Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Oxidative Stress-Dependent C/EBPβ Expression on CAF Transformation Inducing HCT116 Colorectal Cancer Cell Progression; Migration and Invasion

Objective: To investigate oxidative stress-related CAF transformation through C/EBPβ, which affects CRC progression and may have a potential implication for CRC treatment. Methods: The conditioned media (CM) from HCT116, CRC cells, was used to activate CCD-18Co, colon fibroblasts, then the ability of activated FBs to induce HCT116 growth and progression was assessed using MTT assay, transwell migration, and matrix invasion assay. Alteration of the cytokine profile and oxidative stress of the activated FBs were studied with cytokine arrays and DCFH-DA assay, respectively. The protein expressions of the CAF markers (α-SMA and FAP) and C/EBPβ were investigated with immunofluorescence and western blotting. Result: It was found that CM from HCT116 cells induced oxidative stress, change of cytokine profile, CAF markers, and the C/EBPβ expression of activated FBs. Furthermore, when the oxidative stress of the activated FBs was suppressed, FAP and C/EBPβ expression were downregulated, correlating with the disabling of their capability to support the cancer progression. The C/EBPβ and prognosis for CRC patients were accessed using the GEPIA dataset, in which high C/EBPβ expression was associated with a poor prognosis. Conclusion: These findings suggest that C/EBPβ expression has a role in CAF transformation in an oxidative stress-related manner and might be used as a target to improve aggressive CRC treatment outcomes.
Immunity mediates host specificity in the human hookworm Ancylostoma ceylanicum

Hookworm infection affects millions globally, leading to chronic conditions like malnutrition and anaemia. Among the hookworm species, Ancylostoma ceylanicum stands out as a gener-alist, capable of infecting various hosts, including humans, cats, dogs and hamsters. Surprisingly, it cannot establish in mice, despite their close phylogenetic relationship to hamsters. The present study investigated the development of A. ceylanicum in immunodeficient NSG mice to determine the contribution of the immune system to host restriction. The infections became patent on day 19 post-infection (PI) and exhibited elevated egg production which lasted for at least 160 days PI. Infective A. ceylanicum larvae reared from eggs released by infected NSG mice were infectious to hamsters and capable of reproduction, indicating that the adults in the NSG mice were producing viable offspring. In contrast, A. ceylanicum showed limited development in outbred Swiss Webster mice. Furthermore, the closely related canine hookworm Ancylostoma caninum was unable to infect and develop in NSG mice, indicating that different mechanisms may determine host specificity even in closely related species. This is the first report of any hookworm species completing its life cycle in a mouse and implicate the immune system in determining host specificity in A. ceylanicum .
Safety and effectiveness of totally laparoscopic total gastrectomy vs laparoscopic-assisted total gastrectomy: a meta-analysis

Background: For gastric cancer with total gastrectomy, the usual laparoscopic surgical approaches are totally laparoscopic total gastrectomy (TLTG) and laparoscopic-assisted total gastrectomy (LATG). Due to its difficult anastomotic technique, the adoption of TLTG is limited. Therefore, surgeons prefer using LATG, which also led to TLTG being somewhat overlooked, so there is no clear conclusion today as to which surgical procedure is more favorable to the patient’s recovery. This article aimed to compare the safety and short-term outcomes of the two surgical approaches. Materials and methods: Studies comparing TLTG and LATG, published up to December 2022, were searched in PubMed, Web of Science, and Embase databases. The study outcomes, including operative time, blood loss, anastomosis time, number of retrieved lymph nodes, proximal and distal resection margins, time to first fluid and soft diet, hospitalization duration, time to first flatus, and postsurgical and anastomotic complications, were compared between these two different surgical procedures. Statistics were analyzed with RevMan 5.4 and Stata 13.1. Results: Fifteen publications were included in this study. The total sample included 3023 cases. The meta-analysis revealed no significant difference in overall postoperative complications between the two surgical approaches (P>0.05). Compared with LATG, TLTG led to reduced intraoperative blood loss (P<0.0001), an increased number of lymphatic node dissections (P<0.0001), and decreased hospitalization duration (P=0.002). However, operative time, anastomosis time, pulmonary infection, resection margins, time to first fluid and soft diet, time to first flatus and anastomosis-related complications were no significant difference between TLTG and LATG groups (P>0.05). Conclusion: TLTG did not lead to an increase in overall postoperative complications, which is a reliable surgical approach for treatment of gastric cancer. Moreover, it may reduce harm to patients and enable them to obtain better surgical outcomes.
MVDINET: A Novel Multi-Level Enzyme Function Predictor With Multi-View Deep Interactive Learning

As a class of extremely significant of biocatalysts, enzymes play an important role in the process of biological reproduction and metabolism. Therefore, the prediction of enzyme function is of great significance in biomedicine fields. Recently, computational methods for predicting enzyme function have been proposed, and they effectively reduce the cost of enzyme function prediction. However, there are still deficiencies for effectively mining the discriminant information for enzyme function recognition in existing methods. In this study, we present MVDINET, a novel method for multi-level enzyme function prediction. First, the initial multi-view feature data is extracted by the enzyme sequence. Then, the above initial views are fed into various deep specific network modules to learn the depth-specificity information. Further, a deep view interaction network is designed to extract the interaction information. Finally, the specificity information and interaction information are fed into a multi-view adaptively weighted classification. We compressively evaluate MVDINET on benchmark datasets and demonstrate that MVDINET is superior to existing methods.
The potential benefits of long-acting injectable cabotegravir in pregnant and breastfeeding women and their infants

Background: Pregnant and breastfeeding women (PBW) in sub-Saharan Africa have high HIV incidence rates and associated risk of vertical transmission to their infants. Oral preexposure prophylaxis (PrEP) and injectable PrEP (long-acting cabotegravir, or CAB-LA) can potentially reduce this HIV transmission, but population-level impacts are uncertain. Methods: We extended a previously developed model of HIV and PrEP in South Africa to allow for variable PrEP duration and preference in PBW. We considered three potential scenarios for PrEP provision to PBW: oral PrEP only, CAB-LA only, and allowing oral/CAB-LA choice, with uptake and retention assumptions informed by South African data, each compared with a ‘base’ scenario without PrEP for PBW. Results: Without PrEP for PBW, the model estimates 1.31 million new infections will occur between 2025 and 2035 in South African adults and children, including 100 000 in PBW, 16 800 in infants at/before birth, and 35 200 in children through breastmilk. In the oral PrEP-only scenario, these numbers would reduce by 1.2% (95% CI: 0.7–1.7%), 8.6% (4.8–12.9%), 4.0% (2.1–5.8%), and 5.3% (3.0–8.2%) respectively. In the CAB-LA-only scenario, the corresponding reductions would be 6.1% (2.9–9.6%), 41.2% (19.8–65.0%), 12.6% (6.0–19.4%), and 29.5% (13.9–46.8%), respectively, and in the oral/CAB-LA choice scenario, similar reductions would be achieved [5.6% (3.4–8.0%), 39% (23.4–55.9%), 12.4% (7.4–16.8%) and 27.6% (16.5–39.9%) respectively]. Conclusion: CAB-LA has the potential to be substantially more effective than oral PrEP in preventing HIV acquisition in PBW and vertical transmission, and can also modestly reduce HIV incidence at a population level.
The Evolution of Temperature and Desiccation-Related Protein Families in Tardigrada Reveals a Complex Acquisition of Extremotolerance

Abstract Tardigrada is an ecdysozoan lineage famed for its resilience. Tardigrades can tolerate high doses of radiation, low-oxygen environments, desiccation, and both high and low temperatures under a dormant state called “anhydrobiosis”, which is a reversible halt of metabolism upon almost complete desiccation. A large amount of research has focused on the genetic pathways related to these capabilities, and a number of genes have been identified and linked to the extremotolerant response of tardigrades. However, the history of these genes is unclear, and the origins and history of extremotolerant genes within Tardigrada remain a mystery. Here, we generate the first phylogenies of six separate protein families linked with desiccation and radiation tolerance in Tardigrada: cytosolic abundant heat-soluble protein, mitochondrial abundant heat-soluble protein, secretory abundant heat-soluble protein, meiotic recombination 11 homolog, and the newly discovered Echiniscus testudo abundant heat-soluble proteins (alpha and beta). The high number of independent gene duplications found amongst the six gene families studied suggests that tardigrades have a complex history with numerous independent adaptations to cope with aridity within the limnoterrestrial environment. Our results suggest that tardigrades likely transitioned from a marine environment to a limnoterrestrial environment only twice, once in stem Eutardigrada and once in Heterotardigrada, which explains the unique adaptations to anhydrobiosis present in both classes.
Energy diffusion in weakly interacting chains with fermionic dissipation-assisted operator evolution

Interacting lattice Hamiltonians at high temperature generically give rise to energy transport governed by the classical diffusion equation; however, predicting the rate of diffusion requires numerical simulation of the microscopic quantum dynamics. For the purpose of predicting such transport properties, computational time evolution methods must be paired with schemes to control the growth of entanglement to tractably simulate for sufficiently long times. One such truncation scheme -- dissipation-assisted operator evolution (DAOE) -- controls entanglement by damping out components of operators with large Pauli weight. In this paper, we generalize DAOE to treat fermionic systems. Our method instead damps out components of operators with large fermionic weight. We investigate the performance of DAOE, the new fermionic DAOE (FDAOE), and another simulation method, density matrix truncation (DMT), in simulating energy transport in an interacting one-dimensional Majorana chain. The chain is found to have a diffusion coefficient scaling like interaction strength to the fourth power, contrary to naive expectations based on Fermi's Golden rule -- but consistent with recent predictions based on the theory of \emph{weak integrability breaking}. In the weak interaction regime where the fermionic nature of the system is most relevant, FDAOE is found to simulate the system more efficiently than DAOE.
SYZ mirror symmetry of solvmanifolds

We present an effective construction of non-Kaehler supersymmetric mirror pairs in the sense of Lau,Tseng and Yau starting from left-invariant affine structures on Lie groups. Applying this construction we explicitly find SYZ mirror symmetric partners of all known compact 6-dimensional completely solvable solvmanifolds that admit a semi-flat type IIA structure.
Group-wise Sparse and Explainable Adversarial Attacks

Sparse adversarial attacks fool deep neural networks (DNNs) through minimal pixel perturbations, typically regularized by the $\ell_0$ norm. Recent efforts have replaced this norm with a structural sparsity regularizer, such as the nuclear group norm, to craft group-wise sparse adversarial attacks. The resulting perturbations are thus explainable and hold significant practical relevance, shedding light on an even greater vulnerability of DNNs than previously anticipated. However, crafting such attacks poses an optimization challenge, as it involves computing norms for groups of pixels within a non-convex objective. In this paper, we tackle this challenge by presenting an algorithm that simultaneously generates group-wise sparse attacks within semantically meaningful areas of an image. In each iteration, the core operation of our algorithm involves the optimization of a quasinorm adversarial loss. This optimization is achieved by employing the $1/2$-quasinorm proximal operator for some iterations, a method tailored for nonconvex programming. Subsequently, the algorithm transitions to a projected Nesterov's accelerated gradient descent with $2$-norm regularization applied to perturbation magnitudes. We rigorously evaluate the efficacy of our novel attack in both targeted and non-targeted attack scenarios, on CIFAR-10 and ImageNet datasets. When compared to state-of-the-art methods, our attack consistently results in a remarkable increase in group-wise sparsity, e.g., an increase of $48.12\%$ on CIFAR-10 and $40.78\%$ on ImageNet (average case, targeted attack), all while maintaining lower perturbation magnitudes. Notably, this performance is complemented by a significantly faster computation time and a $100\%$ attack success rate.
The ecohydrology of ecosystem transitions: a meta‐analysis

A vast body of literature demonstrated that anthropogenic disturbances such as overgrazing and fire are key drivers of abrupt transition between vegetation types in ecosystems. In this study, we propose that the hydrological context (described in terms of rainfall, evapotranspiration and water yield) is a first‐order, primordial determinant of the propensity of ecosystems to undergo transition. This implies that the anthropogenic disturbance is a second‐order determinant that is strongly conditioned by the first one. Through the meta‐analysis of existing studies, a collection of 685 geo‐referenced study cases was organized to study the hydrological characteristics of three climatic regions and three ecosystems that vary in their relation between woody and grassy plants. Thus, humid, sub‐humid and dry climatic regions, respectively, receiving >1000, 500–1000 and <500 mm year−1, were studied, and possible transition mechanisms among grasslands/savannas, shrublands and forests were analysed. The results showed that the ecohydrological context determines the probabilities of ecosystems transitions in different climatic regions and the prevalence of alternative transition mechanisms. We showed that transition of forests into other ecosystems is highly improbable in high‐precipitation regions, more probable and likely subject to a bi‐stable and reversible regime in sub‐humid regions, and highly probable and irreversible in dry regions. Factors such as runoff, deep‐water drainage, fire, flammable/nonflammable biomass and overgrazing were considered as hypothetical transition mechanisms. As a novel finding, we demonstrate that ecohydrology, as a determinant of transition, is a factor that operates at a hierarchical level higher than that of the human‐driven disturbance. A synthetic graphical model was proposed to characterize resilience (the capacity of ecosystems to withstand transition) in the three study climatic regions. Copyright © 2014 John Wiley & Sons, Ltd.
Integrable Deformations from Twistor Space

Integrable field theories in two dimensions are known to originate as defect theories of 4d Chern-Simons and as symmetry reductions of the 4d anti-self-dual Yang-Mills equations. Based on ideas of Costello, it has been proposed in work of Bittleston and Skinner that these two approaches can be unified starting from holomorphic Chern-Simons in 6 dimensions. We provide the first complete description of this diamond of integrable theories for a family of deformed sigma models, going beyond the Dirichlet boundary conditions that have been considered thus far. Starting from 6d holomorphic Chern-Simons theory on twistor space with a particular meromorphic 3-form $\Omega$, we construct the defect theory to find a novel 4d integrable field theory, whose equations of motion can be recast as the 4d anti-self-dual Yang-Mills equations. Symmetry reducing, we find a multi-parameter 2d integrable model, which specialises to the $\lambda$-deformation at a certain point in parameter space. The same model is recovered by first symmetry reducing, to give 4d Chern-Simons with generalised boundary conditions, and then constructing the defect theory.
X-Rays from RS Ophiuchi’s 2021 Eruption: Shocks In and Out of Ionization Equilibrium

The recurrent nova RS Ophiuchi (RS Oph) underwent its most recent eruption on 2021 August 8 and became the first nova to produce both detectable GeV and TeV emission. We used extensive X-ray monitoring with the Neutron Star Interior Composition Explorer Mission (NICER) to model the X-ray spectrum and probe the shock conditions throughout the 2021 eruption. The rapidly evolving NICER spectra consisted of both line and continuum emission that could not be accounted for using a single-temperature collisional equilibrium plasma model with an absorber that fully covered the source. We successfully modeled the NICER spectrum as a nonequilibrium ionization collisional plasma with partial covering absorption. The temperature of the nonequilibrium plasma shows a peak on day 5 with a kT of approximately 24 keV. The increase in temperature during the first five days could have been due to increasing contribution to the X-ray emission from material behind fast polar shocks or a decrease is the amount of energy being drained from the shocks into particle acceleration during that period. The absorption showed a change from fully covering the source to having a covering fraction of roughly 0.4, suggesting a geometrical evolution of the shock region within the complex global distribution of the circumstellar material. These findings show evidence of the ejecta interacting with some dense equatorial shell initially, and with less dense material in the bipolar regions at later times during the eruption.
Third-generation-philic Hidden Naturalness

We present a solution to the electroweak hierarchy problem, where the relevant new particles are third-generation-philic and hidden in SM processes with third-generation fermions. Due to this feature, the mass bounds from direct searches are much weaker and the required fine-tuning can be reduced drastically. A concrete model is constructed based on a $SU(6)/Sp(6)$ fundamental composite Higgs model with collective symmetry breaking and extended hypercolor mechanism. The construction allows to raise the scale $f$ to $\sim 3\,$TeV, corresponding to resonances at $M_\rho \gtrsim 10$ TeV, without much tuning - employing ingredients that are naturally inherent in the (composite) Goldstone-Higgs framework. The experimental signatures are discussed in detail. It is found that current bounds allow for a model with negligible tuning.
Liquid inertia versus bubble cloud buoyancy in circular plunging jet experiments

Abstract When a liquid jet plunges into a pool, it can generate a bubble-laden jet flow underneath the surface. This common and simple phenomenon is investigated experimentally for circular jets to illustrate and quantify the role played by the net gas/liquid void fraction on the maximum bubble penetration depth. It is first shown that an increase in either the impact diameter or the jet fall height to diameter ratio at constant impact momentum leads to a reduction in the bubble cloud size. By measuring systematically the local void fraction using optical probes in the biphasic jet, it is then demonstrated that this effect is a direct consequence of the increase in air content within the cloud. A simple momentum balance model, including only inertia and the buoyancy force, is shown to predict the bubble cloud depth without any fitting parameters. Finally, a Froude number based on the bubble terminal velocity, the cloud depth and also the net void fraction is introduced to propose a simple criterion for the threshold between the inertia-dominated and buoyancy-dominated regimes.
A positivity preserving scheme for Poisson-Nernst-Planck Navier-Stokes equations and its error analysis

We consider in this paper a numerical approximation of Poisson-Nernst-Planck-Navier- Stokes (PNP-NS) system. We construct a decoupled semi-discrete and fully discrete scheme that enjoys the properties of positivity preserving, mass conserving, and unconditionally energy stability. Then, we establish the well-posedness and regularity of the initial and (periodic) boundary value problem of the PNP-NS system under suitable assumptions on the initial data, and carry out a rigorous convergence analysis for the fully discretized scheme. We also present some numerical results to validate the positivity-preserving property and the accuracy of our scheme.
A Pipeline For Discourse Circuits From CCG

There is a significant disconnect between linguistic theory and modern NLP practice, which relies heavily on inscrutable black-box architectures. DisCoCirc is a newly proposed model for meaning that aims to bridge this divide, by providing neuro-symbolic models that incorporate linguistic structure. DisCoCirc represents natural language text as a `circuit' that captures the core semantic information of the text. These circuits can then be interpreted as modular machine learning models. Additionally, DisCoCirc fulfils another major aim of providing an NLP model that can be implemented on near-term quantum computers. In this paper we describe a software pipeline that converts English text to its DisCoCirc representation. The pipeline achieves coverage over a large fragment of the English language. It relies on Combinatory Categorial Grammar (CCG) parses of the input text as well as coreference resolution information. This semantic and syntactic information is used in several steps to convert the text into a simply-typed $\lambda$-calculus term, and then into a circuit diagram. This pipeline will enable the application of the DisCoCirc framework to NLP tasks, using both classical and quantum approaches.
Model Performance Prediction for Hyperparameter Optimization of Deep Learning Models Using High Performance Computing and Quantum Annealing

Hyperparameter Optimization (HPO) of Deep Learning-based models tends to be a compute resource intensive process as it usually requires to train the target model with many different hyperparameter configurations. We show that integrating model performance prediction with early stopping methods holds great potential to speed up the HPO process of deep learning models. Moreover, we propose a novel algorithm called Swift-Hyperband that can use either classical or quantum support vector regression for performance prediction and benefit from distributed High Performance Computing environments. This algorithm is tested not only for the Machine-Learned Particle Flow model used in High Energy Physics, but also for a wider range of target models from domains such as computer vision and natural language processing. Swift-Hyperband is shown to find comparable (or better) hyperparameters as well as using less computational resources in all test cases.