Miracle-dz/UniFAR-FTUs huggingface dataset:
Competition between binding sites determines gene expression at low transcription factor concentrations

The response of gene expression to intra-and extra-cellular cues is largely mediated through changes in the activity of transcription factors (TFs), whose sequence specificities are largely known. However, the rules by which promoters decode the amount of active TF into gene expression are not well understood. Here, we measure the activity of 6500 designed promoters at six different levels of TF activity in budding yeast. We observe that maximum promoter activity is determined by TF activity and not by the number of sites. Surprisingly, the addition of an activator-binding site often reduces expression. A thermodynamic model that incorporates competition between neighboring binding sites for a local pool of TF molecules explains this behavior and accurately predicts both absolute expression and the amount by which addition of a site increases or reduces expression. Taken together, our findings support a model in which neighboring binding sites interact competitively when TF is limiting but otherwise act additively Significance Statement In response to intracellular and extracellular signals organisms alter the concentration and activity of transcription factors (TFs), proteins that regulate gene expression. However, the molecular mechanisms that determine the response of a target promoter to changes in the number of active TF molecules are not well understood. By combining mathematical modeling with measurements of TF dose-response curves for thousands of designed promoters, we show that competition for active TF molecules is a major factor in determining gene expression. At low TF concentrations additional activator-binding sites within a promoter can actually reduce expression. Thermodynamic modeling suggests that steric hindrance between neighboring binding sites cannot explain this behavior, but that competition for limiting TF molecules can.
Monitoring chest compression rate in automated external defibrillators using the autocorrelation of the transthoracic impedance

Aim High-quality chest compressions is challenging for bystanders and first responders to out-of-hospital cardiac arrest (OHCA). Long compression pauses and compression rates higher than recommended are common and detrimental to survival. Our aim was to design a simple and low computational cost algorithm for feedback on compression rate using the transthoracic impedance (TI) acquired by automated external defibrillators (AEDs). Methods ECG and TI signals from AED recordings of 242 OHCA patients treated by basic life support (BLS) ambulances were retrospectively analyzed. Beginning and end of chest compression series and each individual compression were annotated. The algorithm computed a biased estimate of the autocorrelation of the TI signal in consecutive non-overlapping 2-s analysis windows to detect the presence of chest compressions and estimate compression rate. Results A total of 237 episodes were included in the study, with a median (IQR) duration of 10 (6–16) min. The algorithm performed with a global sensitivity in the detection of chest compressions of 98.7%, positive predictive value of 98.7%, specificity of 97.1%, and negative predictive value of 97.1% (validation subset including 207 episodes). The unsigned error in the estimation of compression rate was 1.7 (1.3–2.9) compressions per minute. Conclusion Our algorithm is accurate and robust for real-time guidance on chest compression rate using AEDs. The algorithm is simple and easy to implement with minimal software modifications. Deployment of AEDs with this capability could potentially contribute to enhancing the quality of chest compressions in the first minutes from collapse.
Understanding the trade-off between the environment and fertility in cows and ewes

Abstract The environment contributes to production diseases that in turn badly affect cow performance, fertility and culling. Oestrus intensity is lower in lame cows, and in all cows 26% potential oestrus events are not expressed (to avoid getting pregnant). To understand these trade-offs, we need to know how animals react to their environment and how the environment influences hypothalamus-pituitary-adrenal axis (HPA) interactions with the hypothalamus-pituitary-ovarian axis (HPO). Neurotransmitters control secretion of GnRH into hypophyseal portal blood. GnRH/LH pulse amplitude and frequency drive oestradiol production, culminating in oestrus behaviour and a precisely-timed GnRH/LH surge, all of which are disrupted by poor environments. Responses to peripheral neuronal agents give clues about mechanisms, but do these drugs alter perception of stimuli, or suppress consequent responses? In vitro studies confirm some neuronal interactions between the HPA and HPO; and immuno-histochemistry clarifies the location and sequence of inter-neurone activity within the brain. In both species, exogenous corticoids, ACTH and/or CRH act at the pituitary (reduce LH release by GnRH), and hypothalamus (lower GnRH pulse frequency and delay surge release). This requires inter-neurones as GnRH cells do not have receptors for HPA compounds. There are two (simultaneous, therefore fail-safe? ) pathways for CRH suppression of GnRH release via CRH-Receptors: one being the regulation of kisspeptin/dynorphin and other cell types in the hypothalamus, and the other being the direct contact between CRH and GnRH cell terminals in the median eminence. When we domesticate animals, we must provide the best possible environment otherwise animals trade-off with lower production, less intense oestrus behaviour, and impaired fertility. Avoiding life-time peri-parturient problems by managing persistent lactations in cows may be a worthy trade-off on both welfare and economic terms – better than the camouflage use of drugs/hormones/feed additives/intricate technologies? In the long term, getting animals and environment in a more harmonious balance is the ultimate strategy.
Bioactive Compounds and Antioxidant, Antiperoxidative, and Antihemolytic Properties Investigation of Three Apiaceae Species Grown in the Southeast of Morocco

For a long time, Apiaceae species have been widely employed in the southeast of Morocco for culinary and folk healing purposes. In the current study, we investigated three Apiaceae herbs known as coriander (Coriandrum sativum), celery (Apium graveolens), and parsley (Petroselinum crispum) for their antioxidant, antiperoxidative, and antihemolytic properties. The HPLC-DAD has been used to classify and measure phenolic compounds. The major phenolic compounds studied were p-coumaric, chlorogenic, caffeic acids, luteolin, and quercetin. The polyphenol level was also estimated via Folin–Ciocalteu's method, aluminium chloride, and acidified vanillin. Parsley showed the highest polyphenol level and, thus, showed potential antioxidant activities demonstrated by DPPH, ABTS scavenging tests, and reducing power (FRAP), as well as TBARS assays. Very strong correlations were depicted among phenol levels and antioxidant assays (R2 ≥ 0.910) and among antihemolytic activity and flavonoids (R2 ≥ 0.927), indicating the implication of phenolic compounds, mainly flavonoids, in the antiradical properties. These finding may prove the traditional use of these Apiaceae species in the management of numerous disorders cited within the Moroccan pharmacopoeia.
New approaches to diagnose and target reproductive failure in cattle

Abstract Reproductive failure and pregnancy loss in cattle are some of the largest economic burdens to cattle producers and one of most perplexing factors influencing management decisions. Pregnancy loss may occur at any point during gestation with the largest percentage of loss occurring in the first 30 days and, subsequently, decreasing as the pregnancy progresses. Losses may be attributed to numerous factors, predisposed issues or environmental conditions such as nutritional stressors or disease. From a research perspective, determining the exact causes of pregnancy loss or embryonic mortality in cattle have been difficult, due to limitations of accurately determining early gestation pregnancy status. Until methods that precisely determine embryo success early in gestation are available, our understanding of in vivo pregnancy loss will lack clarity necessary to develop management strategies to decrease such loss. In this review, we will briefly discuss the pivotal periods of pregnancy loss affecting beef and dairy cattle, methods and technologies to determine pregnancy status and embryo viability and potential opportunities to decrease reproductive failure.
The Application of Mechanical Stimulations in Tendon Tissue Engineering

Tendon injury is the most common disease in the musculoskeletal system. The current treatment methods have many limitations, such as poor therapeutic effects, functional loss of donor site, and immune rejection. Tendon tissue engineering provides a new treatment strategy for tendon repair and regeneration. In this review, we made a retrospective analysis of applying mechanical stimulation in tendon tissue engineering, and its potential as a direction of development for future clinical treatment strategies. For this purpose, the following topics are discussed; (1) the context of tendon tissue engineering and mechanical stimulation; (2) the applications of various mechanical stimulations in tendon tissue engineering, as well as their inherent mechanisms; (3) the application of magnetic force and the synergy of mechanical and biochemical stimulation. With this, we aim at clarifying some of the main questions that currently exist in the field of tendon tissue engineering and consequently gain new knowledge that may help in the development of future clinical application of tissue engineering in tendon injury.
Effect of Massa Medicata Fermentata on the Gut Microbiota of Dyspepsia Mice Based on 16S rRNA Technique

Massa Medicata Fermentata (MMF) is a traditional Chinese medicine (TCM) for treating indigestion and its related disorders. This study analyzes the effect of MMF on intestinal microorganisms in dyspepsia mice based on 16S rRNA technology. We take a dyspepsia model caused by a high-protein, high-calorie, high-fat diet. The 60 specific-pathogen free Kunming (SPF KM) mice were randomly divided into a model group (n=12), an MMF group (LSQ group, n=12), a Jianweixiaoshi group (JWXS group, n=12), a domperidone group (DP group, n=12), and a blank group (n=12). On the seventh day of administration, mice were fasted and deprived of water. After 24 h, take the second feces of stress defecation in mice under strict aseptic conditions and quickly transfer them to a sterile cryotube. This study comprehensively evaluates the α-diversity, β-diversity, flora abundance and composition of each group of miceʼs intestinal microorganisms, and their correlation with functional dyspepsia based on the 16S rRNA gene sequencing technology. After modeling, some dyspepsia reactions, proximal gastric relaxation reduction, and intestinal microflora changes were noted. Dyspepsia mice showed dyspepsia reactions and proximal gastric relaxation reduction, characterized by a significant decrease of contents of gastrin (P < 0.01) and cholinesterase (P < 0.01). MMF can improve dyspepsia symptoms and promote proximal gastric relaxation. Significant intestinal flora disorders were found in dyspepsia mice, including downregulation of Bacteroidetes, Lactobacillus, and Prevotellaceae and upregulation of Proteobacteria, Verrucomicrobia, Epsilonbacteraeota, Firmicutes, Lachnospiraceae NK4A136 group, and Lachnospiraceae. MMF could alleviate intestinal microflora disturbance, and the regulation effect of MMF on Bacteroidetes, Verrucomicrobia, and Epsilonbacteraeota was more reliable than that of Jianweixiaoshi tables and domperidone. The intestinal microflora may be correlated with the promoted digestion of MMF.
DL-DP: Improving the Security of Industrial IoT with Decentralized Ledger Defined Perimeter

The adoption of industrial internet of things (IIoT) greatly improves the efficiency of industrial facilities by providing more accurate and rich information and increasing automation. The benefits are further amplified when IIoT is integrated with cloud for collaboration and data analytic capability. Modern IIoT systems are highly dynamic and usually owned by multiple parties that need to collaborate with each other. These features make it harder to manage the system, and previous protection mechanisms such as physical separation and network isolation are not applicable any more. To mitigate the security risks without sacrificing the benefits of IIoT, we propose DL-DP, the decentralized ledger defined perimeter for IIoT. DL-DP introduces the concept of perimeter for IIoT resources management and isolation, and utilizes a novel hierarchy structure of decentralized ledger to effectively support a large number of IIoT devices and related cloud services. DL-DP provides a rich set of security functions including access control, denial-of-service mitigation and auditability. We also evaluate the performance with a prototype of DL-DP to demonstrate its practicability.
SmartWitness: A Proactive Software Transparency System using Smart Contracts

Package managers have become essential for software distribution and management. Their goal is to allow users to install programs, drivers, or updates in their systems in a secure, quick, and often, unattended way. However, in recent years, attackers have found severe flaws in software distribution systems and used them as a stealthy launch pad for malicious software. Moreover, it was proved that actors of the software supply-chain are ineffective in detecting and stopping attacks on user devices. In this paper, we present a design for software distribution systems based on distributed ledgers. By replacing traditional code signing certificates with smart contracts, named SmartWitness, we propose a novel system that provides properties of binary transparency, useful and granular package revocation, and dynamic and proactive security assessment improving risk awareness of end users. SmartWitness keeps all actors transparent and accountable, and it enables security providers to participate earlier in the software distribution process, directly influencing package installations on user devices. We show how SmartWitness is integrated into an existing package manager system, and we present results from conducted experiments indicating that the system is practical as for today.
Smoother Network Tuning and Interpolation for Continuous-level Image Processing

In Convolutional Neural Network (CNN) based image processing, most studies propose networks that are optimized to single-level (or single-objective); thus, they underperform on other levels and must be retrained for delivery of optimal performance. Using multiple models to cover multiple levels involves very high computational costs. To solve these problems, recent approaches train networks on two different levels and propose their own interpolation methods to enable arbitrary intermediate levels. However, many of them fail to generalize or have certain side effects in practical usage. In this paper, we define these frameworks as network tuning and interpolation and propose a novel module for continuous-level learning, called Filter Transition Network (FTN). This module is a structurally smoother module than existing ones. Therefore, the frameworks with FTN generalize well across various tasks and networks and cause fewer undesirable side effects. For stable learning of FTN, we additionally propose a method to initialize non-linear neural network layers with identity mappings. Extensive results for various image processing tasks indicate that the performance of FTN is comparable in multiple continuous levels, and is significantly smoother and lighter than that of other frameworks.
Dealing with multiple testing: To adjust or not to adjust

Multiple testing problems arise naturally in scientific studies because of the need to capture or convey more information with more variables. The literature is enormous, but the emphasis is primarily methodological, providing numerous methods with their mathematical justification and practical implementation. Our aim is to highlight the logical issues involved in the application of multiple testing adjustment.
A Unifying View on Implicit Bias in Training Linear Neural Networks

We study the implicit bias of gradient flow (i.e., gradient descent with infinitesimal step size) on linear neural network training. We propose a tensor formulation of neural networks that includes fully-connected, diagonal, and convolutional networks as special cases, and investigate the linear version of the formulation called linear tensor networks. For $L$-layer linear tensor networks that are orthogonally decomposable, we show that gradient flow on separable classification finds a stationary point of the $\ell_{2/L}$ max-margin problem in a "transformed" input space defined by the network. For underdetermined regression, we prove that gradient flow finds a global minimum which minimizes a norm-like function that interpolates between weighted $\ell_1$ and $\ell_2$ norms in the transformed input space. Our theorems subsume existing results in the literature while removing most of the convergence assumptions. We also provide experiments that corroborate our analysis.
Animal Cell Cytokinesis: The Rho-Dependent Actomyosin-Anilloseptin Contractile Ring as a Membrane Microdomain Gathering, Compressing, and Sorting Machine

Cytokinesis is the last step of cell division that partitions the cellular organelles and cytoplasm of one cell into two. In animal cells, cytokinesis requires Rho-GTPase-dependent assembly of F-actin and myosin II (actomyosin) to form an equatorial contractile ring (CR) that bisects the cell. Despite 50 years of research, the precise mechanisms of CR assembly, tension generation and closure remain elusive. This hypothesis article considers a holistic view of the CR that, in addition to actomyosin, includes another Rho-dependent cytoskeletal sub-network containing the scaffold protein, Anillin, and septin filaments (collectively termed anillo-septin). We synthesize evidence from our prior work in Drosophila S2 cells that actomyosin and anillo-septin form separable networks that are independently anchored to the plasma membrane. This latter realization leads to a simple conceptual model in which CR assembly and closure depend upon the micro-management of the membrane microdomains to which actomyosin and anillo-septin sub-networks are attached. During CR assembly, actomyosin contractility gathers and compresses its underlying membrane microdomain attachment sites. These microdomains resist this compression, which builds tension. During CR closure, membrane microdomains are transferred from the actomyosin sub-network to the anillo-septin sub-network, with which they flow out of the CR as it advances. This relative outflow of membrane microdomains regulates tension, reduces the circumference of the CR and promotes actomyosin disassembly all at the same time. According to this hypothesis, the metazoan CR can be viewed as a membrane microdomain gathering, compressing and sorting machine that intrinsically buffers its own tension through coordination of actomyosin contractility and anillo-septin-membrane relative outflow, all controlled by Rho. Central to this model is the abandonment of the dogmatic view that the plasma membrane is always readily deformable by the underlying cytoskeleton. Rather, the membrane resists compression to build tension. The notion that the CR might generate tension through resistance to compression of its own membrane microdomain attachment sites, can account for numerous otherwise puzzling observations and warrants further investigation using multiple systems and methods.
Efficient One-Pass End-to-End Entity Linking for Questions

We present ELQ, a fast end-to-end entity linking model for questions, which uses a biencoder to jointly perform mention detection and linking in one pass. Evaluated on WebQSP and GraphQuestions with extended annotations that cover multiple entities per question, ELQ outperforms the previous state of the art by a large margin of +12.7% and +19.6% F1, respectively. With a very fast inference time (1.57 examples/s on a single CPU), ELQ can be useful for downstream question answering systems. In a proof-of-concept experiment, we demonstrate that using ELQ significantly improves the downstream QA performance of GraphRetriever (arXiv:1911.03868). Code and data available at this https URL
Cerebral Perfusion Effects of Cognitive Training and Transcranial Direct Current Stimulation in Mild-Moderate TBI

Background: Persistent post-traumatic symptoms (PPS) after traumatic brain injury (TBI) can lead to significant chronic functional impairment. Pseudocontinuous arterial spin labeling (pCASL) has been used in multiple studies to explore changes in cerebral blood flow (CBF) that may result in acute and chronic TBI, and is a promising neuroimaging modality for assessing response to therapies. Methods: Twenty-four subjects with chronic mild-moderate TBI (mmTBI) were enrolled in a pilot study of 10 days of computerized executive function training combined with active or sham anodal transcranial direct current stimulation (tDCS) for treatment of cognitive PPS. Behavioral surveys, neuropsychological testing, and magnetic resonance imaging (MRI) with pCASL sequences to assess global and regional CBF were obtained before and after the training protocol. Results: Robust improvements in depression, anxiety, complex attention, and executive function were seen in both active and sham groups between the baseline and post-treatment visits. Global CBF decreased over time, with differences in regional CBF noted in the right inferior frontal gyrus (IFG). Active stimulation was associated with static or increased CBF in the right IFG, whereas sham was associated with reduced CBF. Neuropsychological performance and behavioral symptoms were not associated with changes in CBF. Discussion: The current study suggests a complex picture between mmTBI, cerebral perfusion, and recovery. Changes in CBF may result from physiologic effect of the intervention, compensatory neural mechanisms, or confounding factors. Limitations include a small sample size and heterogenous injury sample, but these findings suggest promising directions for future studies of cognitive training paradigms in mmTBI.
Isolation and Molecular Characterization of Shiga Toxin-Producing Escherichia Coli in Beef Retail Markets -

Shiga toxin-producing Escherichia coli (STEC) are foodborn pathogens cause mild to serious diseases, leading to people death. This study reports the prevalence and characterization of STEC O157 and non-O157 in beef retail markets (commercial ground beef and instruments samples: meat tables, knives, meat mincing machines) obtained from 25 retail markets in Kafer El-sheikh governorate. The STEC isolates were serotyped and virulence genes as stx1 (Shiga toxin 1), stx2 (Shiga toxin 2) and eae (intimin) were determined. STEC O157 were identified in 11 (14.6 %) of raw beef samples and 8 (10.6%) in instruments samples, while STEC non-O157 (O128, O78, O111, O26 and O119) were present in 6(8%) in raw beef samples and 9 (12%) in instruments samples. Among strains isolated , the prevalent genotype for O157 were stx1,stx2and eae while for STEC non-O157 were stx1 , stx2 and eae in O111, stx1 and stx2 in O26 , stx1 in O128 and O119 , stx2 in O78 . In conclusion, cross-contamination between meat and the environment could be suspected.