Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial and Ecological Drivers of Genetic Structure in Greek Populations of Alkanna tinctoria (Boraginaceae), a Polyploid Medicinal Herb

Background and Aims: Quantifying genetic variation is fundamental to understand a species’ demographic trajectory and its ability to adapt to future changes. In comparison with diploids, however, genetic variation and factors fostering genetic divergence remain poorly studied in polyploids due to analytical challenges. Here, by employing a ploidy-aware framework, we investigated the genetic structure and its determinants in polyploid Alkanna tinctoria (Boraginaceae), an ancient medicinal herb that is the source of bioactive compounds known as alkannin and shikonin (A/S). From a practical perspective, such investigation can inform biodiversity management strategies. Methods: We collected 14 populations of A. tinctoria within its main distribution range in Greece and genotyped them using restriction site-associated DNA sequencing. In addition, we included two populations of A. sieberi. By using a ploidy-aware genotype calling based on likelihoods, we generated a dataset of 16,107 high-quality SNPs. Classical and model-based analysis was done to characterize the genetic structure within and between the sampled populations, complemented by genome size measurements and chromosomal counts. Finally, to reveal the drivers of genetic structure, we searched for associations between allele frequencies and spatial and climatic variables. Key Results: We found support for a marked regional structure in A. tinctoria along a latitudinal gradient in line with phytogeographic divisions. Several analyses identified interspecific admixture affecting both mainland and island populations. Modeling of spatial and climatic variables further demonstrated a larger contribution of neutral processes and a lesser albeit significant role of selection in shaping the observed genetic structure in A. tinctoria. Conclusion: Current findings provide evidence of strong genetic structure in A. tinctoria mainly driven by neutral processes. The revealed natural genomic variation in Greek Alkanna can be used to further predict variation in A/S production, whereas our bioinformatics approach should prove useful for the study of other non-model polyploid species.
Quantification of Viable Brochothrix thermosphacta in Cold-Smoked Salmon Using PMA/PMAxx-qPCR

The aim of this study was to develop a rapid and accurate PMA-qPCR method to quantify viable Brochothrix thermosphacta in cold-smoked salmon. B. thermosphacta is one of the main food spoilage bacteria. Among seafood products, cold-smoked salmon is particularly impacted by B. thermosphacta spoilage. Specific and sensitive tools that detect and quantify this bacterium in food products are very useful. The culture method commonly used to quantify B. thermosphacta is time-consuming and can underestimate cells in a viable but not immediately culturable state. We designed a new PCR primer set from the single-copy rpoC gene. QPCR efficiency and specificity were compared with two other published primer sets targeting the rpoC and rpoB genes. The viability dyes PMA or PMAxx were combined with qPCR and compared with these primer sets on viable and dead B. thermosphacta cells in BHI broth and smoked salmon tissue homogenate (SSTH). The three primer sets displayed similar specificity and efficiency. The efficiency of new designed rpoC qPCR on viable B. thermosphacta cells in SSTH was 103.50%, with a linear determination coefficient (r2) of 0.998 and a limit of detection of 4.04 log CFU/g. Using the three primer sets on viable cells, no significant difference was observed between cells treated or untreated with PMA or PMAxx. When dead cells were used, both viability dyes suppressed DNA amplification. Nevertheless, our results did not highlight any difference between PMAxx and PMA in their efficiency to discriminate viable from unviable B. thermosphacta cells in cold-smoked salmon. Thus, this study presents a rapid, specific and efficient rpoC-PMA-qPCR method validated in cold-smoked salmon to quantify viable B. thermosphacta in foods.
The Effect of Computerized Cognitive Behavioral Therapy on People's Anxiety and Depression During the 6 Months of Wuhan's Lockdown of COVID-19 Epidemic: A Pilot Study

Background: The effectiveness of computerized cognitive behavioral therapy (CCBT) has been proven for mild and moderate anxiety and depression. In 2016, the first official Chinese CCBT system was launched by Chinese Cognitive Behavior Therapy Professional Organizations and included four items: getting out of depression, overcoming anxiety, staying away from insomnia and facing Obsessive-compulsive disorder. During the COVID-19 epidemic, Chinese CCBT system served the public for free. This study explored the effects of CCBT on anxiety and depression by comparing the use of the platform during the epidemic and during the same period in 2019. Methods: Users were divided into a depression group or an anxiety group according to their own discretion. The subjects used the self-rating anxiety scale (SAS) and self-rating depression scale (SDS) before each training. Each training group completed the corresponding CCBT training project, which had 5–6 training sessions, an average of once every 5 days. The training content in 2019 and 2020 was identical. This study compared the demographic characteristics, depression, and anxiety levels of CCBT platform users during the lockdown period in Wuhan (LP2020), where the outbreak was concentrated in China, from January 23 to July 23, 2020 and the same period in 2019 (SP2019). Result: (1) There were significant differences in gender (χ2 = 7.215, P = 0.007), region (χ2 = 4.225, P = 0.040) and duration of illness (χ2 = 7.867, P = 0.049) between the two periods. (2) There was a positive Pearson correlation between the number of users of CCBT platform during LP2020 and number of confirmed cases of COVID-19 in each province (r = 0.9429, P < 0.001). (3) In LP2020, the SAS (t = 2.579, P = 0.011) and SDS (t = 2.894, P = 0.004) scores at T0 in Hubei were significantly higher than those in other regions. (4) The CCBT platform has an obvious effect on anxiety (F = 4.74, P = 0.009) and depression on users (F = 4.44, P = 0.009). Conclusion: This study showed women, students and people who are more seriously affected by the epidemic were more likely to accept the CCBT training. The CCBT platform made a significant contribution toward alleviating the anxiety and depression symptoms of users during the epidemic. When face-to-face psychotherapy is not available during the epidemic, CCBT can be used as an effective alternative.
Synaptic Plasticity in Memristive Artificial Synapses and Their Robustness Against Noisy Inputs

Emerging brain-inspired neuromorphic computing paradigms require devices that can emulate the complete functionality of biological synapses upon different neuronal activities in order to process big data flows in an efficient and cognitive manner while being robust against any noisy input. The memristive device has been proposed as a promising candidate for emulating artificial synapses due to their complex multilevel and dynamical plastic behaviors. In this work, we exploit ultrastable analog BiFeO3 (BFO)-based memristive devices for experimentally demonstrating that BFO artificial synapses support various long-term plastic functions, i.e., spike timing-dependent plasticity (STDP), cycle number-dependent plasticity (CNDP), and spiking rate-dependent plasticity (SRDP). The study on the impact of electrical stimuli in terms of pulse width and amplitude on STDP behaviors shows that their learning windows possess a wide range of timescale configurability, which can be a function of applied waveform. Moreover, beyond SRDP, the systematical and comparative study on generalized frequency-dependent plasticity (FDP) is carried out, which reveals for the first time that the ratio modulation between pulse width and pulse interval time within one spike cycle can result in both synaptic potentiation and depression effect within the same firing frequency. The impact of intrinsic neuronal noise on the STDP function of a single BFO artificial synapse can be neglected because thermal noise is two orders of magnitude smaller than the writing voltage and because the cycle-to-cycle variation of the current–voltage characteristics of a single BFO artificial synapses is small. However, extrinsic voltage fluctuations, e.g., in neural networks, cause a noisy input into the artificial synapses of the neural network. Here, the impact of extrinsic neuronal noise on the STDP function of a single BFO artificial synapse is analyzed in order to understand the robustness of plastic behavior in memristive artificial synapses against extrinsic noisy input.
Neuroimaging Markers of Cerebral Small Vessel Disease on Hemorrhagic Transformation and Functional Outcome After Intravenous Thrombolysis in Patients With Acute Ischemic Stroke: A Systematic Review and Meta-Analysis

Objective: The aim of this study was to perform a systematic review and meta-analysis to assess whether cerebral small vessel disease (CSVD) on neuroimaging of patients with acute ischemic stroke (AIS) treated with intravenous thrombolysis (IVT) is associated with an increased risk of hemorrhagic transformation (HT), symptomatic intracranial hemorrhage (sICH), and poor functional outcome (PFO). Methods: A thorough search of several databases was carried out to identify relevant studies up to December 2020. We included studies of patients with AIS and neuroimaging markers of CSVD treated with IVT. The primary outcome was HT, and the secondary outcomes were sICH and 3-month PFO. The quality of the studies involved was evaluated using the Newcastle–Ottawa Scale (NOS). The meta-analysis with the fixed effects model was performed. Results: Twenty-four eligible studies (n = 9,419) were pooled in the meta-analysis. All included studies were regarded as high quality with the NOS scores of at least 6 points. The meta-analysis revealed associations between the presence of CSVD and HT, sICH, and the 3-month PFO after IVT. Compared with no CSVD, the presence of CSVD was associated with an increased risk of HT (OR: 1.81, 95% CI: 1.52–2.16), sICH (OR: 2.42, 95% CI: 1.76–3.33), and 3-month PFO (OR: 2.15, 95% CI: 1.89–2.44). For patients with AIS complicated with CSVD, compared with a CSVD score of 0–1, a CSVD score of 2–4 was associated with an increased risk of HT (OR: 3.10, 95% CI: 1.67–5.77), sICH (OR: 2.86, 95% CI: 1.26–6.49), and 3-month PFO (OR: 4.58, 95% CI: 2.97–7.06). Conclusion: Patients with AIS complicated with neuroimaging markers of CSVD are at increased risk of HT and 3-month PFO after IVT. However, it is still necessary to clarify the exact role of CSVD in the occurrence, development, and prognosis of AIS. Systematic Review Registration: www.ClinicalTrials. gov, identifier CRD4202123 3900.
Increased Virulence of Outer Membrane Porin Mutants of Mycobacterium abscessus

Chronic pulmonary infections caused by non-tuberculous mycobacteria of the Mycobacterium abscessus complex (MABSC) are emerging as a global health problem and pose a threat to susceptible individuals with structural lung disease such as cystic fibrosis. The molecular mechanisms underlying the pathogenicity and intrinsic resistance of MABSC to antibiotics remain largely unknown. The involvement of Msp-type porins in the virulence and biocide resistance of some rapidly growing non-tuberculous mycobacteria and the finding of deletions and rearrangements in the porin genes of serially collected MABSC isolates from cystic fibrosis patients prompted us to investigate the contribution of these major surface proteins to MABSC infection. Inactivation by allelic replacement of the each of the two Msp-type porin genes of M. abscessus subsp. massiliense CIP108297, mmpA and mmpB, led to a marked increase in the virulence and pathogenicity of both mutants in murine macrophages and infected mice. Neither of the mutants were found to be significantly more resistant to antibiotics. These results suggest that adaptation to the host environment rather than antibiotic pressure is the key driver of the emergence of porin mutants during infection.
Engaging Drivers in Ride Hailing via Competition: A Case Study with Arena

Sustained work enthusiasms of drivers are crucial for the success of large-scale ride-hailing platforms. In this paper, we conduct the first-of-its-kind exploration to encourage active participation of drivers via competition. We design Arena, a competition where drivers compete for prizes via completing more trips. Through a pilot study covering over 2,600 participants, we uncover the easy-win problem, an overlooked and serious issue in competition design for real-world drivers. It refers to situations where one competitor does not show up during competition whereas the other easily wins. To solve the easy-win problem without impairing motivation of drivers, we devise a novel prediction-based matchmaking framework. On observing that no-shows are highly correlated to the online time of drivers during competition, we propose to identify potential no-shows by predicting drivers’ online time and avoid matching potential noshow drivers with drivers that will show up so as to reduce easy-wins. We conduct large-scale experiments based on real competition data involving over 10,000 drivers. The results show that our prediction-based matchmaking scheme can effectively reduce the ratio of easy-wins.
Construction and Validation of an Immune-Based Prognostic Model for Pancreatic Adenocarcinoma Based on Public Databases

Background Pancreatic adenocarcinoma (PAAD) is a highly lethal and aggressive tumor with poor prognoses. The predictive capability of immune-related genes (IRGs) in PAAD has yet to be explored. We aimed to explore prognostic-related immune genes and develop a prediction model for indicating prognosis in PAAD. Methods The messenger (m)RNA expression profiles acquired from public databases were comprehensively integrated and differentially expressed genes were identified. Univariate analysis was utilized to identify IRGs that related to overall survival. Whereafter, a multigene signature in the Cancer Genome Atlas cohort was established based on the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Moreover, a transcription factors regulatory network was constructed to reveal potential molecular processes in PAAD. PAAD datasets downloaded from the Gene Expression Omnibus database were applied for the validations. Finally, correlation analysis between the prognostic model and immunocyte infiltration was investigated. Results Totally, 446 differentially expressed immune-related genes were screened in PAAD tissues and normal tissues, of which 43 IRGs were significantly related to the overall survival of PAAD patients. An immune-based prognostic model was developed, which contained eight IRGs. Univariate and multivariate Cox regression revealed that the risk score model was an independent prognostic indicator in PAAD (HR > 1, P < 0.001). Besides, the sensitivity of the model was evaluated by the receiver operating characteristic curve analysis. Finally, immunocyte infiltration analysis revealed that the eight-gene signature possibly played a pivotal role in the status of the PAAD immune microenvironment. Conclusion A novel prognostic model based on immune genes may serve to characterize the immune microenvironment and provide a basis for PAAD immunotherapy.
Perampanel Reduces Hyperthermia-Induced Seizures in Dravet Syndrome Mouse Model

Treatment options for Dravet syndrome are limited. The aim of this study was to evaluate the antiepileptic effect of the AMPA receptor antagonist perampanel (PER) on a mouse model of Dravet syndrome (Scn1a E1099X/+ ). We report here that the PER (2 mg/kg) treatment inhibited the spontaneous recurrent seizures and attenuated epileptic activity in Scn1a E1099X/+ mice. In the hyperthermia-induced seizure experiment, PER clearly increased temperature tolerance and significantly ameliorated seizure frequency and discharge duration. PER also demonstrated antiepileptic effects in a cross-over study and a synergistic effect for attenuating heat-induced seizure when given in combination with stiripentol or valproic acid. The results showed that PER effectively decreased the occurrence of spontaneous recurrent seizures and showed significant therapeutic potential for hyperthermia-induced seizures with regard to both susceptibility and severity in a Dravet syndrome mouse model. Potential therapeutic effects of PER for treatment of Dravet syndrome were demonstrated.
Response: Commentary: An In Silico–In Vitro Pipeline Identifying an HLA-A*02:01+ KRAS G12V+ Spliced Epitope Candidate for a Broad Tumor-Immune Response in Cancer Patients

1 Centre for Inflammation Biology and Cancer Immunology (CIBCI) & Peter Gorer Department of Immunobiology, King’s College London, London, United Kingdom, 2 Francis Crick Institute, London, United Kingdom, 3 Department of Cell and Chemical Biology, Oncode Institute, Leiden University Medical Center (LUMC), Leiden, Netherlands, 4 Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany, 5 Bioanalytics, Institute of Clinical Chemistry, University Medical Center, Göttingen, Germany
Energy-effective Offloading Scheme in UAV-assisted C-RAN System

In this paper, we aim to minimize the total power of all the user equipments (UEs) by jointly optimizing user association, computation capacity, transmit power, and the location of UAVs in an unmanned aerial vehicles (UAVs) assisted cloud radio access network (C-RAN). In order to solve this non-convex problem, we use block coordinate descent (BCD) and successive convex approximation (SCA) to transform this problem into four tractable subproblems, and an effective algorithm by solving four subproblems iteratively. The simulation results demonstrate that the proposed algorithm can greatly reduce the total power consumption of UEs.
CO2 Activation Within a Superalkali-Doped Fullerene

With the aim of finding a suitable synthesizable superalkali species, using the B3LYP/6-31G* density functional level of theory we provide results for the interaction between the buckminsterfullerene C60 and the superalkali Li3F2. We show that this endofullerene is stable and provides a closed environment in which the superalkali can exist and interact with CO2. It is worthwhile to mention that the optimized Li3F2 structure inside C60 is not the most stable C2v isomer found for the “free” superalkali but the D3h geometry. The binding energy at 0 K between C60 and Li3F2 (D3h) is computed to be 119 kJ mol−1. Once CO2 is introduced in the endofullerene, it is activated, and the O C O ^ angle is bent to 132°. This activation does not follow the previously studied CO2 reduction by an electron transfer process from the superalkali, but it is rather an actual reaction where a F (from Li3F2) atom is bonded to the CO2. From a thermodynamic analysis, both CO2 and the encapsulated [Li3F2⋅CO2] are destabilized in C60 with solvation energies at 0 K of 147 and < −965 kJ mol−1, respectively.
Predicting Completion: The Road to Informed Study Decisions in Higher Online Education

Non-completion is an ongoing concern in higher education, and even more so in higher online education. One way to address this problem is to take initiatives prior to student enrollment, enabling informed decision making. In line with this, an institution for open higher online education seeks to develop a (non-committal) online self-assessment for prospective students. To identify variables (tests) to be included in this self-assessment, the present study aims at validating variables–previously identified as “predictive of completion in higher education and open to intervention before enrollment”—within the current higher online education context. Results of correlational analyses indicate that the following modifiable variables are relevant to include: hours planned to study, employment hours, study intention, discipline, discipline confidence, basic mathematical skills, and social support. Based on a sensitivity cut-off of 95% (to minimize false negatives) about 13% of the actual non-completers could be identified correctly. Implications for future development of the self-assessment are discussed.
Object-Oriented Building Contour Optimization Methodology for Image Classification Results via Generalized Gradient Vector Flow Snake Model

Building boundary optimization is an essential post-process step for building extraction (by image classification). However, current boundary optimization methods through smoothing or line fitting principles are unable to optimize complex buildings. In response to this limitation, this paper proposes an object-oriented building contour optimization method via an improved generalized gradient vector flow (GGVF) snake model and based on the initial building contour results obtained by a classification method. First, to reduce interference from the adjacent non-building object, each building object is clipped via their extended minimum bounding rectangles (MBR). Second, an adaptive threshold Canny edge detection is applied to each building image to detect the edges, and the progressive probabilistic Hough transform (PPHT) is applied to the edge result to extract the line segments. For those cases with missing or wrong line segments in some edges, a hierarchical line segments reconstruction method is designed to obtain complete contour constraint segments. Third, accurate contour constraint segments for the GGVF snake model are designed to quickly find the target contour. With the help of the initial contour and constraint edge map for GGVF, a GGVF force field computation is executed, and the related optimization principle can be applied to complex buildings. Experimental results validate the robustness and effectiveness of the proposed method, whose contour optimization has higher accuracy and comprehensive value compared with that of the reference methods. This method can be used for effective post-processing to strengthen the accuracy of building extraction results.
Retrieve Ice Velocities and Invert Spatial Rigidity of the Larsen C Ice Shelf Based on Sentinel-1 Interferometric Data

The Larsen C Ice Shelf (LCIS) is the largest ice shelf in the Antarctica Peninsula, and its state can be considered to be an indicator of local climate change. The goal of this paper is to invert the rigidity of the LCIS based on the interferometric synthetic aperture radar (InSAR) technique using Sentinel-1 images. A targeted processing chain is first used to obtain reliable interferometric phase measurements under the circumstance of rapid ice flow. Unfortunately, only the descending data are available, which disallows the corresponding 2-D velocity field to be directly obtained from such measurements. A new approach is thus proposed to estimate the interferometric phase-based 2-D velocity field with the assistance of speckle tracking offsets. This approach establishes an implicit relationship between range and azimuth displacements based on speckle tracking observations. By taking advantage of such a relationship, the equivalent interferometric signals in the azimuth direction are estimated, thereby recovering the interferometric phase-based 2-D ice velocity field of the LCIS. To further investigate the state of the LCIS, the recovered 2-D velocity field is utilized to invert the ice rigidity. The shallow-shelf approximation (SSA) is the core of the reverse model, which is closely dependent on boundary conditions, including kinematic and dynamic conditions. The experimental results demonstrate that the spatial distribution of the rigidity varies approximately from 70 MPa·s1/3 to 300 MPa·s1/3. This rigidity distribution can reproduce a similar ice flow pattern to the observations.