Miracle-dz/UniFAR-FTUs huggingface dataset:
Trans-arterial embolization for intractable primary postpartum hemorrhage caused by arterial aneurysms with arteriovenous fistulas in the lower vagina bilaterally: a case report

Failure of conservative management for controlling postpartum hemorrhage (PPH) is not uncommon, particularly when PPH is caused by vascular lesions. Awareness of this possibility and initiating timely trans-arterial embolization (TAE) are essential for improving the outcome. Herein, we describe the case of a 34-year-old woman presenting with arterial aneurysms with arteriovenous fistulas in the lower vagina bilaterally, which caused intractable PPH. Conservative management failed to resolve the PPH; however, TAE successfully controlled the bleeding, and the patient recovered smoothly. Knowledge of this possible etiology for intractable PPH is crucial for timely TAE. This case report aims to highlight the pivotal role of TAE in detecting and treating this unusual cause of PPH.
Generation and characterization of a Ddx4‐iCre transgenic line for deletion in the germline beginning at genital ridge colonization

Germline‐specific Cre lines are useful for analyses of primordial germ cell, spermatogonial and oogonial development, but also for whole‐body deletions when transmitted through subsequent generations. Several germ cell specific Cre mouse strains exist, with various degrees of specificity, efficiency, and temporal activation. Here, we describe the CRISPR/Cas9 targeted insertion of an improved Cre (iCre) sequence in‐frame at the 3′ end of the Ddx4 locus to generate the Ddx4‐P2A‐iCre allele. Our functional assessment of this new allele, designated Ddx4iCreJoBo, reveals that Cre activity begins in PGCs from at least E10.5, and that it achieves higher efficiency for early gonadal (E10.5–12.5) germline deletion when compared to the inducible Oct4CreERT2 line. We found the Ddx4iCreJoBo allele to be hypomorphic for Ddx4 expression and homozygous males, but not females, were infertile. Using two reporter lines (R26RLacZ and R26RtdTomato) and a floxed gene of interest (Criptoflox) we found ectopic activity in multiple organs; global recombination (a common feature of germline Cre alleles) varies from 10 to 100%, depending on the particular floxed allele. There is a strong maternal effect, and therefore it is preferable for Ddx4iCreJoBo to be inherited from the male parent if ubiquitous deletion is not desired. With these limitations considered, we describe the Ddx4iCreJoBo line as useful for germline studies in which early gonadal deletion is required.
A Rapid and Easy Method of MALDI Biotyper Antibiotic Susceptibility Test Rapid Assay To Provide Early Meropenem Susceptibility Profile in Enterobacterales

The simplification of the MBT-ASTRA technique, especially in spectrum analysis, can considerably allow more laboratories to rapidly determine antimicrobial susceptibility profiles. ABSTRACT Antimicrobial susceptibility testing (AST) that can provide faster results is necessary. The MALDI Biotyper antibiotic susceptibility test rapid assay (MBT-ASTRA) can provide early AST results but still needs to be simplified in order to facilitate its execution by microbiology laboratories. The aim of this study was to evaluate an adaptation of MBT-ASTRA. Isolates of Enterobacterales were tested for meropenem susceptibility by MBT-ASTRA using a solution prepared from meropenem disks and performing a manual spectrum analysis. The relative growth (RG) was calculated for each isolate, and a cutoff value was established to determine the susceptibility profile of the isolates. Results of the adapted method were compared with the standard susceptibility method (broth microdilution). An adapted method of MBT-ASTRA was developed. The RG cutoff values for meropenem were ≤0.1510 for susceptibility and >0.6272 for resistance, presenting 95.65% categorical agreement, with 2.9% (2/69) minor discrepancy and 3.23% (1/31) very major discrepancy. MBT-ASTRA can be used to provide rapid AST results with a simpler and more accessible protocol, especially regarding spectrum analysis. IMPORTANCE The simplification of the MBT-ASTRA technique, especially in spectrum analysis, can considerably allow more laboratories to rapidly determine antimicrobial susceptibility profiles.
Seroprevalence of scrub typhus and other rickettsial diseases among the household rodents of Mizoram, North‐East India

In the last decade, scrub typhus, a zoonotic disease has emerged as a major health concern in Mizoram, a North‐East Indian state that shares international borders with Myanmar and Bangladesh. Mizoram is a biodiversity hotspot and >85% of the state is under forest cover, which provides an ideal ecological niche for the rodents and mites to transmit scrub typhus and other rickettsial infections. Using the Weil‐Felix test, a serosurvey of household rodents from 41 villages spread across all the 11 districts in Mizoram was undertaken to gather important insights on their role in disease transmission. Furthermore, the chigger and flea indexes were calculated from the captured rodents. The 163 rodents captured belonged to five species; the highest numbers were from Rattus tanezumi (87), followed by Rattus rattus (41), Mus musculus (17), Suncus murinus (16), and Bandicota bengalensis (2). The rickettsial seropositivity of the captured rodents was 66.26% (108 out of 163 were positive). Among the 163 rodents, sera of 75 (46.01%), 61 (37.42%), and 73 (44.78%) were reactive to OXK, OX19, and OX2 antigens, respectively. The chigger and flea index were 17.92 and 0.16, respectively. Overall, the study has given important insights into the risk of multiple rickettsial infections that household rodents could transmit in Mizoram. These findings indicate the need for the urgent implementation of effective rodent control strategies in Mizoram.
P-Channel Tunnel Field-Effect Transistors down to Sub-50 nm Channel Lengths

Experimental results of p-channel silicon vertical tunnel field-effect transistors down to sub-50 nm channel length are shown. As predicted by two-dimensional simulations, we show that the device on-current is nearly independent of channel length scaling. As the drain current is determined by electrons tunneling from the valence band to the conduction band, we show that mobility does not play any role in determining the device characteristics. Low temperature measurements reveal weak positive temperature coefficient in the transfer characteristics due to the dependence of bandgap on temperature. However, as expected for the silicon devices, low on-current is observed. Thus, we propose a lateral tunnel FET on SiGe-on-insulator with high on-currents and symmetric performance in n-channel as well as p-channel operating modes.
SKP2 Contributes to AKT Activation by Ubiquitination Degradation of PHLPP1, Impedes Autophagy, and Facilitates the Survival of Thyroid Carcinoma

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid carcinoma. Despite a good prognosis, approximately a quarter of PTC patients are likely to relapse. Previous reports suggest an association between S-phase kinase-associated protein 2 (SKP2) and the prognosis of thyroid cancer. SKP1 is related to apoptosis of PTC cells; however, its role in PTC remains largely elusive. This study aimed to understand the expression and molecular mechanism of SKP2 in PTC. SKP2 expression was upregulated in PTC tissues and closely associated with clinical diagnosis. In vitro and in vivo knockdown of SKP2 expression in PTC cells suppressed cell growth and proliferation and induced apoptosis. SKP2 depletion promoted cell autophagy under glucose deprivation. SKP2 interacted with PH domain leucine-rich repeat protein phosphatase-1 (PHLPP1), triggering its degradation by ubiquitination. Furthermore, SKP2 activates the AKT-related pathways via PHLPP1, which leads to the cytoplasmic translocation of SKP2, indicating a reciprocal regulation between SKP2 and AKT. In conclusion, the upregulation of SKP2 leads to PTC proliferation and survival, and the regulatory network among SKP2, PHLPP1, and AKT provides novel insight into the molecular basis of SKP2 in tumor progression.
Neurexins in serotonergic neurons regulate neuronal survival, serotonin transmission, and complex mouse behaviors

Extensive serotonin (5-hydroxytryptamine, 5-HT) innervation throughout the brain corroborates 5-HT’s modulatory role in numerous cognitive activities. Volume transmission is the major mode for 5-HT transmission but mechanisms underlying 5-HT signaling are still largely unknown. Abnormal brain 5-HT levels and function have been implicated in autism spectrum disorder (ASD). Neurexin (Nrxn) genes encode presynaptic cell adhesion molecules important for the regulation of synaptic neurotransmitter release, notably glutamatergic and GABAergic transmission. Mutations in Nrxn genes are associated with neurodevelopmental disorders including ASD. However, the role of Nrxn genes in the 5-HT system is poorly understood. Here, we generated a mouse model with all three Nrxn genes disrupted specifically in 5-HT neurons to study how Nrxns affect 5-HT transmission. Loss of Nrxns in 5-HT neurons reduced the number of serotonin neurons in the early postnatal stage, impaired 5-HT release, and decreased 5-HT release sites and serotonin transporter expression. Furthermore, 5-HT neuron-specific Nrxn knockout reduced sociability and increased depressive-like behavior. Our results highlight functional roles for Nrxns in 5-HT neurotransmission, 5-HT neuron survival, and the execution of complex behaviors.
Lack of the human choline transporter‐like protein SLC44A2 causes hearing impairment and a rare red blood phenotype

Blood phenotypes are defined by the presence or absence of specific blood group antigens at the red blood cell (RBC) surface, due to genetic polymorphisms among individuals. The recent development of genomic and proteomic approaches enabled the characterization of several enigmatic antigens. The choline transporter‐like protein CTL2 encoded by the SLC44A2 gene plays an important role in platelet aggregation and neutrophil activation. By investigating alloantibodies to a high‐prevalence antigen of unknown specificity, found in patients with a rare blood type, we showed that SLC44A2 is also expressed in RBCs and carries a new blood group system. Furthermore, we identified three siblings homozygous for a large deletion in SLC44A2, resulting in complete SLC44A2 deficiency. Interestingly, the first‐ever reported SLC44A2‐deficient individuals suffer from progressive hearing impairment, recurrent arterial aneurysms, and epilepsy. Furthermore, SLC44A2null individuals showed no significant platelet aggregation changes and do not suffer from any apparent hematological disorders. Overall, our findings confirm the function of SLC44A2 in hearing preservation and provide new insights into the possible role of this protein in maintaining cerebrovascular homeostasis.
Prevalence of Multistationarity and Absolute Concentration Robustness in Reaction Networks

For reaction networks arising in systems biology, the capacity for two or more steady states, that is, multistationarity, is an important property that underlies biochemical switches. Another property receiving much attention recently is absolute concentration robustness (ACR), which means that some species concentration is the same at all positive steady states. In this work, we investigate the prevalence of each property while paying close attention to when the properties occur together. Specifically, we consider a stochastic block framework for generating random networks, and prove edge-probability thresholds at which - with high probability - multistationarity appears and ACR becomes rare. We also show that the small window in which both properties occur only appears in networks with many species. Taken together, our results confirm that, in random reversible networks, ACR and multistationarity together, or even ACR on its own, is highly atypical. Our proofs rely on two prior results, one pertaining to the prevalence of networks with deficiency zero, and the other"lifting"multistationarity from small networks to larger ones.
Prediction of COVID-19 by Its Variants using Multivariate Data-driven Deep Learning Models

The Coronavirus Disease 2019 or the COVID-19 pandemic has swept almost all parts of the world since the first case was found in Wuhan, China, in December 2019. With the increasing number of COVID-19 cases in the world, SARS-CoV-2 has mutated into various variants. Given the increasingly dangerous conditions of the pandemic, it is crucial to know when the pandemic will stop by predicting confirmed cases of COVID-19. Therefore, many studies have raised COVID-19 as a case study to overcome the ongoing pandemic using the Deep Learning method, namely LSTM, with reasonably accurate results and small error values. LSTM training is used to predict confirmed cases of COVID-19 based on variants that have been identified using ECDC's COVID-19 dataset containing confirmed cases of COVID-19 that have been identified from 30 countries in Europe. Tests were conducted using the LSTM and BiLSTM models with the addition of RNN as comparisons on hidden size and layer size. The obtained result showed that in testing hidden sizes 25, 50, 75 to 100, the RNN model provided better results, with the minimum MSE value of 0.01 and the RMSE value of 0.012 for B.1. 427/B.1. 429 variant with hidden size 100. In further testing of layer sizes 2, 3, 4, and 5, the result shows that the BiLSTM model provided better results, with minimum MSE value of 0.01 and the RMSE of 0.01 for the B.1. 427/B.1. 429 variant with hidden size 100 and layer size 2.
Gas and Stars in the Teacup Quasar Looking with the 6-m Telescope

New results on the radio-quiet type 2 quasar, known as the Teacup galaxy (SDSSJ1430+1339), based on the long-slit and 3D spectroscopic data obtained at the Russian 6-m telescope, are presented. The ionized gas giant nebula, which extends up to r=56 kpc in the [O iii] emission line, was mapped with the scanning Fabry–Perot interferometer. The direct estimation of the emission line ratios confirmed that the giant nebula is ionized by the AGN. Stars in the inner r<5 kpc are significantly younger than the outer host galaxy and have a solar metallicity. The central starburst age (∼1 Gyr) agrees with possible ages for the galactic merger events and the previous episode of the quasar outflow produced two symmetric arcs visible in the [O iii] emission at the distances r= 50–55 kpc. The ionized gas velocity field can be fitted by the model of a circular rotating disk significantly inclined or even polar to the stellar host galaxy.
Square distance functions are Polyak-{\L}ojasiewicz and vice-versa

This short note gathers known results to state that the squared distance function to a (nonconvex) closed set of an Euclidean space is Polyak-{\L}ojasiewicz. As a fuzzy reciprocate, we also recall that every Polyak-{\L}ojasiewicz function can be bounded from below by the squared distance function to its set of minimizers.
New aging properties of the Clayton-Oakes model based on multivariate dispersion

In this work we present a recent de? nition of Multivariate Increasing Failure Rate (MIFR) based on the concept of multivariate dispersion. This new de? nition is an extension of the univariate characterization of IFR distributions under dispersive ordering of the residual lifetimes. We apply this de? nition to the Clayton-Oakes model. In particular, we provide several conditions to order in the multivariate dispersion sense the residual lifetimes of random vectors with a dependence structure given by the Clayton-Oakes survival copula. We illustrate our results with a graphical method.
Asymmetrizing infinite trees

A graph $G$ is asymmetrizable if it has a set of vertices whose setwise stablizer only consists of the identity automorphism. The motion $m$ of a graph is the minimum number of vertices moved by any non-identity automorphism. It is known that infinite trees $T$ with motion $m=\aleph_0$ are asymmetrizable if the vertex-degrees are bounded by $2^m. $ We show that this also holds for arbitrary, infinite $m$, and that the number of inequivalent asymmetrizing sets is $2^{|T|}$.
Local Feature Extraction from Salient Regions by Feature Map Transformation

Local feature matching is essential for many applications, such as localization and 3D reconstruction. However, it is challenging to match feature points accurately in various camera viewpoints and illumination conditions. In this paper, we propose a framework that robustly extracts and describes salient local features regardless of changing light and viewpoints. The framework suppresses illumination variations and encourages structural information to ignore the noise from light and to focus on edges. We classify the elements in the feature covariance matrix, an implicit feature map information, into two components. Our model extracts feature points from salient regions leading to reduced incorrect matches. In our experiments, the proposed method achieved higher accuracy than the state-of-the-art methods in the public dataset, such as HPatches, Aachen Day-Night, and ETH, which especially show highly variant viewpoints and illumination.
Relation-Algebraic Verification of Disjoint-Set Forests

This paper studies how to use relation algebras, which are useful for high-level specification and verification, for proving the correctness of lower-level array-based implementations of algorithms. We give a simple relation-algebraic semantics of read and write operations on associative arrays. The array operations seamlessly integrate with assignments in computation models supporting while-programs. As a result, relation algebras can be used for verifying programs with associative arrays. We verify the correctness of an array-based implementation of disjoint-set forests using the union-by-rank strategy and find operations with path compression, path splitting and path halving. All results are formally proved in Isabelle/HOL. This paper is an extended version of [1].
Effects of Variable Linewidth Laser and Variable Linewidth Shape Laser on Coherent FMCW LiDAR

Terahertz (THz) waves have attracted attention as carrier waves for next-generation wireless communications (6G). Electronic THz emitters are widely used in current mobile communications; however, they may face technical limitations in 6G with upper-frequency limits. We demonstrate wireless communication in a 560-GHz band by using a photonic THz emitter based on photomixing of a 560-GHz-spacing soliton microcomb in a uni-travelling carrier photodiode together with a THz receiver of Schottky barrier diode. The on-off keying data transfer with 2-Gbit/s achieves a Q-factor of 3.4, thus, satisfying the limit of forward error correction.
A Deep Gaussian Process Model for Seismicity Background Rates

The spatio-temporal properties of seismicity give us incisive insight into the stress state evolution and fault structures of the crust. Empirical models based on self-exciting point-processes continue to provide an important tool for analyzing seismicity, given the epistemic uncertainty associated with physical models. In particular, the epidemic-type aftershock sequence (ETAS) model acts as a reference model for studying seismicity catalogs. The traditional ETAS model uses simple parametric definitions for the background rate of triggering-independent seismicity. This reduces the effectiveness of the basic ETAS model in modelling the temporally complex seismicity patterns seen in seismic swarms that are dominated by aseismic tectonic processes such as fluid injection rather than aftershock triggering. In order to robustly capture time-varying seismicity rates, we introduce a deep Gaussian process formulation for the background rate as an extension to ETAS. Gaussian processes (GPs) are a robust non-parametric model for function spaces with covariance structure. By conditioning the lengthscale structure of a GP with another GP, we have a deep-GP: a probabilistic, hierarchical model that automatically tunes its structure to match data constraints. We show how the deep-GP-ETAS model can be efficiently sampled by making use of a Metropolis-within-Gibbs scheme, taking advantage of the branching process formulation of ETAS and a stochastic partial differential equation (SPDE) approximation for MatÃ©rn GPs. We illustrate our method using synthetic examples, and show that the deep-GP-ETAS model successfully captures multiscale temporal behavior in the background forcing rate of seismicity. We then apply the results to two real-data catalogues: the Ridgecrest, CA July 5 2019 Mw 7.1 event catalogue, showing that deep-GP-ETAS can succesfully characterize a classical aftershock sequence; and the 2016–2019 Cahuilla, CA earthquake swarm, which shows two distinct phases of aseismic forcing concordant with a fluid injection driven initial sequence, arrest of the fluid along a physical barrier, and release following the largest Mw 4.4 event of the sequence.
Infinite memory effects on the stability of Biharmonic Schr\"odinger equation

This paper deals with the stabilization of the linear Biharmonic Schr\"odinger equation in an $n$-dimensional open bounded domain under Dirichlet-Neumann boundary conditions considering three infinite memory terms as damping mechanisms. We show that depending on the smoothness of initial data and the arbitrary growth at infinity of the kernel function, this class of solution goes to zero with a polynomial decay rate like $t^{-n}$ depending on assumptions about the kernel function associated with the infinite memory terms.
Central support for triangulated categories

For any essentially small triangulated category the centre of its lattice of thick subcategories is introduced; it is a spatial frame and yields a notion of central support. A relative version of this centre recovers the support theory for tensor triangulated categories and provides a universal notion of cohomological support. Along the way we establish Mayer-Vietoris sequences for pairs of commuting subcategories.
Exact and rapid linear clustering of networks with dynamic programming

We study the problem of clustering networks whose nodes have imputed or physical positions in a single dimension, for example prestige hierarchies or the similarity dimension of hyperbolic embeddings. Existing algorithms, such as the critical gap method and other greedy strategies, only offer approximate solutions to this problem. Here, we introduce a dynamic programming approach that returns provably optimal solutions in polynomial time—O(n2) steps—for a broad class of clustering objectives. We demonstrate the algorithm through applications to synthetic and empirical networks, and show that it outperforms existing heuristics by a significant margin, with a similar execution time.