Miracle-dz/UniFAR-FTUs huggingface dataset:
New Data on the Range Expansion of the Thaumetopoea pityocampa (Lepidoptera: Notodontidae) ‘ENA clade’ in Greece: The Role of Bacterial Endosymbionts

Abstract The pine processionary moth, Thaumetopoea pityocampa (Denis and Schiffermüller), is an important insect in the Mediterranean region, as it defoliates pines and its urticating hairs can cause allergic reactions in humans and animals. Moreover, this species exhibits an interesting genetic structure as recently a distinct East-North African mtDNA lineage (‘ENA clade’) has been described.This clade has been recently detected in Greek populations where it has currently expanded its range by replacing the ‘endemic’ T. pityocampa lineages. Here, we report new data on the rapid spread of ‘ENA clade’ in the Greek island Evoia in only a few years. As the underlying mechanisms of the ‘ENA clade’ range expansion has not been studied so far, we screened T. pityocampa for an infection with the heritable bacterial endosymbionts Wolbachia (Bacteria: Anaplasmataceae), Cardinium (Bacteria: Bacteroidaceae), Rickettsia (Bacteria: Rickettsiaceae) and Spiroplasma (Bacteria: Spiroplasmataceae). These bacteria can manipulate the reproduction of infected hosts, something that could potentially explain the rapid spread of ‘ENA clade’ lineage. Therefore, we screened 28 individuals that exhibited T. pityocampa ‘ENA clade’ and ‘endemic’ T. pityocampa haplotypes from nine populations scattered all over Greece. None of them was infected with any of the four endosymbionts, suggesting that these bacteria do not cause reproductive manipulations in T. pityocampa lineages and, thus, other factors should be explored in future research efforts.
Missed opportunities for prevention and treatment of hepatitis C among persons with HIV/HCV coinfection

ABSTRACT Hepatitis C (HCV) and HIV have common modes of transmission but information about HCV transmission risk, prevention, and treatment among persons with coinfection is lacking. The Medical Monitoring Project produces nationally representative estimates describing adults with diagnosed HIV in the United States. Using medical record data recorded during 6/2013–5/2017, we identified persons with detectable HCV RNA documented during the past 24 months. Among persons with coinfection, we described HCV transmission risk factors and receipt of HCV prevention services during the past 12 months and prescription of HCV treatment during the past 24 months. Overall, 4.9% had documented active HCV coinfection, among whom 30.2% were men who have sex with men (MSM), 6.7% reported injection drug use, and 62.1% were prescribed HCV treatment. Among MSM, 45.5% reported condomless anal sex and 42.3% received free condoms. Among persons who used drugs, 30.8% received drug or alcohol counseling, and among persons who injected drugs, 79.2% received sterile syringes. Among persons with HIV/HCV coinfection, recent drug injection was uncommon and most received sterile syringes. However, 1 in 3 were MSM, of whom half reported recent HCV sexual transmission risk behaviors. More than one-third of those with coinfection were not prescribed curative HCV treatment.
CD8+ and Regulatory T cells Differentiate Tumor Immune Phenotypes and Predict Survival in Locally Advanced Head and Neck Cancer

Background: The tumor immune status “inflamed”, “immune excluded”, and “desert” might serve as a predictive parameter. We studied these three cancer immune phenotypes while using a simple immunohistochemical algorithm. Methods: Pre-treatment tissue samples of 280 patients with locally advanced HNSCC treated with radiochemotherapy were analyzed. A double staining of CD8+ cytotoxic T cells (CTL) and FoxP3+ (Treg) was performed and the cell density was evaluated in the intraepithelial and stromal compartment of the tumor. Results: The classification of tumors as “immune desert” when stromal CTL were ≤ 50 cells/mm2, “inflamed” when intraepithelial CTL were > 500 cells/mm2, and as “excluded” when neither of these definitions met these cut off values allowed the best discrimination regarding overall survival. These groups had median OS periods of 37, 61, and 85 months, respectively. In “immune desert” and “immune excluded” tumors high Treg tended to worsen OS, but in “inflamed” tumors high Treg clearly improved OS. Conclusions: We propose that, in locally advanced HNSCC, the tumor immune state “inflamed”, “immune excluded”, and “immune desert” can be defined by intraepithelial and stromal CTL. Tregs can further subdivide these groups. The opposing effects of Tregs in the different groups might be the reason for the inconsistency of Tregs prognostic values published earlier.
Experimental Evaluation of an RSSI-Based Localization Algorithm on IoT End-Devices

In recent years, wireless sensor networks (WSNs) have experienced a significant growth as a fundamental part of the Internet of Things (IoT). WSNs nodes constitute part of the end-devices present in the IoT, and in many cases location data of these devices is expected by IoT applications. For this reason, many localization algorithms for WSNs have been developed in the last years, although in most cases the results provided are obtained from simulations that do not consider the resource constraints of the end-devices. Therefore, in this work we present an experimental evaluation of a received signal strength indicator (RSSI)-based localization algorithm implemented on IoT end-devices, comparing its results with those obtained from simulations. We have implemented the fuzzy ring-overlapping range-free (FRORF) algorithm with some modifications to make its operation feasible on resource-constrained devices. Multiple tests have been carried out to obtain the localization accuracy data in three different scenarios, showing the difference between simulation and real results. While the overall behaviour is similar in simulations and in real tests, important differences can be observed attending to quantitative accuracy results. In addition, the execution time of the algorithm running in the nodes has been evaluated. It ranges from less than 10 ms to more than 300 ms depending on the fuzzification level, which demonstrates the importance of evaluating localization algorithms in real nodes to prevent the introduction of large overheads that may not be affordable by resource-constrained nodes.
Estimating Chlorophyll Content of Leafy Green Vegetables from Adaxial and Abaxial Reflectance

As a primary pigment of leafy green vegetables, chlorophyll plays a major role in indicating vegetable growth status. The application of hyperspectral remote sensing reflectance offers a quick and nondestructive method to estimate the chlorophyll content of vegetables. Reflectance of adaxial and abaxial leaf surfaces from three common leafy green vegetables: Pakchoi var. Shanghai Qing (Brassica chinensis L. var. Shanghai Qing), Chinese white cabbage (Brassica campestris L. ssp. Chinensis Makino var. communis Tsen et Lee), and Romaine lettuce (Lactuca sativa var longifoliaf. Lam) were measured to estimate the leaf chlorophyll content. Modeling based on spectral indices and the partial least squares regression (PLS) was tested using the reflectance data from the two surfaces (adaxial and abaxial) of leaves in the datasets of each individual vegetable and the three vegetables combined. The PLS regression model showed the highest accuracy in estimating leaf chlorophyll content of pakchoi var. Shanghai Qing (R2 = 0.809, RMSE = 62.44 mg m−2), Chinese white cabbage (R2 = 0.891, RMSE = 45.18 mg m−2) and Romaine lettuce (R2 = 0.834, RMSE = 38.58 mg m−2) individually as well as of the three vegetables combined (R2 = 0.811, RMSE = 55.59 mg m−2). The good predictability of the PLS regression model is considered to be due to the contribution of more spectral bands applied in it than that in the spectral indices. In addition, both the uninformative variable elimination PLS (UVE-PLS) technique and the best performed spectral index: MDATT, showed that the red-edge region (680–750 nm) was effective in estimating the chlorophyll content of vegetables with reflectance from two leaf surfaces. The combination of the PLS regression model and the red-edge region are insensitive to the difference between the adaxial and abaxial leaf structure and can be used for estimating the chlorophyll content of leafy green vegetables accurately.
Correlation between Changes in the Transverse Relaxation Time and Electromyographic Measurements of the Superficial Masseter and Temporal Muscles

We analyzed the correlations between the T2 shift and integrated electromyographic (iEMG) values in the masseter and temporal muscles. Six healthy adults engaged in a clenching task over two durations at various bite forces. We evaluated the mean T2 shift per voxel and assessed their correlations with iEMG using a linear mixed model. The regression coefficients were different for each muscle type, similar for the left and right sides, and decreased upon doubling duration.
A Qualitative Study on Employees’ Experiences of a Support model for Systematic Work Environment Management

Background: The aim is to explore how an organisational work environment support model, the Stamina model, influences employees’ work situations and the development of sustainable work systems. Methods: It was a qualitative study with semi-structured, focus-group interviews, including 45 employees from six work groups. Eighteen focus group interviews were conducted over a period of two years. Data were analysed with constant comparative method. Results: The core category, shifting focus from an individual to an organisational perspective of work, illustrated how communication and increased understanding of one’s work tasks changed over time and contributed to deeper focus on the actual operation. These insights were implemented at different time points among the work groups during the two-year process. Conclusions: Our results indicate that working with the model engages employees in the work environment management, puts emphasis on reflections and discussions about the meaning and purpose of the operations and enables a shared platform for communication. These are important features that need to continue over time in order to create a sustainable work system. The Stamina model, thus seems to have the potential to promote productive and healthy work places.
SERS-Based Immunoassays for the Detection of Botulinum Toxins A and B Using Magnetic Beads

Rapid and sensitive detection of botulinum neurotoxins (BoNTs) is important for immediate treatment with proper antitoxins. However, it is difficult to detect BoNTs at the acute phase of infection, owing to its rarity and ambiguous symptoms. To resolve this problem, we developed a surface-enhanced Raman scattering (SERS)-based immunoassay technique for the rapid and sensitive detection of BoNTs. Magnetic beads and SERS nanotags as capture substrates and detection probes, respectively, and Nile Blue A (NBA) and malachite green isothiocyanate (MGITC) as Raman reporter molecules were used for the detection of two different types of BoNTs (types A and B), respectively. The corresponding limits of detection (LODs) were determined as 5.7 ng/mL (type A) and 1.3 ng/mL (type B). Total assay time, including that for immunoreaction, washing, and detection, was less than 2 h.
A Complete Protocol for Rapid and Low-Cost Fabrication of Polymer Microfluidic Chips Containing Three-Dimensional Microstructures Used in Point-of-Care Devices

This protocol provides insights into the rapid, low-cost, and largescale fabrication of polymer microfluidic chips containing three-dimensional microstructures used in point-of-care devices for applications such as detection of pathogens via molecular diagnostic methods. The details of the fabrication methods are described in this paper. This study offers suggestions for researchers and experimentalists, both at university laboratories and in industrial companies, to prevent doom fabrication issues. For a demonstration of bio-application in point-of-care testing, the 3D microarrays fabricated are then employed in multiplexed detection of Salmonella (Salmonella Typhimurium and Salmonella Enteritidis), based on a molecular detection technique called solid-phase polymerase chain reaction (SP-PCR).
Performance Sensing Data Prediction for an Aircraft Auxiliary Power Unit Using the Optimized Extreme Learning Machine †

The aircraft auxiliary power unit (APU) is responsible for environmental control in the cabin and the main engines starting the aircraft. The prediction of its performance sensing data is significant for condition-based maintenance. As a complex system, its performance sensing data have a typically nonlinear feature. In order to monitor this process, a model with strong nonlinear fitting ability needs to be formulated. A neural network has advantages of solving a nonlinear problem. Compared with the traditional back propagation neural network algorithm, an extreme learning machine (ELM) has features of a faster learning speed and better generalization performance. To enhance the training of the neural network with a back propagation algorithm, an ELM is employed to predict the performance sensing data of the APU in this study. However, the randomly generated weights and thresholds of the ELM often may result in unstable prediction results. To address this problem, a restricted Boltzmann machine (RBM) is utilized to optimize the ELM. In this way, a stable performance parameter prediction model of the APU can be obtained and better performance parameter prediction results can be achieved. The proposed method is evaluated by the real APU sensing data of China Southern Airlines Company Limited Shenyang Maintenance Base. Experimental results show that the optimized ELM with an RBM is more stable and can obtain more accurate prediction results.
Cyber Situation Comprehension for IoT Systems based on APT Alerts and Logs Correlation

With the emergence of the Advanced Persistent Threat (APT) attacks, many Internet of Things (IoT) systems have faced large numbers of potential threats with the characteristics of concealment, permeability, and pertinence. However, existing methods and technologies cannot provide comprehensive and prompt recognition of latent APT attack activities in the IoT systems. To address this problem, we propose an APT Alerts and Logs Correlation Method, named APTALCM and a framework of deploying APTALCM on the IoT system, where an edge computing architecture was used to achieve cyber situation comprehension without too much data transmission cost. Specifically, we firstly present a cyber situation ontology for modeling the concepts and properties to formalize APT attack activities in the IoT systems. Then, we introduce a cyber situation instance similarity measurement method based on the SimRank mechanism for APT alerts and logs Correlation. Combining with instance similarity, we further propose an APT alert instances correlation method to reconstruct APT attack scenarios and an APT log instances correlation method to detect log instance communities. Through the coalescence of these methods, APTALCM can accomplish the cyber situation comprehension effectively by recognizing the APT attack intentions in the IoT systems. The exhaustive experimental results demonstrate that the two kernel modules, i.e., Alert Instance Correlation Module (AICM) and Log Instance Correlation Module (LICM) in our APTALCM, can achieve both high true-positive rate and low false-positive rate.
Induction of Urokinase Activity by Retinoic Acid in Two Cell Lines of Neuronal Origin

Retinoic acid is one of the most well-known agents able to induce differentiation in several types of tumours. Unfortunately, most of the tumours are refractive to the differentiation cues. The aim of this investigation was to analyse the effects of prolonged treatment with retinoic acid on two cell lines of neural origin refractive to differentiation. Cells were also treated with retinoic acid in combination with a poly(ADP-ribosyl) polymerase (PARP) inhibitor because PARP1 is a known chromatin modulator and can influence the process of differentiation. The main methods comprised tumour cell line culturing and treatment; analysis of RNA and protein expression after cell treatment; as well as analysis of urokinase activity, migration, and proliferation. Both cell lines continued to proliferate under the prolonged treatment and showed increase in urokinase plasminogen activator activity. Analysis of gene expression and cell phenotype revealed different mechanisms, which only in neuroblastoma H4 cells could indicate the process of epithelial-mesenchymal transition. The data collected indicate that the activity of the urokinase plasminogen activator, although belonging to an extracellular protease, does not necessary lead to epithelial-mesenchymal reprogramming and increase in cell migration but can have different outcomes depending on the intracellular milieu.
Assessment of the Inner Surface Microstructure of Decellularized Cortical Bone by a Scanning Electron Microscope

The microstructural changes of bones, which form a hierarchy of skeletal tissue, vary, depending on their condition, and are affected by the behaviors of bone cells. The purpose of this study is to assess the microstructural changes in the inner femoral surface of Sprague Dawley rats according to the conditions using a scanning electron microscope. Microstructural differences on the endocortical surface were observed in the characteristics of osteocytic canaliculi, bone fibers, and surface roughness, showing a rougher surface in old adults and an osteoporosis model by quantitative comparison. These results could be helpful for developing a basic understanding of the microstructural changes that occur on the bone surface under various conditions.
Visualizing ToF-SIMS hyperspectral imaging data using color-tagged toroidal self-organizing maps.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface characterization technique capable of producing high spatial resolution hyperspectral images, in which each pixel comprises an entire mass spectrum. Such images can provide insight into the chemical composition across a surface. However, issues arise due to the size and complexity of the data produced. Data are particularly complicated for biological samples, primarily due to overlapping spectra produced by similar components. The traditional approach of selecting individual ion peaks as representative of particular components is insufficient for such complex data sets. Multivariate analysis (MVA) can help to overcome this significant hurdle. We demonstrate that Kohonen self-organizing maps (SOMs) with a toroidal to-pology can be used to analyze a ToF-SIMS hyperspectral imaging data set and identify spectral similarities between pixels. We present a method for color-tagging the toroidal SOM output, which reduces the entire data set to a single RGB image in which similar pixels - based on their associated mass spectra - are assigned a similar color. This method was exemplified using a ToF-SIMS image of dried large multilamellar vesicles (LMVs), loaded with the antibiotic cefditoren pivoxil (CP). We successfully identified CP-loaded and empty LMVs without the need for any prior knowledge of the sample, despite their highly similar spectra. We also identified which specific ion peaks were most important in differentiating the two LMV populations. This approach is entirely unsupervised and requires minimal experimenter input. It was developed with the aim of providing a user-friendly yet sophisticated workflow for understanding complex biological samples using ToF-SIMS images.
Synergistic Phytotoxic Effects of Culmorin and Trichothecene Mycotoxins

Species of the fungus Fusarium cause Fusarium head blight (FHB) of cereal crops and contaminate grain with sesquiterpenoid mycotoxins, including culmorin (CUL) and trichothecenes. While the phytotoxicity of trichothecenes, such as deoxynivalenol (DON), and their role in virulence are well characterized, less is known about the phytotoxicity of CUL and its role in the development of FHB. Herein, we evaluated the phytotoxic effects of purified CUL and CUL-trichothecene mixtures using Chlamydomonas reinhardtii growth and Triticum aestivum (wheat) root elongation assays. By itself, CUL did not affect growth in either system. However, mixtures of CUL with DON, 3-acetyldeoxynivalenol, 15-acetyldeoxynivalenol, or NX-3, but not with nivalenol, inhibited growth in a synergistic manner. Synergistic phytotoxic effects of CUL and DON were also observed on multiple plant varieties and species. The severity of wheat FHB caused by 15 isolates of Fusarium graminearum was negatively correlated with the CUL/DON ratio, but positively correlated with the sum of both CUL and DON. Additionally, during the first week of infection, CUL biosynthetic genes were more highly expressed than the TRI5 trichothecene biosynthetic gene. Furthermore, genomic analysis of Fusarium species revealed that CUL and trichothecene biosynthetic genes consistently co-occur among species closely related to F. graminearum.
Emergence of a Novel Ehrlichia minasensis Strain, Harboring the Major Immunogenic Glycoprotein trp36 with Unique Tandem Repeat and C-Terminal Region Sequences, in Haemaphysalis hystricis Ticks Removed from Free-Ranging Sheep in Hainan Province, China

Ehrlichia minasensis, a recently described Ehrlichia species that is the most closely related to, but clearly distinct from, Ehrlichia canis, has been circulating in not only bovines, cervids, and dogs but also several tick species from Canada, Brazil, France, Pakistan, Ethiopia, and Israel. However, there are no reports of E. minasensis in China. The purpose of this study was to explore whether E. minasensis is present naturally in ticks in China. Through PCR targeting of the genus-conserved dsb gene, E. minasensis DNA was detected in Haemaphysalis hystricis ticks removed from free-ranging sheep in Hainan Province, South China in 2017. The partial sequence of the dsb, 16S rRNA, and groEL genes demonstrated that the Hainan strain shared 99% identity with the dsb gene of E. minasensis strain UFMG-EV (GenBank: JX629808), with the 16S rRNA of E. minasensis isolate E-2650 (MH500005) and with the groEL gene of E. minasensis strain UFMG-EV (JX629806), respectively. Moreover, sequence analysis of the major immunogenic tandem repeat protein (trp36) revealed that the Hainan strain harbored a unique tandem repeat sequence (APEAAPVSAPEAAPVSAPVS) and a C-terminal region that differed from those of other known E. minasensis strains. Additionally, phylogenetic analysis based on the entire amino acid sequence of trp36 revealed that the Hainan strain was closely related to a recently described E. minasensis strain from Brazil, of which the sister clade contained different strains of E. canis. The discovery of this novel Hainan strain in H. hystricis ticks represents the first known natural presence of E. minasensis in South China, highlighting the need for its constant surveillance.