Miracle-dz/UniFAR-FTUs huggingface dataset:
Developmental Exposure to a Mixture of Unconventional Oil and Gas Chemicals Increased Risk-Taking Behavior, Activity and Energy Expenditure in Aged Female Mice After a Metabolic Challenge

Chemicals used in unconventional oil and gas (UOG) operations can act as endocrine disrupting chemicals and metabolic disruptors. Our lab has reported altered energy expenditure and activity in C57BL/6J mice that were preconceptionally, gestationally, and lactationally exposed via maternal drinking water to a laboratory-created mixture of 23 UOG chemicals from gestational day 1 to postnatal day 21 in 7-month-old female mice with no change in body composition. We hypothesized that allowing the mice to age and exposing them to a high fat, high sugar diet might reveal underlying changes in energy balance. To investigate whether aging and metabolic challenge would exacerbate this phenotype, these mice were aged to 12 months and given a high fat, high sugar diet (HFHSD) challenge. The short 3-day HFHSD challenge increased body weight and fasting blood glucose in all mice. Developmental exposure to the 23 UOG mixture was associated with increased activity and non-resting energy expenditure in the light cycle, increased exploratory behavior in the elevated plus maze test, and decreased sleep in 12 month female mice. Each of these effects was seen in the light cycle when mice are normally less active. Further studies are needed to better understand the behavioral changes observed after developmental exposure to UOG chemicals.
Revealing Cues for Fungal Interplay in the Plant–Air Interface in Vineyards

Plant-associated microorganisms play a crucial role in plant health and productivity. Belowground microbial diversity is widely reported as a major factor in determining the composition of the plant microbiome. In contrast, much less is known about the role of the atmosphere in relation to the plant microbiome. The current study examined the hypothesis that the atmospheric microbiome influences the composition of fungal communities of the aboveground organs (flowers, fruit, and leaves) of table grape and vice versa. The atmosphere surrounding grape plantings exhibited a significantly higher level of fungal diversity relative to the nearby plant organs and shared a higher number of phylotypes (5,536 OTUs, 40.3%) with the plant than between organs of the same plant. Using a Bayesian source tracking approach, plant organs were determined to be the major source of the atmospheric fungal community (92%). In contrast, airborne microbiota had only a minor contribution to the grape microbiome, representing the source of 15, 4, and 35% of the fungal communities of leaves, flowers, and fruits, respectively. Moreover, data indicate that plant organs and the surrounding atmosphere shared a fraction of each other’s fungal communities, and this shared pool of fungal taxa serves as a two-way reservoir of microorganisms. Microbial association analysis highlighted more positive than negative interactions between fungal phylotypes. Positive interactions were more common within the same environment, while negative interactions appeared to occur more frequently between different environments, i.e., atmosphere, leaf, flower, and fruit. The current study revealed the interplay between the fungal communities of the grape phyllosphere with the surrounding air. Plants were identified as a major source of recruitment for the atmospheric microbiome, while the surrounding atmosphere contributed only a small fraction of the plant fungal community. The results of the study suggested that the plant–air interface modulates the plant recruitment of atmospheric fungi, taking a step forward in understanding the plant holobiont assembly and how the atmosphere surrounding plants plays a role in this process. The impact of plants on the atmospheric microbiota has several biological and epidemiological implications for plants and humans.
Molecular Genetics Analysis of 70 Chinese Families With Muscular Dystrophy Using Multiplex Ligation-Dependent Probe Amplification and Next-Generation Sequencing

Background: Muscular dystrophy (MD) includes multiple types, of which dystrophinopathies caused by dystrophin (DMD) mutations are the most common types in children. An accurate identification of the causative mutation at the genomic level is critical for genetic counseling of the family, and analysis of genotype–phenotype correlations, as well as a reference for the development of gene therapy. Methods: Totally, 70 Chinese families with suspected MD probands were enrolled in the study. The multiplex ligation-dependent probe amplification (MLPA) was first performed to screen large deletions/duplications of DMD exons in the patients, and then, next-generation sequencing (NGS) was carried out to detect small mutations in the MLPA-negative patients. Results: Totally, 62 mutations of DMD were found in 62 probands with DMD/BMD, and two compound heterozygous mutations in LAMA2 were identified in two probands with MDC1A (a type of congenital MD), indicating that the diagnostic yield was 91.4% by MLPA plus NGS for MD diagnosis in this cohort. Out of the mutations, 51 large mutations encompassing 47 (75.8%) deletions and four duplications (6.5%) were identified by MLPA; 11 small mutations including six (9.7%) nonsense, two (3.2%) small deletions, two splice-site mutations (3.2%), and one small insertion (1.6%) were found by NGS. Large mutations were found most frequently in the hotspot region between exons 45 and 55 (70.6%). Out of the 11 patients harboring point mutations in DMD, 8 were novel mutations. Additionally, one novel mutation in LAMA2 was identified. All the novel mutations were analyzed and predicted as pathogenic according to American College of Medical Genetics and Genomics (ACMG) guideline. Finally, 34 DMD, 4 BMD, 24 BMD/DMD, and 2 MDC1A were diagnosed in the cohort. Conclusion: Our data indicated that the MLPA plus NGS can be a comprehensive and effective tool for precision diagnosis and potential treatment of MD and is particularly necessary for the patients at very young age with only two clinical indicators (persistent hyperCKemia and typical myopathy performance on electromyogram) but no definite clinical manifestations.
Analysis of Prefrontal Single-Channel EEG Data for Portable Auditory ERP-Based Brain–Computer Interfaces

An electroencephalogram (EEG)-based brain-computer interface (BCI) is a tool to non-invasively control computers by translating the electrical activity of the brain. This technology has the potential to provide patients who have severe generalized myopathy, such as those suffering from amyotrophic lateral sclerosis (ALS), with the ability to communicate. Recently, auditory oddball paradigms have been developed to implement more practical event-related potential (ERP)-based BCIs because they can operate without ocular activities. These paradigms generally make use of clinical (over 16-channel) EEG devices and natural sound stimuli to maintain the user's motivation during the BCI operation; however, most ALS patients who have taken part in auditory ERP-based BCIs tend to complain about the following factors: (i) total device cost and (ii) setup time. The development of a portable auditory ERP-based BCI could overcome considerable obstacles that prevent the use of this technology in communication in everyday life. To address this issue, we analyzed prefrontal single-channel EEG data acquired from a consumer-grade single-channel EEG device using a natural sound-based auditory oddball paradigm. In our experiments, EEG data was gathered from nine healthy subjects and one ALS patient. The performance of auditory ERP-based BCI was quantified under an offline condition and two online conditions. The offline analysis indicated that our paradigm maintained a high level of detection accuracy (%) and ITR (bits/min) across all subjects through a cross-validation procedure (for five commands: 70.0 ± 16.1 and 1.29 ± 0.93, for four commands: 73.8 ± 14.2 and 1.16 ± 0.78, for three commands: 78.7 ± 11.8 and 0.95 ± 0.61, and for two commands: 85.7 ± 8.6 and 0.63 ± 0.38). Furthermore, the first online analysis demonstrated that our paradigm also achieved high performance for new data in an online data acquisition stream (for three commands: 80.0 ± 19.4 and 1.16 ± 0.83). The second online analysis measured online performances on the different day of offline and first online analyses on a different day (for three commands: 62.5 ± 14.3 and 0.43 ± 0.36). These results indicate that prefrontal single-channel EEGs have the potential to contribute to the development of a user-friendly portable auditory ERP-based BCI.
Action Generation Adapted to Low-Level and High-Level Robot-Object Interaction States

Our daily environments are complex, composed of objects with different features. These features can be categorized into low-level features, e.g., an object position or temperature, and high-level features resulting from a pre-processing of low-level features for decision purposes, e.g., a binary value saying if it is too hot to be grasped. Besides, our environments are dynamic, i.e., object states can change at any moment. Therefore, robots performing tasks in these environments must have the capacity to (i) identify the next action to execute based on the available low-level and high-level object states, and (ii) dynamically adapt their actions to state changes. We introduce a method named Interaction State-based Skill Learning (IS2L), which builds skills to solve tasks in realistic environments. A skill is a Bayesian Network that infers actions composed of a sequence of movements of the robot's end-effector, which locally adapt to spatio-temporal perturbations using a dynamical system. In the current paper, an external agent performs one or more kinesthetic demonstrations of an action generating a dataset of high-level and low-level states of the robot and the environment objects. First, the method transforms each interaction to represent (i) the relationship between the robot and the object and (ii) the next robot end-effector movement to perform at consecutive instants of time. Then, the skill is built, i.e., the Bayesian network is learned. While generating an action this skill relies on the robot and object states to infer the next movement to execute. This movement selection gets inspired by a type of predictive models for action selection usually called affordances. The main contribution of this paper is combining the main features of dynamical systems and affordances in a unique method to build skills that solve tasks in realistic scenarios. More precisely, combining the low-level movement generation of the dynamical systems, to adapt to local perturbations, with the next movement selection simultaneously based on high-level and low-level states. This contribution was assessed in three experiments in realistic environments using both high-level and low-level states. The built skills solved the respective tasks relying on both types of states, and adapting to external perturbations.
Brackish-Water Benthic Fauna Under Fluctuating Environmental Conditions: The Role of Eutrophication, Hypoxia, and Global Change

We studied the spatio-temporal impacts of physical and chemical environmental variables (depth, sediment type, salinity, temperature, oxygen, total phosphorus and total nitrogen) on soft-sediment zoobenthos in the open coastal Gulf of Finland during 2001-2015. The study included 55 sampling-stations covering the east-west gradient of the Finnish coastal zone. The chosen environmental variables significantly influenced the distribution of the species in space and over time. Some zoobenthic taxa formed assemblages with each other, occurring in similar environmental conditions, while Gammarus spp. and Chironomidae clearly differed from other taxa in regards to ecological requirements. We showed the critical influence of oxygen (normoxia, hypoxia, anoxia) on individual species, some better adapted to low oxygen conditions (e.g. Chironomidae) than others (e.g. Monoporeia affinis). The nutrient concentrations in the surface sediment also significantly affected the benthic assemblage patterns. The number of species in space and time increased with increasing oxygen concentrations. This study clearly shows that in order to maintain healthy marine communities, it is essential to counteract excess nutrient inputs and their indirect effects on sufficient O2 conditions for the benthic habitats.
Altered Topology of the Structural Brain Network in Patients With Post-stroke Depression

There is a pressing need to further our understanding of the mechanisms underlying the depression symptoms in patients with post-stroke depression (PSD) in order to inform targeted therapeutic approaches. While previous research has demonstrated a reorganization in the functional brain network of PSD, it remains uncertain whether, or not it also occurs in the structural brain network. We therefore aim to investigate the structural brain network of patients with PSD as compared to post-stroke non-depression (PSND) patients. In addition, our research considers the relationship between network metrics and functional measurements. Thirty-one PSD patients and twenty-three PSND patients were recruited. All patients underwent MRI and functional assessments, including the Barthel index, mini-mental state examination (MMSE), and Hamilton depression rating scale (HAMD). Diffusion tensor imaging was used to construct the structural brain network and to conduct the subsequent graph theoretical analysis. Network measures were computed and compared between PSD and PSND patients. Associations between functional assessments and network measures were studied as well. We successfully detected increased global and local efficiency in patients with PSD. Regions with disrupted local connections were located primarily in the cognitive and limbic systems. More importantly, PSD patients’ global and regional network measures were associated with depression severity, as measured by HAMD. These findings suggest that disrupted global and local network topologies might contribute to PSD patients’ depression symptoms. Therefore, connectome-based network measures could be potential bio-markers for evaluating stroke patients’ depression levels.
Dosimetric and Radiobiological Comparison of External Beam Radiotherapy Using Simultaneous Integrated Boost Technique for Esophageal Cancer in Different Location

Objectives: To compare treatment plans of intensity modulated radiotherapy (IMRT), volumetric modulated arc radiotherapy (VMAT), and helical tomotherapy (HT) with simultaneous integrated boost (SIB) technique for esophageal cancer (EC) of different locations using dosimetry and radiobiology. Methods: Forty EC patients were planned for IMRT, VMAT, and HT plans, including 10 cases located in the cervix, upper, middle, and lower thorax, respectively. Dose-volume metrics, conformity index (CI), homogeneity index (HI), tumor control probability (TCP), and normal tissue complication probability (NTCP) were analyzed to evaluate treatment plans. Results: HT showed significant improvement over IMRT and VMAT in terms of CI (p = 0.007), HI (p < 0.001), and TCP (p < 0.001) in cervical EC. IMRT yielded more superior CI, HI and TCP compared with VMAT and HT in upper and middle thoracic EC (all p < 0.05). Additionally, V30 (27.72 ± 8.67%), mean dose (1801.47 ± 989.58cGy), and NTCP (Niemierko model: 0.44 ± 0.55%; Lyman-Kutcher-Burman model: 0.61 ± 0.59%) of heart in IMRT were sharply reduced than VMAT and HT in middle thoracic EC. For lower thoracic EC, the three techniques offered similar CI and HI (all p > 0.05). But VMAT dramatically lowered liver V30 (9.97 ± 2.84%), and reduced NTCP of lungs (Niemierko model: 0.47 ± 0.48%; Lyman-Kutcher-Burman model: 1.41 ± 1.07%) and liver (Niemierko model: 0.10 ± 0.08%; Lyman-Kutcher-Burman model: 0.17 ± 0.17%). Conclusions: HT was a good option for cervical EC with complex target coverage but little lungs and heart involvement as it achieved superior dose conformity and uniformity. Due to potentially improving tumor control and reducing heart dose with acceptable lungs sparing, IMRT was a preferred choice for upper and middle thoracic EC with large lungs involvement. VMAT could ameliorate therapeutic ratio and lower lungs and liver toxicity, which was beneficial for lower thoracic EC with little thoracic involvement but being closer to heart and liver. Individually choosing optimal technique for EC in different location will be warranted.
Longitudinal Alterations in Prefrontal Resting Brain Connectivity in Non-Treatment-Seeking Young Adults With Cannabis Use Disorder

Background: Cannabis is increasingly perceived as a harmless drug by recreational users, yet chronic use may impact brain changes into adulthood. Repeated cannabis exposure has been associated with enduring synaptic changes in executive control and reward networks. It is important to determine whether there are brain functional alterations within these networks in individuals that do not seek treatment for chronic cannabis abuse. Methods: This longitudinal study compared resting-state functional connectivity changes in executive control and reward networks between 23 non-treatment-seeking young adults with cannabis use disorder (6 females; baseline age M = 19.3 ± 1.18) and 21 age-matched controls (10 females; baseline age M = 19.4 ± 0.65) to determine group differences in the temporal trajectories of resting-state functional connectivity across a 2-year span. Results: Results showed i) significant increases in resting-state functional connectivity between the caudal anterior cingulate cortex and precentral and parietal regions over time in the control group, but not in the cannabis use disorder group, and ii) sustained lower resting-state functional connectivity of anterior cingulate cortex seeds with frontal and thalamic regions in the cannabis use disorder group vs. the age-matched controls. Resting-state functional connectivity strength was correlated with cannabis use patterns in the cannabis use disorder sample. Conclusion: Longitudinal alterations in intrinsic functional organization of executive control networks found in non-treatment-seeking young adults with cannabis use disorder (when compared to age-matched controls) may impact regulatory control over substance use behavior. Current findings were limited to examining executive control and reward networks seeded in ACC and NAcc, respectively. Future studies with larger sample sizes and enough power are needed to conduct exploratory analyses examining rsFC of other networks beyond those within the scope of the current study.
Applied Uses of Extracorporeal Membrane Oxygenation Therapy

Extracorporeal membrane oxygenation (ECMO) therapy has been around since the 1970s and has completely changed how critical care physicians view supportive therapy for certain patients. ECMO therapy is a supportive therapy provided by a mechanical extracorporeal circuit that is able to directly oxygenate and remove carbon dioxide from the blood. By performing this, ECMO can provide cardiac, respiratory, or combined cardiopulmonary supportive therapy in cases of failure. ECMO therapy also places less emphasis on invasive mechanical ventilation, which prevents barotrauma and gives rest to the lungs. Therefore, they are used for several different conditions. This review article focuses on the definition, principles, types, and practical applications of ECMO therapy.
Comparing information literacy of student beginners among different branches of study

In our paper we present a study in which we investigated the level of information literacy of first-year students across different studies offered by faculties at the University of Graz. Data were collected by means of a multiple-choice questionnaire. In total we analyzed 232 questionnaires completed by first-year students from six studies (faculties). The results show that the overall level of information literacy is mediocre. However, the difference in the level of information literacy across the studies is not as big as originally expected. The type of high school completed has a strong effect at least in the beginning of the studies. Another interesting result shows that the students rated their information literacy skills much higher than the test indicated. It can be concluded that multiple-choice questionnaires are an efficient and objective test instrument to inform the students that they are much less information literate than they believe themselves to be.
Marine biodiversity from zero to a thousand meters at Clipperton Atoll (Île de La Passion), Tropical Eastern Pacific

Clipperton Atoll (Île de La Passion) is the only atoll in the Tropical Eastern Pacific (TEP) ecoregion and, owing to its isolation, possesses several endemic species and is likely an important stepping stone between Oceania, the remainder of the TEP, including other oceanic islands and the west coast of Central America. We describe the biodiversity at this remote atoll from shallow water to depths greater than one thousand meters using a mixture of technologies (SCUBA, stereo baited remote underwater video stations, manned submersible, and deep-sea drop cameras). Seventy-four unique taxa of invertebrates were identified during our expedition. The majority (70%) of these taxa were confined to the top 400 m and consisted mostly of sessile organisms. Decapod crustaceans and black corals (Antipatharia) had the broadest depth ranges, 100–1,497 m and 58–967 m, respectively. Decapods were correlated with the deepest depths, while hard corals were correlated with the shallow depths. There were 96 different fish taxa from 41 families and 15 orders, of which 70% were restricted to depths <200 m. While there was a decreasing trend in richness for both fish and invertebrate taxa with depth, these declines were not linear across the depth gradient. Instead, peaks in richness at ∼200 m and ∼750 m coincided with high turnover due to the appearance of new taxa and disappearance of other taxa within the community and is likely associated with the strong oxygen minimum zone that occurs within the region. The overall depth effect was stronger for fishes compared with invertebrates, which may reflect ecological preferences or differences in taxonomic resolution among groups. The creation of a no-take marine reserve 12 nautical miles around the atoll in 2016 will help conserve this unique and relatively intact ecosystem, which possesses high predator abundance.
Modeling method for weapon system of systems structure based on semantic meta-model

According to the ideas of data-centric in architecture modeling,the semantic model of weapon system of systems architecture is proposed,which is named semantic weapon system of systems.Firstly,the semantic meta-model is proposed based on DoDAF meta-model(DM2),and the concept and relationship of base classes are defined in system of systems architecture.Then an ontology describe frame is given by classes,relationships,attributes and instances which are generated as quadruples.Secondly,ontology models of combat view,system view and capability view based on the semantic meta-model are constructed.In addition,the definitions,relationships and properties of constituent elements in each view are formally clarified.Finally,the early warning detection system in naval battlefield is studied as a case to verify the feasibility of the method.