Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple in vivo roles for the C-terminal domain of the RNA chaperone Hfq

Hfq, a bacterial RNA chaperone, stabilizes small regulatory RNAs (sRNAs) and facilitates sRNA base-pairing with target mRNAs. Hfq has a conserved N-terminal domain and a poorly conserved disordered C-terminal domain (CTD). In a transcriptome-wide examination of the effects of a chromosomal CTD deletion (Hfq1-65), the Escherichia coli mutant was most defective for the accumulation of sRNAs that bind the proximal and distal faces of Hfq (Class II sRNAs), but other sRNAs also were affected. There were only modest effects on the levels of mRNAs, suggesting little disruption of sRNA-dependent regulation. However, cells expressing Hfq lacking the CTD deletion in combination with a weak distal face mutation were defective for the function of the Class II sRNA ChiX and repression of mutS, both dependent upon distal face RNA binding. Loss of the region between amino acids 66-72 was critical for this defect. The CTD region beyond amino acid 72 was not necessary for distal face-dependent regulation, but was needed for functions associated with the Hfq rim, seen most clearly in combination with a rim mutant. Our results suggest that the C-terminus collaborates in various ways with different binding faces of Hfq, leading to distinct outcomes for individual sRNAs.
Large-Scale Landslide Susceptibility Mapping Using an Integrated Machine Learning Model: A Case Study in the Lvliang Mountains of China

Integration of different models may improve the performance of landslide susceptibility assessment, but few studies have tested it. The present study aims at exploring the way to integrating different models and comparing the results among integrated and individual models. Our objective is to answer this question: Will the integrated model have higher accuracy compared with individual model? The Lvliang mountains area, a landslide-prone area in China, was taken as the study area, and ten factors were considered in the influencing factors system. Three basic machine learning models (the back propagation (BP), support vector machine (SVM), and random forest (RF) models) were integrated by an objective function where the weight coefficients among different models were computed by the gray wolf optimization (GWO) algorithm. 80 and 20% of the landslide data were randomly selected as the training and testing samples, respectively, and different landslide susceptibility maps were generated based on the GIS platform. The results illustrated that the accuracy expressed by the area under the receiver operating characteristic curve (AUC) of the BP-SVM-RF integrated model was the highest (0.7898), which was better than that of the BP (0.6929), SVM (0.6582), RF (0.7258), BP-SVM (0.7360), BP-RF (0.7569), and SVM-RF models (0.7298). The experimental results authenticated the effectiveness of the BP-SVM-RF method, which can be a reliable model for the regional landslide susceptibility assessment of the study area. Moreover, the proposed procedure can be a good option to integrate different models to seek an “optimal” result.
What Is An Artificial Neural Network And Why Do We Need It?

Your brain controls everything you do, and it is much more powerful than any computer you can find. This complex organ sends messages using cells called neurons, and it never stops analyzing data, even as you sleep. Scientists are trying to understand the brain to create a digital version. But is it possible for computers to do the same things our brains can? For computers to do so, we need to create something called an artificial neural network, which has digital neurons connected into a complex net that resembles the structure of the brain. To make an artificial neural network, we need to use the most universal language—mathematics.
Microbiological Surveillance of Biogas Plants: Targeting Acetogenic Community

Acetogens play a very important role in anaerobic digestion and are essential in ensuring process stability. Despite this, targeted studies of the acetogenic community in biogas processes remain limited. Some efforts have been made to identify and understand this community, but the lack of a reliable molecular analysis strategy makes the detection of acetogenic bacteria tedious. Recent studies suggest that screening of bacterial genetic material for formyltetrahydrofolate synthetase (FTHFS), a key marker enzyme in the Wood-Ljungdahl pathway, can give a strong indication of the presence of putative acetogens in biogas environments. In this study, we applied an acetogen-targeted analyses strategy developed previously by our research group for microbiological surveillance of commercial biogas plants. The surveillance comprised high-throughput sequencing of FTHFS gene amplicons and unsupervised data analysis with the AcetoScan pipeline. The results showed differences in the acetogenic community structure related to feed substrate and operating parameters. They also indicated that our surveillance method can be helpful in the detection of community changes before observed changes in physico-chemical profiles, and that frequent high-throughput surveillance can assist in management towards stable process operation, thus improving the economic viability of biogas plants. To our knowledge, this is the first study to apply a high-throughput microbiological surveillance approach to visualise the potential acetogenic population in commercial biogas digesters.
Genomic Variation Landscape of the Model Salt Cress Eutrema salsugineum

Eutrema salsugineum has long been used as the model for examining salt and other abiotic stress in plants. In addition to the forward genetics approaches widely used in the lab, natural variations undoubtedly will provide a rich genetic resource for studying molecular mechanisms underlying the stress tolerance and local adaptation of this species. We used 90 resequencing whole genomes of natural populations of this species across its Asian and North American distributions to detect the selection signals for genes involved in salt and other stresses at the species-range level and local distribution. We detected selection signals for genes involved in salt and other abiotic tolerance at the species level. In addition, several cold-induced and defense genes showed selection signals due to local adaptation in North America-NE Russia or northern China, respectively. These variations and findings provide valuable resources for further deciphering genetic mechanisms underlying the stress tolerance and local adaptations of this model species.
Reef Conservation off the Hook: Can Market Interventions Make Coral Reef Fisheries More Sustainable?

The overexploitation of coral reef fisheries threatens the persistence of reef ecosystems and the livelihoods and food security of millions of people. Market-based initiatives to increase fisheries sustainability have been widely implemented in industrialized commodity fisheries, but the suitability of these initiatives for coral reef fisheries has not been systematically investigated. Here, we present a typology of market-based interventions and coral reef fisheries sectors and identity promising approaches for each fishery archetype. For high value, export-oriented reef fisheries that are highly unsustainable (live reef food fish and dried sea cucumbers), traditional regulatory efforts including trade restrictions will be most effective. For high-value, export-oriented fisheries for highly fecund invertebrates (lobsters and mollusks), certification and ratings efforts, fishery improvement projects, and sustainable purchasing commitments can improve fishing practices and increase fisher market access and revenue. For lower-value fisheries targeting species for domestic or regional consumption, sustainable purchasing commitments among local buyers, consumer awareness campaigns, and local certification and ratings schemes hold promise for shifting attitudes toward sustainability and increasing food security for local communities. Finally, fisher empowerment efforts including direct access to local markets and market information, training on improved post-harvest methods, and formation of fisher associations hold promise for increasing fisher incomes, reducing wasteful catch, increasing food security, and de-incentivizing unsustainable practices. Despite the potential of market-based interventions, specific approaches must be carefully tailored to the ecological and social reality of these systems, including the inherent unsustainability of commercial coral reef fisheries, the limited capacity for fisheries governance, the limited financial support of market-based initiatives, and the threatened status of coral reef ecosystems globally.
Coronary Magnetic Resonance Angiography in Chronic Coronary Syndromes

Cardiovascular disease is the leading cause of mortality worldwide, with atherosclerotic coronary artery disease (CAD) accounting for the majority of cases. X-ray coronary angiography and computed tomography coronary angiography (CCTA) are the imaging modalities of choice for the assessment of CAD. However, the use of ionising radiation and iodinated contrast agents remain drawbacks. There is therefore a clinical need for an alternative modality for the early identification and longitudinal monitoring of CAD without these associated drawbacks. Coronary magnetic resonance angiography (CMRA) could be a potential alternative for the detection and monitoring of coronary arterial stenosis, without exposing patients to ionising radiation or iodinated contrast agents. Further advantages include its versatility, excellent soft tissue characterisation and suitability for repeat imaging. Despite the early promise of CMRA, widespread clinical utilisation remains limited due to long and unpredictable scan times, onerous scan planning, lower spatial resolution, as well as motion related image quality degradation. The past decade has brought about a resurgence in CMRA technology, with significant leaps in image acceleration, respiratory and cardiac motion estimation and advanced motion corrected or motion-resolved image reconstruction. With the advent of artificial intelligence, great advances are also seen in deep learning-based motion estimation, undersampled and super-resolution reconstruction promising further improvements of CMRA. This has enabled high spatial resolution (1 mm isotropic), 3D whole heart CMRA in a clinically feasible and reliable acquisition time of under 10 min. Furthermore, latest super-resolution image reconstruction approaches which are currently under evaluation promise acquisitions as short as 1 min. In this review, we will explore the recent technological advances that are designed to bring CMRA closer to clinical reality.
Targeting the Microtubule-Network Rescues CTL Killing Efficiency in Dense 3D Matrices

Efficacy of cytotoxic T lymphocyte (CTL)-based immunotherapy is still unsatisfactory against solid tumors, which are frequently characterized by condensed extracellular matrix. Here, using a unique 3D killing assay, we identify that the killing efficiency of primary human CTLs is substantially impaired in dense collagen matrices. Although the expression of cytotoxic proteins in CTLs remained intact in dense collagen, CTL motility was largely compromised. Using light-sheet microscopy, we found that persistence and velocity of CTL migration was influenced by the stiffness and porosity of the 3D matrix. Notably, 3D CTL velocity was strongly correlated with their nuclear deformability, which was enhanced by disruption of the microtubule network especially in dense matrices. Concomitantly, CTL migration, search efficiency, and killing efficiency in dense collagen were significantly increased in microtubule-perturbed CTLs. In addition, the chemotherapeutically used microtubule inhibitor vinblastine drastically enhanced CTL killing efficiency in dense collagen. Together, our findings suggest targeting the microtubule network as a promising strategy to enhance efficacy of CTL-based immunotherapy against solid tumors, especially stiff solid tumors.
A Diffusion Model for Cyclic Voltammetry with Nanostructured Electrode Surfaces

iii DEDICATION . v ACKNOWLEDGMENTS . vi LIST OF FIGURES . ix LIST OF TABLES . x LIST OF ABBREVIATIONS AND NOTATION . xi CHAPTER 1: INTRODUCTION . 1 Common Electrode Nanostructures . 3 Applications of Nanostructured Electrodes . 4 Electrodes for Fuel Cells . 4 Electrodes for Sensors. 4 Electrodes for Batteries . 5 Electrodes for Supercapacitors . 5 CHAPTER 2: MODEL BACKGROUND . 7 The Nicholson Model of Voltammetry for a Diffusion Limited System. 8 Laviron’s Model of Voltammetry for a Kinetically Limited System . 10
Targeted Therapy as a Potential De-Escalation Strategy in Locally Advanced HPV-Associated Oropharyngeal Cancer: A Literature Review

The treatment landscape of locally advanced HPV-oropharyngeal squamous cell carcinoma (OPSCC) is undergoing transformation. This is because the high cures rates observed in OPSCC are paired with severe treatment-related, long-term toxicities. These significant adverse effects have led some to conclude that the current standard of care is over-treating patients, and that de-intensifying the regimens may achieve comparable survival outcomes with lower toxicities. Consequently, several de-escalation approaches involving locally advanced OPSCC are underway. These include the reduction of dosage and volume of intensive cytotoxic regimens, as well as elimination of invasive surgical procedures. Such de-intensifying treatments have the potential to achieve efficacy and concurrently alleviate morbidity. Targeted therapies, given their overall safer toxicity profiles, also make excellent candidates for de-escalation, either alone or alongside standard treatments. However, their role in these endeavors is currently limited, because few targeted therapies are currently in clinical use for head and neck cancers. Unfortunately, cetuximab, the only FDA-approved targeted therapy, has shown inferior outcomes when paired with radiation as compared to cisplatin, the standard radio-sensitizer, in recent de-escalation trials. These findings indicate the need for a better understanding of OPSCC biology in the design of rational therapeutic strategies and the development of novel, OPSCC-targeted therapies that are safe and can improve the therapeutic index of standard therapies. In this review, we summarize ongoing research on mechanism-based inhibitors in OPSCC, beginning with the salient molecular features that modulate tumorigenic processes and response, then exploring pharmacological inhibition and pre-clinical validation studies of candidate targeted agents, and finally, summarizing the progression of those candidates in the clinic.
Phylogenetic Occurrence of the Phenylpropanoid Pathway and Lignin Biosynthesis in Plants

The phenylpropanoid pathway serves as a rich source of metabolites in plants and provides precursors for lignin biosynthesis. Lignin first appeared in tracheophytes and has been hypothesized to have played pivotal roles in land plant colonization. In this review, we summarize recent progress in defining the lignin biosynthetic pathway in lycophytes, monilophytes, gymnosperms, and angiosperms. In particular, we review the key structural genes involved in p-hydroxyphenyl-, guaiacyl-, and syringyl-lignin biosynthesis across plant taxa and consider and integrate new insights on major transcription factors, such as NACs and MYBs. We also review insight regarding a new transcriptional regulator, 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase, canonically identified as a key enzyme in the shikimate pathway. We use several case studies, including EPSP synthase, to illustrate the evolution processes of gene duplication and neo-functionalization in lignin biosynthesis. This review provides new insights into the genetic engineering of the lignin biosynthetic pathway to overcome biomass recalcitrance in bioenergy crops.
Agonistic Behavior Is Affected by Memory in the Dusky Damselfish Stegastes fuscus

The ability to discriminate familiar from unfamiliar conspecifics has been demonstrated in several species of fish. Agonistic interactions are among the most frequent behaviors exhibited by territorial species and could offer useful information for the individual recognition process. In agonistic situations, memory may modulate the behavioral response and affect social dynamics, but few studies have explored the memory retention acquired during aggressive encounters. The present study investigated the memory retention of an agonistic encounter in the dusky damselfish Stegastes fuscus. The experimental procedure was divided into three parts: (1) Familiarization; (2) Recognition test; and (3) Memory test. During the familiarization phase, the fish were visually exposed to the same conspecific for 5 days (10 min per day) and the behavior was recorded. On the following day (conspecific recognition test), half of the animals were paired with the same conspecific and the other half with a different conspecific for 10 min, and the behavior was recorded. The fish were retested 5, 10, and 15 days after the test to evaluate memory retention. In the memory test, they were exposed to the same conspecific as before or to a different conspecific. We found that the damselfish reduced their agonistic displays when the stimulus fish was familiar, but when it was unfamiliar, the animals were more aggressive and only reduced their mnemonic response after 10 days. These results suggest that the recognition ability of damselfish can be affected by time and that it modulates agonistic response.
Indoor Visible Light Applications for Communication, Positioning, and Security

With the rapid development of smart cities, white light-emitting diodes (LEDs) are widely used in indoor lighting due to their characteristics of energy-saving, long lifetimes, and low cost. At the same time, the high-frequency modulated LEDs allow visible light to be used for indoor communications, positioning, and security. Visible light applications have many advantages, such as avoiding electromagnetic interference, high communication speed, great privacy, and high-precise positioning. In this paper, we will survey the application prospects and research results of visible light from scenarios such as high-speed communication, privacy security, and navigation localization and focus on analyzing and discussing the challenges and development trends encountered in visible light positioning.
Differentially Expressed Functional LncRNAs in Human Subjects With Metabolic Syndrome Reflect a Competing Endogenous RNA Network in Circulating Extracellular Vesicles

Metabolic syndrome (MetS), a collective cluster of disease risk factors that include dyslipidemia, obesity, inflammation, hypertension, and insulin resistance, affects numerous people worldwide. Accumulating studies have shown that long non-coding RNAs (lncRNAs) serve as competing endogenous RNAs (ceRNAs) to play essential roles in regulating gene expression in various diseases. To explore the role of lncRNAs as ceRNAs in MetS, we examined a MetS-associated network in circulating extracellular vesicles (EVs) collected from the systemic blood of MetS and control patients (n = 5 each). In total, 191 differentially expressed lncRNAs, 1,389 mRNAs, and 138 miRNAs were selected for further analysis. Biological processes and pathway functional enrichment analysis were performed based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The lncRNA/mRNA/miRNA ceRNA network was constructed by Cytoscape v3.8 based on the DE-RNAs and included 13 lncRNAs, 8 miRNAs, and 64 mRNAs. MetS patients showed elevated body weight, glucose, blood pressure, insulin, liver injury, and inflammatory marker levels. We found that lncRNAs reflect a ceRNA network that may regulate central cellular processes and complications of MetS, including cancer. These findings suggest that MetS alters the interactions among the ceRNA network components in circulating EVs and that this cargo of circulating EVs may have potential translational ramifications for MetS.
Prefrontal tDCS Attenuates Self-Referential Attentional Deployment: A Mechanism Underlying Adaptive Emotional Reactivity to Social-Evaluative Threat

Social-evaluative threat (SET) – a situation in which one could be negatively evaluated by others – elicits profound (psycho)physiological reactivity which, if chronically present and not adaptively regulated, has deleterious effects on mental and physical health. Decreased self-awareness and increased other-awareness are understood to be an adaptive response to SET. Attentional deployment – the process of selectively attending to certain aspects of emotional stimuli to modulate emotional reactivity – is supported by fronto-parietal and fronto-limbic networks, with the dorsolateral prefrontal cortex being a central hub. The primary aim of the current study was to investigate the effects of active (versus sham) prefrontal transcranial direct current stimulation (tDCS) on self and other-attentional deployment during the exposure to a SET context. Seventy-four female participants received active or sham tDCS and were subsequently exposed to a rigged social feedback paradigm. In this paradigm a series of social evaluations were presented together with a photograph of the supposed evaluator and a self- photograph of the participant, while gaze behavior (time to first fixation, total fixation time) and skin conductance responses (SCRs; a marker of emotional reactivity) were measured. For half of the evaluations, participants could anticipate the valence (negative or positive) of the evaluation a priori. Analyses showed that participants receiving active tDCS were (a) slower to fixate on their self-photograph, (b) spent less time fixating on their self-photograph, and (c) spent more time fixating on the evaluator photograph. During unanticipated evaluations, active tDCS was associated with less time spent fixating on the evaluation. Furthermore, among those receiving active tDCS, SCRs were attenuated as a function of slower times to fixate on the self-photograph. Taken together, these results suggest that in a context of SET, prefrontal tDCS decreases self-attention while increasing other-attention, and that attenuated self-referential attention specifically may be a neurocognitive mechanism through which tDCS reduces emotional reactivity. Moreover, the results suggest that tDCS reduces vigilance toward stimuli that possibly convey threatening information, corroborating past research in this area.