Miracle-dz/UniFAR-FTUs huggingface dataset:
Life Within a Contaminated Niche: Comparative Genomic Analyses of an Integrative Conjugative Element ICEnahCSV86 and Two Genomic Islands From Pseudomonas bharatica CSV86T Suggest Probable Role in Colonization and Adaptation

Comparative genomic and functional analyses revealed the presence of three genomic islands (GIs, >50 Kb size): ICEnahCSV86, Pseudomonas bharatica genomic island-1 (PBGI-1), and PBGI-2 in the preferentially aromatic-degrading soil bacterium, Pseudomonas bharatica CSV86T. Site-specific genomic integration at or near specific transfer RNAs (tRNAs), near-syntenic structural modules, and phylogenetic relatedness indicated their evolutionary lineage to the type-4 secretion system (T4SS) ICEclc family, thus predicting these elements to be integrative conjugative elements (ICEs). These GIs were found to be present as a single copy in the genome and the encoded phenotypic traits were found to be stable, even in the absence of selection pressure. ICEnahCSV86 harbors naphthalene catabolic (nah-sal) cluster, while PBGI-1 harbors Co-Zn-Cd (czc) efflux genes as cargo modules, whereas PBGI-2 was attributed to as a mixed-function element. The ICEnahCSV86 has been reported to be conjugatively transferred (frequency of 7 × 10–8/donor cell) to Stenotrophomonas maltophilia CSV89. Genome-wide comparative analyses of aromatic-degrading bacteria revealed nah-sal clusters from several Pseudomonas spp. as part of probable ICEs, syntenic to conjugatively transferable ICEnahCSV86 of strain CSV86T, suggesting it to be a prototypical element for naphthalene degradation. It was observed that the plasmids harboring nah-sal clusters were phylogenetically incongruent with predicted ICEs, suggesting genetic divergence of naphthalene metabolic clusters in the Pseudomonas population. Gene synteny, divergence estimates, and codon-based Z-test indicated that ICEnahCSV86 is probably derived from PBGI-2, while multiple recombination events masked the ancestral lineage of PBGI-1. Diversifying selection pressure (dN-dS = 2.27–4.31) imposed by aromatics and heavy metals implied the modular exchange-fusion of various cargo clusters through events like recombination, rearrangement, domain reshuffling, and active site optimization, thus allowing the strain to evolve, adapt, and maximize the metabolic efficiency in a contaminated niche. The promoters (Pnah and Psal) of naphthalene cargo modules (nah, sal) on ICEnahCSV86 were proved to be efficient for heterologous protein expression in Escherichia coli. GI-based genomic plasticity expands the metabolic spectrum and versatility of CSV86T, rendering efficient adaptation to the contaminated niche. Such isolate(s) are of utmost importance for their application in bioremediation and are the probable ideal host(s) for metabolic engineering.
Detection of Brain Network Communities During Natural Speech Comprehension From Functionally Aligned EEG Sources

In recent years, electroencephalograph (EEG) studies on speech comprehension have been extended from a controlled paradigm to a natural paradigm. Under the hypothesis that the brain can be approximated as a linear time-invariant system, the neural response to natural speech has been investigated extensively using temporal response functions (TRFs). However, most studies have modeled TRFs in the electrode space, which is a mixture of brain sources and thus cannot fully reveal the functional mechanism underlying speech comprehension. In this paper, we propose methods for investigating the brain networks of natural speech comprehension using TRFs on the basis of EEG source reconstruction. We first propose a functional hyper-alignment method with an additive average method to reduce EEG noise. Then, we reconstruct neural sources within the brain based on the EEG signals to estimate TRFs from speech stimuli to source areas, and then investigate the brain networks in the neural source space on the basis of the community detection method. To evaluate TRF-based brain networks, EEG data were recorded in story listening tasks with normal speech and time-reversed speech. To obtain reliable structures of brain networks, we detected TRF-based communities from multiple scales. As a result, the proposed functional hyper-alignment method could effectively reduce the noise caused by individual settings in an EEG experiment and thus improve the accuracy of source reconstruction. The detected brain networks for normal speech comprehension were clearly distinctive from those for non-semantically driven (time-reversed speech) audio processing. Our result indicates that the proposed source TRFs can reflect the cognitive processing of spoken language and that the multi-scale community detection method is powerful for investigating brain networks.
Synaptopathy in Guinea Pigs Induced by Noise Mimicking Human Experience and Associated Changes in Auditory Signal Processing

Noise induced synaptopathy (NIS) has been researched extensively since a large amount of synaptic loss without permanent threshold shift (PTS) was found in CBA mice after a brief noise exposure. However, efforts to translate these results to humans have met with little success—and might not be possible since noise exposure used in laboratory animals is generally different from what is experienced by human subjects in real life. An additional problem is a lack of morphological data and reliable functional methods to quantify loss of afferent synapses in humans. Based on evidence for disproportionate synaptic loss for auditory nerve fibers (ANFs) with low spontaneous rates (LSR), coding-in-noise deficits (CIND) have been speculated to be the major difficulty associated with NIS without PTS. However, no robust evidence for this is available in humans or animals. This has led to a re-examination of the role of LSR ANFs in signal coding in high-level noise. The fluctuation profile model has been proposed to support a role for high-SR ANFs in the coding of high-level noise in combination with efferent control of cochlear gain. This study aimed to induce NIS by a low-level, intermittent noise exposure mimicking what is experienced in human life and examined the impact of the NIS on temporal processing under masking. It also evaluated the role of temporal fluctuation in evoking efferent feedback and the effects of NIS on this feedback.
The Interplay Between Poor Sleep and Work-Related Health

Objectives Sleep disorders can arise from work. Employees who experience work overload are more likely to develop sleep problems. Poor sleep leads to decreased performance, sick leave, and accidents. Therefore, sleep disorders may be linked to workplace hazards as well as decreased occupational health, however, the relationship remains unknown. Methods This relationship was examined using secondary data analysis of aggregated survey data from 97 companies based in Germany between 2003 and 2020 as part of Workplace Health Management project. Two extreme groups with respect to sleep problems were analyzed (N = 4,865 + 9,795). The survey “Diagnosis of corporate health” contained 137 individual questions which recorded all relevant working conditions, aspects of health, and one question relating to insomnia traits. A one-way analysis of variance was used to examine whether and to what extent the potentials, hazards, and health aspects differed between employees depending on their perceived sleep problems. In addition, multiple linear regressions were used to determine whether and to what extent work characteristics affect various health aspects for both good and poor sleepers. Results In total, 49.7% of staff reported moderate difficulty falling and/or remaining asleep. These poor sleepers perceived all health potentials worse than good sleepers, especially on scales such as fair assessment, work climate, and learning at work. Furthermore, poor sleepers perceived health hazards (physical environmental stress, job insecurity, and time pressure) more whilst positive health indicators (joy of work and confidence) were perceived less. Conclusion Overall, the determination of sleep difficulties could be used as a substantial health indicator. Also, these sleep problems are reported more frequently in certain occupations compared to others, which could mean that the perception of sleep health varies between professions. Therefore, it is important to implement specific recommendations for each industry in order to improve working conditions for poor sleepers which in turn, improves their health.
[68Ga]Ga-DOTA-Siglec-9 Detects Pharmacodynamic Changes of FAP-Targeted IL2 Variant Immunotherapy in B16-FAP Melanoma Mice

Vascular adhesion protein-1 (VAP-1) is an inflammation-inducible adhesion molecule, which supports contact between leukocytes and inflamed endothelium. There is evidence that VAP-1 is involved in the recruitment of leukocytes to melanoma tumors. Interleukin-2 (IL-2)-based immunotherapy is an efficient therapy that promotes immune system activity against cancers but is associated with toxicity. In the present study, we evaluated the feasibility of PET/CT imaging using the radiotracer [68Ga]Ga-DOTA-Siglec-9, which is targeted to VAP-1, to monitor pharmacodynamic effects of a novel FAP-IL2v immunocytokine (a genetically engineered variant of IL-2 fused with fibroblast activation protein) in the B16-FAP melanoma model. At 9 days after the inoculation of B16-FAP melanoma cells, mice were studied with [68Ga]Ga-DOTA-Siglec-9 PET/CT as a baseline measurement. Immediately after baseline imaging, mice were treated with FAP-IL2v or vehicle, and treatment was repeated 3 days later. Subsequent PET/CT imaging was performed 3, 5, and 7 days after baseline imaging. In addition to in vivo PET imaging, ex vivo autoradiography, histology, and immunofluorescence staining were performed on excised tumors. B16-FAP tumors were clearly detected with [68Ga]Ga-DOTA-Siglec-9 PET/CT during the follow-up period, without differences in tumor volume between FAP-IL2v-treated and vehicle-treated groups. Tumor-to-muscle uptake of [68Ga]Ga-DOTA-Siglec-9 was significantly higher in the FAP-IL2v-treated group than in the vehicle-treated group 7 days after baseline imaging, and this was confirmed by tumor autoradiography analysis. FAP-IL2v treatment did not affect VAP-1 expression on the tumor vasculature. However, FAP-IL2v treatment increased the number of CD8+ T cells and natural killer cells in tumors. The present study showed that [68Ga]Ga-DOTA-Siglec-9 can detect B16-FAP tumors and allows monitoring of FAP-IL2v treatment.
Learning Causal Effects From Observational Data in Healthcare: A Review and Summary

Causal inference is a broad field that seeks to build and apply models that learn the effect of interventions on outcomes using many data types. While the field has existed for decades, its potential to impact healthcare outcomes has increased dramatically recently due to both advancements in machine learning and the unprecedented amounts of observational data resulting from electronic capture of patient claims data by medical insurance companies and widespread adoption of electronic health records (EHR) worldwide. However, there are many different schools of learning causality coming from different fields of statistics, some of them strongly conflicting. While the recent advances in machine learning greatly enhanced causal inference from a modeling perspective, it further exacerbated the fractured state in this field. This fractured state has limited research at the intersection of causal inference, modern machine learning, and EHRs that could potentially transform healthcare. In this paper we unify the classical causal inference approaches with new machine learning developments into a straightforward framework based on whether the researcher is most interested in finding the best intervention for an individual, a group of similar people, or an entire population. Through this lens, we then provide a timely review of the applications of causal inference in healthcare from the literature. As expected, we found that applications of causal inference in medicine were mostly limited to just a few technique types and lag behind other domains. In light of this gap, we offer a helpful schematic to guide data scientists and healthcare stakeholders in selecting appropriate causal methods and reviewing the findings generated by them.
Dramatic Efficacy of Interferon and Vemurafenib on Psychiatric Symptoms Revealing BRAFV600E -Mutated Erdheim–Chester Disease: A Case Report

Erdheim–Chester disease (ECD) is a rare condition with underestimated neurological involvement. Mild psychiatric symptoms such as mood swings have been rarely described in the clinical spectrum of neuro-ECD. We here describe the first patient with psychiatric manifestations of delirium revealing ECD with neurological involvement with favorable evolution under interferon followed by BRAF inhibitor monotherapy. An 81-year-old woman was referred to the hospital because of delirium and severe cognitive impairment associated with a cerebellar syndrome. Brain magnetic resonance imaging showed “FLAIR-changes” lesions in the pons and upper cerebellum peduncles. Blood and cerebrospinal fluid (CSF) analyses showed normal results except for an elevated neopterin level in the CSF. Whole-body CT scan (18FDG-PET) showed peri-nephric fat infiltration and aorta adventitia sheathing with radiotracer uptake in the pons, vessels, peri-nephric fat, and bone lesions, which was characteristic of ECD. The diagnosis was confirmed on perirenal tissue biopsy, which also showed a BRAFV600E mutation. Treatment with interferon resulted in the resolution of delirium, and treatment with BRAF inhibitor subsequently resulted in a partial remission of all active sites. This case highlights that delirium can be the first manifestation of neurodegenerative ECD. ECD should be screened in unexplained psychiatric features as interferon and targeted therapy appear to be effective in this situation.
Monitoring Dryland Trees With Remote Sensing. Part A: Beyond CORONA—Historical HEXAGON Satellite Imagery as a New Data Source for Mapping Open-Canopy Woodlands on the Tree Level

Monitoring woody cover by remote sensing is considered a key methodology towards sustainable management of trees in dryland forests. However, while modern very high resolution satellite (VHRS) sensors allow woodland mapping at the individual tree level, the historical perspective is often hindered by lack of appropriate image data. In this first study employing the newly accessible historical HEXAGON KH-9 stereo-panoramic camera images for environmental research, we propose their use for mapping trees in open-canopy conditions. The 2–4 feet resolution panchromatic HEXAGON satellite photographs were taken 1971–1986 within the American reconnaissance programs that are better known to the scientific community for their lower-resolution CORONA images. Our aim is to evaluate the potential of combining historical CORONA and HEXAGON with recent WorldView VHRS imagery for retrospective woodland change mapping on the tree level. We mapped all trees on 30 1-ha test sites in open-canopy argan woodlands in Morocco in the field and from the VHRS imagery for estimating changes of tree density and size between 1967/1972 and 2018. Prior to image interpretation, we used simulations based on unmanned aerial system (UAS) imagery for exemplarily examining the role of illumination, viewing geometry and image resolution on the appearance of trees and their shadows in the historical panchromatic images. We show that understanding these parameters is imperative for correct detection and size-estimation of tree crowns. Our results confirm that tree maps derived solely from VHRS image analysis generally underestimate the number of small trees and trees in clumped-canopy groups. Nevertheless, HEXAGON images compare remarkably well with WorldView images and have much higher tree-mapping potential than CORONA. By classifying the trees in three sizes, we were able to measure tree-cover changes on an ordinal scale. Although we found no clear trend of forest degradation or recovery, our argan forest sites show varying patterns of change, which are further analysed in Part B of our study. We conclude that the HEXAGON stereo-panoramic camera images, of which 670,000 worldwide will soon be available, open exciting opportunities for retrospective monitoring of trees in open-canopy conditions and other woody vegetation patterns back into the 1980s and 1970s.
Meaning, Message, and Rhetoric in Kitabisa.com Advertisement

This research focused to found the meanings, messages, signs and types of rhetoric used in Kitabisa.com advertisements. The was qualitative approach and descriptive analysis techniques. The data source of this research was taken from official website Kitabisa.com www.kitabisa. com. The data taken from one sample from each fifteen categories of donations published in 2021. The results of this research found that the fifteen data were contained signs which found in the images and language used in Kitabisa.com advertisements. Denotation meanings were to invite the society to donate. The connotative meaning were implied implisit meaning such as satire, criticism, inspirational stories and invested a brand image. Myths were closely related with the society because came from themselves. The messages were another piece of informations that want to conveyed by the fundraiser. Types of rhetoric results showed that 4 advertisements data used homonym . The types of rhetoric such rhetorical questions, rhyme and parison , were found in each of the 2 advertisements data. The types of rethoric such anaphora, hyperbole, antanaclasis, alliteration and anadiplosis found in 1 advertisements data. The image aspect of donations affected the amount of donations especially sick people because they were considered more able to attract public sympathies.
Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States

Abstract. Global climate models (GCMs) have advanced in many ways as computing power has allowed more complexity and finer resolutions. As GCMs reach storm-resolving scales, they need to be able to produce realistic precipitation intensity, duration, and frequency at fine scales with consideration of scale-aware parameterization. This study uses a state-of-the-art storm-resolving GCM with a nonhydrostatic dynamical core – the Model for Prediction Across Scales (MPAS), incorporated in the atmospheric component (Community Atmosphere Model, CAM) of the open-source Community Earth System Model (CESM), within the System for Integrated Modeling of the Atmosphere (SIMA) framework (referred to as SIMA-MPAS). At uniform coarse (here, at 120 km) grid resolution, the SIMA-MPAS configuration is comparable to the standard hydrostatic CESM (with a finite-volume (FV) dynamical core) with reasonable energy and mass conservation on climatological timescales. With the comparable energy and mass balance performance between CAM-FV (workhorse dynamical core) and SIMA-MPAS (newly developed dynamical core), it gives confidence in SIMA-MPAS's applications at a finer resolution. To evaluate this, we focus on how the SIMA-MPAS model performs when reaching a storm-resolving scale at 3 km. To do this efficiently, we compose a case study using a SIMA-MPAS variable-resolution configuration with a refined mesh of 3 km covering the western USA and 60 km over the rest of the globe. We evaluated the model performance using satellite and station-based gridded observations with comparison to a traditional regional climate model (WRF, the Weather Research and Forecasting model). Our results show realistic representations of precipitation over the refined complex terrains temporally and spatially. Along with much improved near-surface temperature, realistic topography, and land–air interactions, we also demonstrate significantly enhanced snowpack distributions. This work illustrates that the global SIMA-MPAS at storm-resolving resolution can produce much more realistic regional climate variability, fine-scale features, and extremes to advance both climate and weather studies. This next-generation storm-resolving model could ultimately bridge large-scale forcing constraints and better inform climate impacts and weather predictions across scales.
VIRTUAL PROTOTYPE-BASED KINEMATIC MODELING AND SIMULATION OF A MULTI-MODE AMPHIBIOUS ROBOT

: The amphibious robot, which has the capability of multi-mode motion, can maneuver diverse environments with high mobility and adaptability. These are employed in the area of reconnaissance, search and rescue operations, and monitoring. The existing amphibious robots have lower maneuverability over the crawling period on uneven and slope surfaces on the land. In this paper, a kinematic model of the amphibious robot based on virtual prototyping is designed for multi-mode locomotion. ADAMS (Automated dynamic analysis of mechanical systems) is a multi-body dynamic solver adopted to build the simulation model for the robot. The novel amphibious robot employs a Rockerbogie mechanism equipped with wheel paddles. The locomotion analysis on land involves straight-going and obstacle negotiation, which is simulated using ADAMS. The simulation analysis result demonstrates increased maneuverability, achieving a robot's velocity of 1.6 m/s. Normal forces on the front and rear wheels show equal load distribution, contributing more to the robot’s equilibrium over uneven terrain. The simulation result reflects the accurate kinematic characteristics of the amphibious robot and provides a theoretical basis for developing an algorithm for robot motion control and optimization. Further, this research will concentrate on the kinematic simulation maneuvering in water mode with the wheel paddle.
[The use of neuromodulation for the treatment of tremor].

BACKGROUND Tremor may be a disabling disorder and pharmacologic treatment is the first-line therapy for these patients. Nevertheless, this treatment may lead to a satisfactory tremor reduction in only 50% of patients with essential tremor. Thalamotomy was the treatment of choice for tremor refractory to medical therapy until deep brain stimulation (DBS) of the ventral intermedius nucleus (Vim) of the thalamus has started being used. Nowadays, thalamotomy is rarely performed. METHODS This article is a non-systematic review of the indications, results, programming parameters and surgical technique of DBS of the Vim for the treatment of tremor. RESULTS In spite of the fact that it is possible to achieve similar clinical results using thalamotomy or DBS of the Vim, the former causes more adverse effects than the latter. Furthermore, DBS can be used bilaterally, whereas thalamotomy has a high risk of causing disartria when it is performed in both sides. DBS of the Vim achieved an adequate tremor improvement in several series of patients with tremor caused by essential tremor, Parkinson's disease or multiple sclerosis. Besides the Vim, there are other targets, which are being used by some authors, such as the zona incerta and the prelemniscal radiations. CONCLUSION DBS of the Vim is a useful treatment for disabling tremor refractory to medical therapy. It is essential to carry out an accurate patient selection as well as to use a proper surgical technique. The best stereotactic target for tremor is still unknown, although the Vim is the most used one.
An analogue of the Weil representation for G2.

Let . Fbe a nonarchimedian local field of characteristic 0. Let ψ be a unitary character of F. Let G be a simple split group over Fand g the corresponding Lie algebra. Let i^^ g be a neighborhood of 0 such that the exponential map exp : g -» G is well defined on i^. If τ is an irreducible representation of G we can define a functional Βτ (character) on the space of locally constant, compactly supported measures / on iT by