Miracle-dz/UniFAR-FTUs huggingface dataset:
Upregulation of FOXA2 in uterine luminal epithelium and vaginal basal epithelium of epiERα–/– (Esr1fl/flWnt7aCre/+) mice

Abstract Forkhead box protein A2 (FOXA2) is a pioneer transcription factor important for epithelial budding and morphogenesis in different organs. It has been used as a specific marker for uterine glandular epithelial cells (GE). FOXA2 has close interactions with estrogen receptor α (ERα). ERα binding to Foxa2 gene in the uterus indicates its regulation of Foxa2. The intimate interactions between ERα and FOXA2 and their essential roles in early pregnancy led us to investigate the expression of FOXA2 in the female reproductive tract of pre-implantation epiERα–/– (Esr1fl/flWnt7aCre/+) mice, in which ERα is conditionally deleted in the epithelium of reproductive tract. In the oviduct, FOXA2 is detected in the ciliated epithelial cells of ampulla but absent in the isthmus of day 3.5 post-coitum (D3.5) Esr1fl/fl control and epiERα–/– mice. In the uterus, FOXA2 expression in the GE appears to be comparable between Esr1fl/fl and epiERα–/– mice. However, FOXA2 is upregulated in the D0.5 and D3.5 but not PND25-28 epiERα–/– uterine luminal epithelial cells (LE). In the vagina, FOXA2 expression is low in the basal layer and increases toward the superficial layer of the D3.5 Esr1fl/fl vaginal epithelium, but FOXA2 is detected in the basal, intermediate, and superficial layers, with the strongest FOXA2 expression in the intermediate layers of the D3.5 epiERα–/– vaginal epithelium. This study demonstrates that loss of ERα in LE and vaginal basal layer upregulates FOXA2 expression in these epithelial cells during early pregnancy. The mechanisms for epithelial cell-type specific regulation of FOXA2 by ERα remain to be elucidated. Summary Sentence FOXA2 is upregulated in the uterine luminal epithelial cells and vaginal basal epithelial cells of preimplantation epiERα–/– (Esr1fl/flWnt7aCre/+) mice that are deficient of ERα in the epithelium of the female reproductive tract (FRT). Graphical Abstract
How do Effort, Reward, and Their Combined Effects Predict Burnout, Self-rated Health, and Work-family Conflict Among Permanent and Fixed-term Faculty?

Abstract Employment conditions and psychosocial factors have been linked to various health-related outcomes in different occupational groups, but few studies focus on the conditions in academia. This study explores the effects of effort, reward, and their interaction to explain health-related outcomes, namely burnout, self-rated health, and work-family conflict among academic faculty in Sweden. We also explore these effects among those with permanent and fixed-term employment contracts. Questionnaire data, collected online in 2016, came from 2335 employees (57% women) with a doctoral degree, working at a Swedish higher education institution. Latent moderation analysis combined with multi-group analysis was conducted. Main effects of effort were found for all health-related outcomes revealing that effort was associated with higher burnout, poorer self-rated health, and greater work-family conflict. Reward was negatively associated with burnout and self-rated health revealing that reward reduced burnout and improved self-rated health. The interaction between effort and reward was significantly associated with all outcomes among permanent contract employees, but was non-significant among those with fixed-term contracts. This may suggest that fixed-term faculty are less affected by the presence or lack of reward. Overall, the findings emphasize the importance of the psychosocial work environment to understand health-related consequences for permanent and fixed-term faculty with a doctoral degree.
Decoding High-Order Interleaved Rank-Metric Codes

This paper presents an algorithm for decoding any linear interleaved code of high interleaving order in the rank metric. The new decoder is an adaptation of the Hamming-metric decoder by Metzner and Kapturowski (1990) and guarantees to correct all rank errors of weight up to $d-2$ whose rank over the large base field of the code equals the number of errors, where $d$ is the minimum rank distance of the underlying code. It is based on linear-algebraic computations, and has an explicit and easy-to-handle success condition.
Population Genetic Structure of Phlebotomus sergenti (Diptera: Psychodidae) Collected in Four Regions of Morocco Based on the Analysis of Cyt b and EF-1 α Genes

Abstract Phlebotomus(Ph.) sergentiis the main vector of Leishmania(L.) tropica(Trypanosomatida:Trypanosomatidae), the causative agent of anthroponotic cutaneous leishmaniasis in Morocco. This species has an extended geographical distribution, wider than that of the parasite. The main objective of our study was to analyze the genetic diversity of Ph. sergenti collected in four foci in Morocco: Taza, Foum Jemâa, El Hanchane, and Ouarzazate. We studied a set of diversity and population structure indices by sequencing two markers; nuclear EF-1α and mitochondrial Cyt b from 175 individual sand flies. Our results showed a considerable degree of intraspecific polymorphism with a high number of haplotypes identified in both genes. Many polymorphic sites detected in the Cyt b sequences (SCyt b = 45) indicate that it is the most polymorphic marker showing a distinct distribution of haplotypes according to their geographical origin, whereas the EF-1α marker showed no geographical isolation. Analysis byTajima's D and Fu's Fs tests revealed a possible recent expansion of the populations, especially with the EF-1α marker, showing significant values inTaza and Ouarzazate sequences. The present study revealed significant genetic diversity within Ph. sergenti populations in Morocco. The results warrant further research using a combination of more than two markers including mitochondrial and non-mitochondrial markers, which may provide more information to clarify the genetic status of Ph. sergenti.
Optimal Discrete Adjustments for Short Production Runs

Diameter measurements on successive metal hubs from a machining operation are modeled using a random walk with observation error and linear drift corresponding to tool wear. After producing and measuring a hub, the depth of the cutting tool on the lathe can be adjusted in integer multiples of 0.0001 inches. How should the tool be adjusted? An optimal discrete adjustment strategy is derived assuming that the lathe automatically corrects for deterministic tool wear. The objective is to minimize expected run costs proportional to the sum of squared diameter deviations from a target plus fixed charges for manual tool adjustments. The optimal strategy makes no manual adjustment if an estimate of the process mean is near target. Otherwise, an adjustment is made to return the estimated mean as near to target as possible within the adjustment resolution. The region where no adjustments are made widens near the end of the production run where adjustments have only short-term impact. The region converges as the number of remaining periods increases. Plots of expected run costs show that the extra cost of discreteness is small at high resolution but is substantial when the adjustment grid is coarse.
Development of ANCA-associated vasculitis followed by SARS-CoV-2 vaccination in a patient with HLA-DRB1*09: 01 allele.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), presents with severe pneumonia and fatal systemic complications. Currently, SARS-CoV-2 vaccines are effective in reducing the risk of new onset and getting worse of the disease. However, autoimmune diseases such as antineutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV) have been reported to develop after COVID-19 vaccine administration. Case presentation: A 71-year-old woman presented with fever, malaise, urinary abnormalities and renal dysfunction after receiving the COVID-19 vaccine (Pfizer-BioNTech). We clinically diagnosed AAV with her manifestations and serological test (MPO-ANCA positive). Her clinical findings were improved after immunosuppressive therapy. We examined her genetic susceptibility to AAV and we found that her allele was HLA-DRB1*09:01, which is a risk allele of MPO-AAV. Mechanistically, SARS-CoV-2 vaccines would activate immunity, including neutrophils, and trigger AAV onset in this patient with a genetic risk to develop AAV. The pathophysiology of this case would share with that of autoimmune/inflammatory syndrome induced by adjuvants (ASIA) in the absence of external adjuvants.
Arsenic Causes Distinct Gene Expression Changes in Macrophages Polarized in vitro with either interferon-γ (IFN-γ) or interleukin-4 (IL-4).

Arsenic exposure is correlated with atherosclerosis in epidemiological studies and in animal models. We have previously shown that arsenic exposure enhanced atherosclerotic plaque size, increased plaque lipid content and decreased plaque smooth muscle cell and collagen contents in apoE-/- mice. However, the percentage of plaque-resident macrophages, the primary drivers of atherosclerosis remained unchanged. Therefore, we hypothesized that while arsenic does not change the quantity of macrophages, it alters macrophage transcriptome towards a pro-atherogenic state. To test this hypothesis, we used bone marrow-derived macrophages, polarized them to either IFN-ɣ stimulated, pro-inflammatory or IL-4 stimulated, alternatively-activated macrophages in the presence or absence of 0.67 µM (50 ppb) arsenic and performed RNA sequencing. Arsenic exposure altered the gene expression of the macrophages in a subtype-specific manner. Most differentially expressed genes (88%) were altered specifically in either IFN-ɣ- or IL-4-stimulated macrophages, while in the remaining 12% genes that changed in both cell types, did so in opposite directions. In IL-4-stimulated macrophages, arsenic significantly downregulated the genes involved in cholesterol biosynthesis and the chemokines, CCL17/CCL22. Whereas, in IFN-ɣ-stimulated macrophages, genes associated with liver X receptor (LXR) pathway were downregulated by arsenic. Using a bone marrow transplant experiment, we validated that deletion of LXRα from the hematopoietic compartment rescued arsenic-enhanced atherosclerosis in apoE-/- mouse model. Together, these data suggest that arsenic modulates subtype-specific transcriptomic changes in macrophages and further emphasize the need to define macrophage heterogeneity in atherosclerotic plaques in order to evaluate pro-atherogenic role of arsenic.
Cryopreserved human precision-cut lung slices provide an immune competent pulmonary test system for “on-demand” use and long-term cultures

Abstract Human precision-cut lung slices (hPCLS), considered a highly relevant ex vivo model of the lung, offer native architecture and cells of the lung tissue including respiratory parenchyma, small airways, and immune competent cells. However, the irregular availability of donor lungs has limited the accessibility of this system. As described here, thousands of hPCLS can be created from 1 lung, cryopreserved, and used “on demand” by applying slicing and cryopreservation methodology improvements. Fresh and cryopreserved (∼7 and ∼34 weeks; F&C) hPCLS from 1 donor lung were cultured for up to 29 days and evaluated for biomass, viability, tissue integrity, and inflammatory markers in response to lipopolysaccharide (LPS; 5 µg/ml) and Triton X-100 (TX100; 0.1%) challenge (24 h) at days 1, 8, 15, 22, and 29 following culture initiation. The F&C hPCLS retained biomass, viability, and tissue integrity throughout the 29 days and demonstrated immune responsiveness with up to ∼30-fold LPS-induced cytokine increases. Histologically, more than 70% of normal cytomorphological features were preserved in all groups through day 29. Similar retention of tissue viability and immune responsiveness post cryopreservation (4–6 weeks) and culture (up to 14 days) was observed in hPCLS from additional 3 donor lungs. Banking cryopreserved hPCLS from various donors (and disease states) provides a critical element in researching human-derived pulmonary tissue. The retention of viability and functional responsiveness (≥4 weeks) allows evaluation of long-term, complex endpoints reflecting key events in Adverse Outcome Pathways and positions hPCLS as a valuable human-relevant model for use in regulatory applications.
Pion-nucleon sigma term $\sigma_{\pi N}$ and deeply bound pionic atoms

We investigate the possibility to determine the value of the pion-nucleon sigma term $\sigma_{\pi N}$ precisely by the experimental observables of the deeply bound pionic atoms. We discuss the sensitivity of the observables to $\sigma_{\pi N}$ and take into account the typical errors of the up-to-date experiments of the deeply bound pionic atoms. We find that the gap of the binding energies and the width of the deeply bound pionic states are good observables for the $\sigma_{\pi N}$ value determination by the experimental data. We also discuss the expected difficulties for the accurate determination of the value of $\sigma_{\pi N}$ due to the correlation between the $\sigma$ term and the potential parameter in the pion-nucleus optical potential.
Effective medium model for graphene superlattices with electrostatic and magnetic vector potentials

In this article we develop an effective medium model to characterize the electron wave propagation in graphene based nanostructures with an electrostatic and magnetic vector potentials imposed on their surface. We use a numerical algorithm to determine the effective medium parameters of the heterostructure and calculate the electronic band structure of the system. We apply our formalism to analyze superlattices with solely a magnetic potential and reveal that the response of the structure remains reciprocal and is characterized by a decrease in charge carrier's velocity. We also study the response of superlattices with both potentials superimposed on graphene and show that the response of the system becomes nonreciprocal with a dispersion characterized by a tilted Dirac cone. We demonstrate that it is possible to alternate between a type-I, type-II or type-III Dirac cones by properly tuning the amplitude of the potentials.
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models

With tools like GitHub Copilot, automatic code suggestion is no longer a dream in software engineering. These tools, based on large language models, are typically trained on massive corpora of code mined from unvetted public sources. As a result, these models are susceptible to data poisoning attacks where an adversary manipulates the model's training by injecting malicious data. Poisoning attacks could be designed to influence the model's suggestions at run time for chosen contexts, such as inducing the model into suggesting insecure code payloads. To achieve this, prior attacks explicitly inject the insecure code payload into the training data, making the poison data detectable by static analysis tools that can remove such malicious data from the training set. In this work, we demonstrate two novel attacks, COVERT and TROJANPUZZLE, that can bypass static analysis by planting malicious poison data in out-of-context regions such as docstrings. Our most novel attack, TROJANPUZZLE, goes one step further in generating less suspicious poison data by never explicitly including certain (suspicious) parts of the payload in the poison data, while still inducing a model that suggests the entire payload when completing code (i.e., outside docstrings). This makes TROJANPUZZLE robust against signature-based dataset-cleansing methods that can filter out suspicious sequences from the training data. Our evaluation against models of two sizes demonstrates that both COVERT and TROJANPUZZLE have significant implications for practitioners when selecting code used to train or tune code-suggestion models.
Analysis of a spatio-temporal advection-diffusion model for human behaviors during a catastrophic event

In this work, using the theory of first-order macroscopic crowd models, we introduce a compartmental advection-diffusion model, describing the spatio-temporal dynamics of a population in different human behaviors (alert, panic and control) during a catastrophic event. For this model, we prove the local existence, uniqueness and regularity of a solution, as well as the positivity and $L^1$--boundedness of this solution. Then, in order to study the spatio-temporal propagation of these behavioral reactions within a population during a catastrophic event, we present several numerical simulations for different evacuation scenarios.
Role of Small-scale Impulsive Events in Heating the X-Ray Bright Points of the Quiet Sun

Small-scale impulsive events, known as nanoflares, are thought to be one of the prime candidates that can keep the solar corona hot at its multimillion-Kelvin temperature. Individual nanoflares are difficult to detect with the current generation of instruments; however, their presence can be inferred through indirect techniques such as Differential Emission Measure (DEM) analysis. Here, we employ this technique to investigate the possibility of nanoflare heating of the quiet corona during the minimum of solar cycle 24. We estimate the DEM of disk-integrated quiet Sun and X-ray bright points (XBP) using the observations from XSM on board the Chandrayaan-2 orbiter and AIA on board the Solar Dynamic Observatory. XBPs are found to be the dominant contributor to disk-integrated X-rays, with a radiative flux of ∼2 × 105 erg cm−2 s−1. XBPs consist of small-scale loops associated with bipolar magnetic fields. We simulate such XBP loops using the EBTEL hydrodynamic code. The lengths and magnetic field strengths of these loops are obtained through a potential field extrapolation of the photospheric magnetogram. Each loop is assumed to be heated by random nanoflares having an energy that depends on the loop properties. The composite nanoflare energy distribution for all the loops has a power-law slope close to −2.5. The simulation output is then used to obtain the integrated DEM. It agrees remarkably well with the observed DEM at temperatures above 1 MK, suggesting that the nanoflare distribution, as predicted by our model, can explain the XBP heating.
An endoscopic multi-exposure laser speckle contrast analysis system for blood flow and microcirculation measurements

We present a dual wavelength endoscope which uses Endoscopic Laser Speckle Contrast Analysis (ELASCA) with the aim to image tissue blood flow and perfusion during surgical procedures. In this study we measure speckle decorelation times, which are associated with flow, by imaging speckle patterns at a wide range of detector exposure times. In order to understand the effects of image collection efficiency and sample scattering properties, control experiments with different optical systems were performed by imaging of tissue mimicking phantoms and inferring their flow parameters.
Eigenfunctions of Galactic phase space spirals from dynamic mode decomposition

We investigate the spatiotemporal structure of simulations of the homogeneous slab and isothermal plane models for the vertical motion in the Galactic disc. We use dynamic mode decomposition (DMD) to compute eigenfunctions of the simulated distribution functions for both models, referred to as DMD modes. In the case of the homogeneous slab, we compare the DMD modes to the analytic normal modes of the system to evaluate the feasibility of DMD in collisionless self-gravitating systems. This is followed by the isothermal plane model, where we focus on the effect of self-gravity on phase mixing. We compute DMD modes of the system for varying relative dominance of mutual interaction and external potential, so as to study the corresponding variance in mode structure and lifetime. We find that there is a regime of relative dominance, at approximately 4 : 1 external potential to mutual interaction where the DMD modes are spirals in the (z, vz) plane, and are nearly un-damped. This leads to the proposition that a system undergoing phase mixing in the presence of weak-to-moderate self-gravity can have persisting spiral structure in the form of such modes. We then conclude with the conjecture that such a mechanism may be at work in the phase space spirals observed in Gaia Data Release 2, and that studying more complex simulations with DMD may aid in understanding both the timing and form of the perturbation that lead to the observed spirals.
Pervasiveness of the breakdown of self-interacting vector field theories

Various groups recently argued that self-interacting vector field theories lack a well-defined time evolution when the field grows to large amplitudes, which has drastic consequences for models in gravity and high energy theory. Such field amplitudes can be a result of an external driving mechanism, or occur intrinsically, due to large values of the field and its derivatives in the initial data. This brings a natural question: is small amplitude initial data guaranteed to evolve indefinitely in these theories in the absence of an outside driving term? We answer this question in the negative, demonstrating that arbitrarily low amplitude initial data can still lead to the breakdown of the theory. Namely, ingoing spherically symmetric wave packets in more than one spatial dimensions grow as an inverse power of the radius, and their amplitudes can generically reach high enough values where time evolution ceases to exist. This simple example further establishes the pervasiveness of the pathology of self-interacting vector field theories.
Invariant Gibbs measures for 1D NLS in a trap

We consider the one dimensional cubic nonlinear Schr{\"o}dinger equation with trapping potential behaving like |x| s (s>1) at infinity. We construct Gibbs measures associated to the equation and prove that the Cauchy problem is globally well-posed almost surely on their support. Consequently, the Gibbs measure is indeed invariant under the flow of the equation. We also address the construction and invariance of canonical Gibbs measures, conditioned on the L 2 mass.
Delay-dependent stability criteria for uncertain neutral systems with multiple time-varying delays via LMI approach

The asymptotic stability conditions for a class of uncertain neutral system with multiple time-varying delays are considered. LMI-based delay-dependent criteria are proposed to guarantee the asymptotic stability of systems. Based on the results of this paper, the model transformation is not used in finding the delay-dependent results. Significant improvement for the delay-dependent results has been developed and proposed. Finally, some numerical examples are illustrated to show the improvement of this paper.
Optimal multiple-lag out-of-sequence measurement algorithm based on generalized smoothing framework

Out-of-sequence measurement (OOSM) filtering algorithms have drawn a great deal of attention during the last few years. A number of multiple-lag OOSM filtering algorithms exists in the research literature. Only one of the OOSM filtering algorithms is optimal and remaining algorithms are suboptimal even for the linear dynamics and linear measurement models with additive Gaussian noises. A general feature of each OOSM filtering algorithm is that the algorithm calculates optimally or sub-optimally, the smoothed or retrodicted state estimate, associated covariance, and cross-covariance between the state and the measurement at the OOSM time. The existing optimal OOSM algorithm calculates these three quantities using a forward recursive algorithm. In this paper, we show that the OOSM filtering problem can be solved optimally using a generalized smoothing or retrodiction framework for the linear dynamics and linear measurement models with additive Gaussian noises. We develop a new optimal smoothing based OOSM filtering algorithm which uses the Rauch-Tung-Streibel (RTS) fixed-interval optimal backward smoother. We present numerical results using simulated data which includes two-dimensional position and velocity measurements and analyze the performance of the algorithm using Monte Carlo simulations.