and virtual (Gromov-Witten) counts are found to agree asymptotically in the Fano (and some $(-K)$-nef) examples, but not in general. For toric blow-ups, geometric counts are expressed in terms of integrals on products of Jacobians and symmetric products of the domain curves, and evaluated explicitly in genus 0 and in the case of $\text{Bl}_q(\mathbb{P}^r)$. Virtual counts for $\text{Bl}_q(\mathbb{P}^r)$ are also computed via the quantum cohomology ring.
Population III X-ray binaries and their impact on the early universe

The first population of X-ray binaries (XRBs) is expected to affect the thermal and ionization states of the gas in the early Universe. Although these X-ray sources are predicted to have important implications for high-redshift observable signals, such as the hydrogen 21-cm signal from cosmic dawn and the cosmic X-ray background, their properties are poorly explored, leaving theoretical models largely uninformed. In this paper we model a population of X-ray binaries arising from zero metallicity stars. We explore how their properties depend on the adopted initial mass function (IMF) of primordial stars, finding a strong effect on their number and X-ray production efficiency. We also present scaling relations between XRBs and their X-ray emission with the local star formation rate, which can be used in sub-grid models in numerical simulations to improve the X-ray feedback prescriptions. Specifically, we find that the uniformity and strength of the X-ray feedback in the intergalactic medium is strongly dependant on the IMF. Bottom-heavy IMFs result in a smoother distribution of XRBs, but have a luminosity orders of magnitude lower than more top-heavy IMFs. Top-heavy IMFs lead to more spatially uneven, albeit strong, X-ray emission. An intermediate IMF has a strong X-ray feedback while sustaining an even emission across the intergalactic medium. These differences in X-ray feedback could be probed in the future with measurements of the cosmic dawn 21-cm line of neutral hydrogen, which offers us a new way of constraining population III IMF.
The Mass of the White Dwarf in the Recurrent Nova CI Aquilae

Abstract If recurrent novae (RNe) are progenitors of Type Ia Supernovae (SNe Ia), their white dwarfs (WD) must have masses close to the Chandrasekhar limit. The most reliable means of determining WD masses in RNe is dynamically, via radial-velocity and rotational-broadening measurements of the companion star. Such measurements require the system to be both eclipsing and to show absorption features from the secondary star. The only other reliable RNe mass estimate is for U Sco, which has a WD mass of 1.55 ± 0.24 M⊙ (Thoroughgood et al. 2001). We present new time-resolved, intermediate-resolution spectroscopy of the eclipsing RN CI Aql during quiescence. We find the mass of the WD to be 1.02 ± 0.08 M⊙ and the mass of the secondary star to be 2.41 ± 0.2 M⊙. We estimate the radius of the secondary to be 2.10 ± 0.07 R⊙. The high mass ratio of q=2.37 ± 0.15 and the high secondary star mass suggests that mass transfer occurs on a thermal timescale. We suggest that CI Aql is evolving into a supersoft x-ray source, and ultimately will explode as an SN Ia.
Completion of Matrices with Low Description Complexity

We propose a theory for matrix completion that goes beyond the low-rank structure commonly considered in the literature and applies to general matrices of low description complexity. Specifically, complexity of the sets of matrices encompassed by the theory is measured in terms of Hausdorff and upper Minkowski dimensions. Our goal is the characterization of the number of linear measurements, with an emphasis on rank-$1$ measurements, needed for the existence of an algorithm that yields reconstruction, either perfect, with probability 1, or with arbitrarily small probability of error, depending on the setup. Concretely, we show that matrices taken from a set $\mathcal{U}$ such that $\mathcal{U}-\mathcal{U}$ has Hausdorff dimension $s$ can be recovered from $k>s$ measurements, and random matrices supported on a set $\mathcal{U}$ of Hausdorff dimension $s$ can be recovered with probability 1 from $k>s$ measurements. What is more, we establish the existence of recovery mappings that are robust against additive perturbations or noise in the measurements. Concretely, we show that there are $\beta$-H\"older continuous mappings recovering matrices taken from a set of upper Minkowski dimension $s$ from $k>2s/(1-\beta)$ measurements and, with arbitrarily small probability of error, random matrices supported on a set of upper Minkowski dimension $s$ from $k>s/(1-\beta)$ measurements. The numerous concrete examples we consider include low-rank matrices, sparse matrices, QR decompositions with sparse R-components, and matrices of fractal nature.
Small singular values can increase in lower precision

We perturb a real matrix $A$ of full column rank, and derive lower bounds for the smallest singular values of the perturbed matrix, in terms of normwise absolute perturbations. Our bounds, which extend existing lower-order expressions, demonstrate the potential increase in the smallest singular values, and represent a qualitative model for the increase in the small singular values after a matrix has been downcast to a lower arithmetic precision. Numerical experiments confirm the qualitative validity of this model and its ability to predict singular values changes in the presence of decreased arithmetic precision.
Data-driven Modified Nodal Analysis Circuit Solver

This work introduces a novel data-driven modified nodal analysis (MNA) circuit solver. The solver is capable of handling circuit problems featuring elements for which solely measurement data are available. Rather than utilizing hard-coded phenomenological model representations, the data-driven MNA solver reformulates the circuit problem such that the solution is found by minimizing the distance between circuit states that fulfill Kirchhoff's laws, to states belonging to the measurement data. In this way, the previously inevitable demand for model representations is abolished, thus avoiding the introduction of related modeling errors and uncertainties. The proposed solver is applied to linear and nonlinear RC-circuits and to a half-wave rectifier.
Widespread Hydrogenation of the Moons South Polar Cold Traps

The measured neutron flux from the Moons south polar region shows evidence of locally enhanced hydrogen concentrations, likely in the form of water ice, within most permanently shadowed regions (PSR), poleward of 77 deg S latitude. Results are consistent with the original findings of Watson et al, 1961, which found that the PSRs cryogenic surfaces create exclusive conditions for the sequestration of water ice, due to their extremely low sublimation rates. Widespread PSR hydrogenation is demonstrated in several studies by showing that the contrasting PSR area distribution is being instrumentally blurred. The PSRs expected hydrogen observations are correlated by their area fraction of the fixed 30 km diameter footprint area of the Collimated Sensor for Epithermal Neutrons (CSETN), which is part of the Lunar Exploration Neutron Detector (LEND) onboard the Lunar Reconnaissance Orbiter (LRO). The correlation indicates that the PSRs are similarly hydrogenated, with an expected concentration = 0.27 wt%, relative to that of the anhydrous reference terrain (lower bounds). Hydrogen concentrations are demonstrated to be correlated to maximum temperature distributions within the basins of Haworth, Shoemaker and Faustini PSRs. Cabeus-1 PSR shows an anomalously enhanced hydrogen concentration indicating a second process contributes to its hydrogen budget. Results are consistent with ongoing processes that introduce volatiles to the surface including outgassing, solar wind production with regolith silicates, and mixing from small scale meteor impacts and diurnal temperature variation. We validate the bandpass filter used to subtract CSETNs detection of uncollimated neutrons with profiles of several PSRs neutron suppression before and after processing. Keywords: Moon, Epithermal Neutron, Hydrogen, Water, Ice, Volatiles, LRO, LEND, Diviner, LOLA
iBall: Augmenting Basketball Videos with Gaze-moderated Embedded Visualizations

We present iBall, a basketball video-watching system that leverages gaze-moderated embedded visualizations to facilitate game understanding and engagement of casual fans. Video broadcasting and online video platforms make watching basketball games increasingly accessible. Yet, for new or casual fans, watching basketball videos is often confusing due to their limited basketball knowledge and the lack of accessible, on-demand information to resolve their confusion. To assist casual fans in watching basketball videos, we compared the game-watching behaviors of casual and die-hard fans in a formative study and developed iBall based on the findings. iBall embeds visualizations into basketball videos using a computer vision pipeline, and automatically adapts the visualizations based on the game context and users’ gaze, helping casual fans appreciate basketball games without being overwhelmed. We confirmed the usefulness, usability, and engagement of iBall in a study with 16 casual fans, and further collected feedback from 8 die-hard fans.