Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictors of treatment intensification in uncontrolled hypertension

Purpose: Prior studies have shown that treatment intensification for patients presenting with uncontrolled hypertension (HTN) rarely occurs, even during visits to the patient's own primary care physicians (PCPs). In this article, we identified predictors of treatment intensification for uncontrolled HTN. Methods: We conducted a cross-sectional study using nationally representative survey data on visits by patients aged 18 or above with uncontrolled HTN, defined as a recorded SBP at least 140 and/or a DBP at least 90 using data from the National Ambulatory Medical Care Survey (NAMCS) 2008–2018. Our outcome is treatment intensification defined as the addition of a new blood pressure medication. Results: We analyzed 22 559 visits to PCPs where uncontrolled HTN was noted, representing 801 023 786 visits nationally. Among these encounters, 2138 (10.3%) of the visits resulted in treatment intensification. Visits with the patient's own PCP had higher rates of treatment intensification than visits to another PCP (10.8 vs. 5.9%, P < 0.0001). Visits for patients previously on antihypertensive medications had lower rates of treatment intensification (11% for no medications, 10.4% for one medication, 6.6% for ≥2 medications, P < 0.0001), but there were no statistically significant differences in rates of intensification for those with relevant comorbidities (9.4% for no chronic conditions, 10.8% for one to two chronic conditions, 8.9% for at least three chronic conditions, P = 0.12). Multivariable adjusted results were similar to the unadjusted findings. Conclusion: Visits for patients with uncontrolled HTN rarely result in treatment intensification. Substantial opportunity exists to improve management of HTN, particularly for patients on fewer medications or seen by a covering provider.
Bacteria from the skin of salamanders inhibit Batrachochytrium dendrobatidis

Abstract The fungal pathogen Batrachochytrium dendrobatidis (Bd) is causing a worldwide decline in salamander populations. Bd causes chytridiomycosis in salamanders, which is a lethal infection of keratinized epithelial cells. Previous studies have characterized many microbial species from the skin of amphibians and shown some of them can inhibit Bd by producing antifungal metabolites. In this research, the skin microbiota of four salamanders was sampled by separately swabbing their ventral and dorsal sides. Mixed microbial cultures were obtained on R2A media from the swabs and 64 unique colonies were isolated. Microorganisms were characterized by describing colony color, shape, size, margin, texture, elevation, and pictures were taken. The microorganisms were Gram stained to determine cellular morphologies and 52 were Gram-negative rods, 11 Gram positive (seven rods and four cocci), and one was a fungus. PCR was used to amplify portions of the 16S (prokaryotic) or 18S (eukaryotic) rRNA genes. The PCR products were purified, sequenced, and Basic Local Assignment Search Tool (BLAST) was used to identify the microorganisms, at least to the genus level. The most common genera were Chryseobacterium, Pseudomonas, Acinetobacter, and Bacillus, respectively. Competition assays were performed on tryptone agar plates to test the microorganisms for their ability to inhibit Bd. Nine microorganisms tested positive for inhibiting Bd, and each salamander had at least two isolates that tested positive. Pseudomonas species moraviensis and koreensis produced the largest zones of inhibition, and co-culturing the microorganisms increased the size of the zones by having an additive effect.
Impact of Some Ecological Factors on the Occurrence and Distribution of Mitosporic Fungi in the Cold Desert of Ladakh (India).

Extreme nature of climate and topographical conditions may affect the soil properties, which in turn affect the occurrence and distribution of mycoflora inhabiting cold desert high altitude. In view of this, investigations were carried out to assess the ecological factors regulating the distribution and survival of mitosporic fungi inhabiting the base soil of Moonland (Ladakh), a completely barren, distinctive, splendid, moon-like landscape situated in the Ladakh region of Jammu and Kashmir state (India). The soils were nearly neutral to slightly alkaline and with moderate electrical conductivity. Electrical conductivity showed a negative effect on the occurrence and distribution of mitosporic fungi as well as on majority of the macronutrients. All the soil samples showed good amount of organic matter and the mitosporic fungi were generally found to be proportional to the soil organic matter, organic carbon and pH. The soil samples also possessed high amounts of phosphorus but low levels of potassium. The micronutrients were present in sufficient amounts in all the investigated soil samples. Physico-chemical soil parameters and majority of the macronutrients played an important role in the occurrence, diversity, distribution, and relative abundance of fungal species in the investigated soil samples.
Generating Usage-related Questions for Preference Elicitation in Conversational Recommender Systems

A key distinguishing feature of conversational recommender systems over traditional recommender systems is their ability to elicit user preferences using natural language. Currently, the predominant approach to preference elicitation is to ask questions directly about items or item attributes. Users searching for recommendations may not have deep knowledge of the available options in a given domain. As such, they might not be aware of key attributes or desirable values for them. However, in many settings, talking about the planned use of items does not present any difficulties, even for those that are new to a domain. In this paper, we propose a novel approach to preference elicitation by asking implicit questions based on item usage. As one of the main contributions of this work, we develop a multi-stage data annotation protocol using crowdsourcing, to create a high-quality labeled training dataset. Another main contribution is the development of four models for the question generation task: two template-based baseline models and two neural text-to-text models. The template-based models use heuristically extracted common patterns found in the training data, while the neural models use the training data to learn to generate questions automatically. Using common metrics from machine translation for automatic evaluation, we show that our approaches are effective in generating elicitation questions, even with limited training data. We further employ human evaluation for comparing the generated questions using both pointwise and pairwise evaluation designs. We find that the human evaluation results are consistent with the automatic ones, allowing us to draw conclusions about the quality of the generated questions with certainty. Finally, we provide a detailed analysis of cases where the models show their limitations.
Topological Evaluation of Realistic Mobility Models for Spontaneous Wireless Networks Using Graph Theory Metrics

In recent years, the exponential growth of mobile devices connected to access networks has led to the emergence of connection architectures characterized by a high density of end devices. This, in turn, has posed significant challenges in access management. As a result, the scientific community is increasingly recognizing the crucial need to develop equitable and unbiased access control mechanisms. A fundamental starting point is to conduct a comprehensive analysis of these massive end-device architectures, treating them as high-density graphs of interconnected nodes. In this work, we generated massive topologies/architectures using synthetic models of human mobility that accurately reflect real-world human behavior. Subsequently, we evaluated and compared these topologies using six key metrics derived from graph theory. Additionally, we established connections between nodes within each topology based on the concept of spontaneous Wireless Mesh Networks. The outcomes of our analysis shed light on mobility models that demonstrated superior performance in specific metrics, while also proposing a methodology to effectively characterize these mobility models.
PEM360: A dataset of 360° videos with continuous Physiological measurements, subjective Emotional ratings and Motion traces

From a user perspective, immersive content can elicit more intense emotions than flat-screen presentations. From a system perspective, efficient storage and distribution remain challenging, and must consider user attention. Understanding the connection between user attention, user emotions and immersive content is therefore key. In this work, we will present the PEM360 dataset of user head movements and gaze recordings in 360° videos, along with self-reported emotional ratings of valence and arousal, and continuous physiological measurement of electrodermal activity and heart rate. The stimuli are selected to enable the spatiotemporal analysis of the connection between content, user motion and emotion. We then present findings on the tri-partite connection between user attention, user emotion and visual content in immersive environments. This involves analyzing low-level and high-level saliency of video content, in connection with the data on the user’s state from the PEM360 dataset. This work was published and presented at ACM MMSys 2022 Open Dataset and Software track[2] and at ICIP 2022 [1].
Spontaneous network transitions predict somatosensory perception

Sensory perception is essential for transforming incoming information in the brain into targeted behavior. Thus, variations in our perceptions are ubiquitously associated with human behavioral performance. Since our brains are everlastingly active, the question arises whether spontaneous brain activity relates to perceptual variability and subsequent task performance. We analyzed spontaneous whole-brain activity preceding the trials of an ambiguous tactile temporal discrimination task and identified time-resolved brain networks from the seconds before each trial. Transitions to a frontal and a multi-frequency network across the brain were essential for the correct percept. Conversely, incorrect percepts are mainly preceded by transitions to an alpha-parietal network. Moreover, brain switches occur faster during the period before stimulus presentation for correct stimuli detection, suggesting the need for enhanced network flexibility during this phase. Thus, the interaction between whole-brain networks in the spontaneous pre-stimulus period contributes to the perception during the task.
Electron Spin Resonance Dating of the Late Cenozoic Deformation of the Huoerguosi-Manas-Tugulu Reverse Faults along Southern Edge of Junggar Basin

This paper focuses on the late Cenozoic deformation of the Huoerguosi-Manas-Tugulu reverse fault zone in the southern edge of Zhungaer basin. Twelve gypsum, fault gouge and quartz vein samples with different stuuctural significances were collected and dated by using the Electronic Spin Resonance (ESR) method. The results show that the Huoerguosi-Manas-Tugulu reverse faults has subjected to three major phases of deformation. The onset of reverse faults formation is at about 1500 ka ago and the reverse faults readjusted at 400～1000 ka and 80～120 ka, respectively. These data, along with evidence foruplift phases in Tibetean platean, support the model that relate reverse faulting to uplift processes occurring within the Tibetan plateau and that the late Cenozoic uplif-ting of Tianshan Mountain and tectonic deformation of foreland basins are the results of the collision between India and Eurasia plates.
Application of Transfer Learning for Rapid Calibration of Spatially-resolved Diffuse Reflectance Probes for Extraction of Tissue Optical Properties

Significance Treatment planning for light-based therapies including photodynamic therapy requires tissue optical property knowledge. These are recoverable with spatially-resolved diffuse reflectance spectroscopy (DRS), but requires precise source-detector separation (SDS) determination and time-consuming simulations. Aim An artificial neural network (ANN) to map from DRS at short SDS to optical properties was created. This trained ANN was adapted to fiber-optic probes with varying SDS using transfer learning. Approach An ANN mapping from measurements to Monte Carlo simulation to optical properties was created with one fiber-optic probe. A second probe with different SDS was used for transfer learning algorithm creation. Data from a third were used to test this algorithm. Results The initial ANN recovered absorber concentration with RMSE=0.29 µM (7.5% mean error) and µs’ at 665 nm (µs,665’) with RMSE=0.77 cm-1 (2.5% mean error). For probe-2, transfer learning significantly improved absorber concentration (0.38 vs. 1.67 µM, p=0.0005) and µs,665’ (0.71 vs. 1.8 cm-1, p=0.0005) recovery. A third probe also showed improved absorber (0.7 vs. 4.1 µM, p<0.0001) and µs,665’ (1.68 vs. 2.08 cm-1, p=0.2) recovery. Conclusions A data-driven approach to optical property extraction can be used to rapidly calibrate new fiber-optic probes with varying SDS, with as few as three calibration spectra.
Genome Editing Outcomes Reveal Mycobacterial NucS Participates in a Short-Patch Repair of DNA Mismatches

In the canonical DNA mismatch repair (MMR) mechanism in bacteria, if during replication a nucleotide is incorrectly mis-paired with the template strand, the resulting repair of this mis-pair can result in the degradation and re-synthesis of hundreds or thousands of nucleotides on the newly-replicated strand (long-patch repair). While mycobacteria, which include important pathogens such as Mycobacterium tuberculosis, lack the otherwise highly-conserved enzymes required for the canonical MMR reaction, it was found that disruption of a mycobacterial mismatch-sensitive endonuclease NucS results in a hyper-mutative phenotype, which has led to the idea that NucS might be involved in a cryptic, independently-evolved DNA MMR mechanism. It has been proposed that nuclease activity at a mismatch might result in correction by homologous recombination (HR) with a sister chromatid. Using oligonucleotide recombination, which allows us to introduce mismatches during replication specifically into the genomes of a model for M. tuberculosis, Mycobacterium smegmatis, we find that NucS participates in a direct repair of DNA mismatches where the patch of excised nucleotides is largely confined to within ∼5 - 6 bp of the mis-paired nucleotides, which is inconsistent with mechanistic models of canonical mycobacterial HR or other double-strand break (DSB) repair reactions. The results presented provide evidence of a novel NucS-associated mycobacterial MMR mechanism occurring in vivo to regulate genetic mutations in mycobacteria.
Assessing nanobody interaction with SARS-CoV-2 Nsp9

The interaction between SARS-CoV-2 non-structural protein Nsp9 and the nanobody 2NSP90 was investigated by NMR spectroscopy using the paramagnetic perturbation methodology PENELOP (Paramagnetic Equilibrium vs Nonequilibrium magnetization Enhancement or LOss Perturbation). The Nsp9 monomer is an essential component of the replication and transcription complex (RTC) that reproduces the viral gRNA for subsequent propagation. Therefore preventing Nsp9 recruitment in RTC would represent an efficient antiviral strategy that could be applied to different coronaviruses, given the Nsp9 relative invariance. The NMR results were consistent with a previous characterization suggesting a 4:4 Nsp9-to-nanobody stoichiometry with the occurrence of two epitope pairs on each of the Nsp9 units that establish the inter-dimer contacts of Nsp9 tetramer. The oligomerization state of Nsp9 was also analyzed by molecular dynamics simulations and both dimers and tetramers resulted plausible. However a different distribution of the mapped epitopes on the tetramer surface with respect to the former 4:4 complex could also be possible, as well as different stoichiometries of the Nsp9-nanobody assemblies such as the 2:2 stoichiometry suggested by the recent crystal structure of the Nsp9 complex with 2NSP23 (PDB ID: 8dqu), a nanobody exhibiting essentially the same affinity as 2NSP90. The experimental NMR evidence, however, ruled out the occurrence in liquid state of the relevant Nsp9 conformational change observed in the same crystal structure.
Hyperbolic graph embedding of MEG brain networks to study brain alterations in individuals with subjective cognitive decline

An expansive area of research focuses on discerning patterns of alterations in functional brain networks from the early stages of Alzheimer’s disease, even at the subjective cognitive decline (SCD) stage. Here, we developed a novel hyperbolic MEG brain network embedding framework for transforming high-dimensional complex MEG brain networks into lower-dimensional hyperbolic representations. Using this model, we computed hyperbolic embeddings of the MEG brain networks of two distinct participant groups: individuals with SCD and healthy controls. We demonstrated that these embeddings preserve both local and global geometric information, presenting reduced distortion compared to rival models, even when brain networks are mapped into low-dimensional spaces. In addition, our findings showed that the hyperbolic embeddings encompass unique SCD-related information that improves the discriminatory power above and beyond that of connectivity features alone. Notably, we introduced a unique metric—the radius of the node embeddings—which effectively proxies the hierarchical organization of the brain. Using this metric, we identified subtle hierarchy organizational differences between the two participant groups, suggesting increased hierarchy in the dorsal attention, frontoparietal, and ventral attention subnetworks among the SCD group. Last, we assessed the correlation between these hierarchical variations and cognitive assessment scores, revealing associations with diminished performance across multiple cognitive evaluations in the SCD group. Overall, this study presents the first evaluation of hyperbolic embeddings of MEG brain networks, offering novel insights into brain organization, cognitive decline, and potential diagnostic avenues of Alzheimer’s disease.
Genome of the glacier alga Ancylonema and its insights into the evolution of streptophyte life on ice and land

Contemporary glaciers and ice sheets are home to communities of streptophyte glacier algae that must balance their requirements for photosynthesis and growth with tolerance of extremes in temperature, desiccation and UV radiation. These same environmental challenges have been hypothesized as the driving force behind the evolution of land plants from streptophyte algal ancestors in the Cryogenian (720–635 million years ago). Here, we sequence, assemble and analyze the metagenome-assembled genome (MAG) of the glacier alga Ancylonema nordenskiöldii to investigate its adaptations to life in ice, and whether this represents a vestige of Cryogenian anydrophyte exaptations. Phylogenetic analysis confirms the placement of glacier algae within the sister lineage to land plants, Zygnematophyceae. The MAG is characterized by an expansion of genes involved in high irradiance and UV light tolerance, whilst lineage-specific diversification led to the novel screening pigmentation of glacier algae. We found no support for the hypothesis of a common genomic basis for adaptations to ice and to land in streptophytes. Comparative genomic analysis revealed that reductive genome evolution in the ancestor of Zygnematophyceae correlates with their reductive morphological evolution. This first genome-scale data for glacier algae supports an Ancylonema-specific adaptation to the cryosphere, as well as shedding light on the genome evolution of land plants and Zygnematophyceae.
A hybrid method for size characterization of coarse subsurface fluvial sediments

This paper introduces and evaluates a novel method for ascertaining the grain‐size distribution of subsurface sediments that involves profoundly less sampling effort than standard methods. It is based on hybrid sampling principles previously applied to the construction of synthetic surface grain‐size distributions. The method is developed from an empirical demonstration of the approximate similarity of surface and subsurface grain‐size distributions when compared over a common range of sizes. Subsurface hybrid models are found to provide good facsimiles of grain‐size distributions deﬁned using standard criteria and to yield distribution percentiles with millimetre accuracy. The technique is presented as an expedient alternative to standard methods for large, perennial gravel‐bed rivers. As this is a new technique, prudent application is advised in lieu of further investigation. Copyright © 2004 John Wiley & Sons, Ltd.
A seismological study of normal faulting in the Demirci, Alaşehir and Gediz earthquakes of 1969–70 in western Turkey: implications for the nature and geometry of deformation in the continental crust

Summary. In this study, seismological techniques are combined with surface observations to investigate the faulting associated with three large earthquakes in western Turkey. All involved normal faulting that nucleated at 6–10 km depth with dips in the range 30–50°. The two largest earthquakes, at Alasehir (1969.3.28) and Gediz (1970.3.28), were clearly multiple events and their seismograms indicate that at least two discrete subevents were involved in producing the observed surface faulting. In addition, their seismograms contain later, longer-period signals that are likely to represent source, not structure or propagation, complexities. These later signals can be modelled by subevents with long time functions on almost flat detachment-type faults. As a result of these observations, we propose a model for the deformation of the lower crust, in which brittle failure of the top part occurs when high strain rates are imposed during an earthquake that ruptures right through the upper, brittle crust. Under these special circumstances, seismic motion occurs on discrete faults in the lower crust, which otherwise normally deforms by distributed creep. In the case of the normal faults studied here, motion in the uppermost lower crust takes place on shallow dipping faults that are downward continuations of the steeper faults that break to the surface. The faults thus have an overall listric geometry, flattening into a weak zone below the brittle layer at a depth that is probably dependent on the termperature gradient. This interpretation explains why detachment-type mechanisms are not seen in first motion fault plane solutions of normal faulting earthquakes, and suggests an origin for the Metamorphic Core Complexes seen in the Basin and Range Province, which probably represent flat lower crustal faults, analogous to those postulated at Alasehir and Gediz, that have been uplifted to the surface.
Lifestyle, Coping Resources, and Trauma Symptoms: Predicting Post-traumatic Growth

ABSTRACT:Interpersonal trauma influences levels of post-traumatic stress and post- traumatic growth. Several factors are associated with post-traumatic growth, such as symptom severity, personality traits, and coping resources (Tedeschi & Calhoun, 2004). This study examined the role of trauma symptoms, belonging and social interest (BSI), tension control (TC), social support (SS), and post-traumatic growth (PTG), and a moderated mediation model in a sample of individuals who experienced interpersonal trauma. Both SS and TC contributed to PTG. SS and TC mediated the association between trauma symptoms and PTG. BSI moderated trauma symptoms in SS and trauma symptoms in TC. High BSI accounted for variance in the relationship between trauma symptoms and SS, and lower BSI accounted for more variance between trauma symptoms and TC.