Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonoperative Management and Novel Imaging for Posterior Circumflex Humeral Artery Injury in Volleyball

Abstract We report on a 34-yr-old male elite volleyball player with symptomatic emboli in the spiking hand from a partially thrombosed aneurysm of the posterior circumflex humeral artery (PCHA) in his dominant shoulder. At initial diagnosis and follow-up, a combination of time-resolved and high-resolution steady state contrast-enhanced magnetic resonance angiography (CE-MRA) enabled detailed visualization of: (1) emboli that were not detectable by vascular ultrasound; and (2) the PCHA aneurysm, including compression during abduction and external rotation (ABER provocation). At 15-month follow-up, including forced cessation of volleyball activities over the preceding 9 months, the PCHA aneurysm remained unchanged. Central filling defects in the palmar arch and digital arteries resolved over time and affected arterial vessel segments showed postthrombotic changes. Digital blood pressure values improved substantially and almost normalized during follow-up. In conclusion, this case report is the first to show promising results of nonoperative management for a vascular shoulder overuse injury in a professional volleyball player as an alternative to invasive therapeutic options.
Rhodopsin optogenetic toolbox v2.0 for light-sensitive excitation and inhibition in Caenorhabditis elegans

In optogenetics, rhodopsins were established as light-driven tools to manipulate neuronal activity. However, during long-term photostimulation using channelrhodopsin (ChR), desensitization can reduce effects. Furthermore, requirement for continuous presence of the chromophore all-trans retinal (ATR) in model systems lacking sufficient endogenous concentrations limits its applicability. We tested known, and engineered and characterized new variants of de- and hyperpolarizing rhodopsins in Caenorhabditis elegans. ChR2 variants combined previously described point mutations that may synergize to enable prolonged stimulation. Following brief light pulses ChR2(C128S;H134R) induced muscle activation for minutes or even for hours (‘Quint’: ChR2(C128S;L132C;H134R;D156A;T159C)), thus featuring longer open state lifetime than previously described variants. Furthermore, stability after ATR removal was increased compared to the step-function opsin ChR2(C128S). The double mutants C128S;H134R and H134R;D156C enabled increased effects during repetitive stimulation. We also tested new hyperpolarizers (ACR1, ACR2, ACR1(C102A), ZipACR). Particularly ACR1 and ACR2 showed strong effects in behavioral assays and very large currents with fast kinetics. In sum, we introduce highly light-sensitive optogenetic tools, bypassing previous shortcomings, and thus constituting new tools that feature high effectiveness and fast kinetics, allowing better repetitive stimulation or investigating prolonged neuronal activity states in C. elegans and, possibly, other systems.
ACS Algorithms for Complex Shapes with Certified Numerics and Topology Extension of geometric filtering techniques to higher-degree parametric curves

We present a subdivision algorithm for computing the intersection of spline curves. The complexity depends on geometric quantities that represent the hardness of the computation in a natural way, like the angle of the intersection. The main idea is the application of the super-composition technique, which considers unions of adjacent parameter intervals that are not siblings in the subdivision tree. This approach addresses the common difficulty of non-termination of the classical subdivision approach when the intersection coincides with a subdivision point, but it avoids the numerical overhead associated to alternative methods like a random shift of the parameter.
Augmentable Gamma Belief Networks

To infer multilayer deep representations of high-dimensional discrete and nonnegative real vectors, we propose an augmentable gamma belief network (GBN) that factorizes each of its hidden layers into the product of a sparse connection weight matrix and the nonnegative real hidden units of the next layer. The GBN's hidden layers are jointly trained with an upward-downward Gibbs sampler that solves each layer with the same subroutine. The gamma-negative binomial process combined with a layer-wise training strategy allows inferring the width of each layer given a fixed budget on the width of the first layer. Example results illustrate interesting relationships between the width of the first layer and the inferred network structure, and demonstrate that the GBN can add more layers to improve its performance in both unsupervisedly extracting features and predicting heldout data. For exploratory data analysis, we extract trees and subnetworks from the learned deep network to visualize how the very specific factors discovered at the first hidden layer and the increasingly more general factors discovered at deeper hidden layers are related to each other, and we generate synthetic data by propagating random variables through the deep network from the top hidden layer back to the bottom data layer.
The relationship between serum lipid parameters and renal frame count in hypertensive patients with normal renal functions.

OBJECTIVE Atherosclerosis can contribute to renovascular disease, and high cholesterol level is an independent risk factor for disease progression. Renal frame count (RFC) is an objective angiographic method of measuring macrovascular blood flow in the main renal artery and its segmental branches. The aim of the present study was to demonstrate relationship between serum lipid parameters and RFC. METHODS In this cross-sectional study, 116 hypertensive patients were allocated into 2 groups according to serum low-density lipoprotein (LDL) levels. Group 1 comprised 60 patients with LDL <130 mg/dL and Group 2 consisted of 56 individuals with LDL ≥130 mg/dL. The patients were also divided into 2 groups according to total cholesterol (TC) levels (52 patients in group with TC <200 mg/dL and 64 patients in group with TC ≥200 mg/dL). RESULTS Group 2 had higher mean RFC than Group 1 (p<0.001). RFC of both kidneys in Group 2 was significantly higher than results in Group 1 (p<0.001 and p=0.023, respectively). We found similar significant results in comparison of TC-based patient groups. RFC had positive correlation with smoking, TC, and LDL (r=0.326, p=0.035; r=0.393, p=0.010; and r=0.386, p=0.012, respectively). In multivariate linear regression analysis, LDL, TC, smoking, and creatinine clearance were independent predictors of RFC. CONCLUSION In conclusion, in hypertensive patients with normal renal function, LDL, TC, and smoking may be predictors of RFC and aggressive risk factor modification may help to reduce the risk of renal failure.
Evaluation of the Compressive Yield Strength of Hollow Glass Microsphere – Epoxy Composites as a Function of the Microsphere/ Epoxy Interface Strength

The compressive yield strength of glass microsphere – epoxy composites was evaluated as a function of the interface strength. The behaviour of composites with microspheres without any surface treatment was compared with that of composites fabricated with silane-treated and silicone oil-treated microspheres. Varying the hardener-to-epoxy ratio of the matrix also modified the interface. The results were compared with those derived from theoretical models, and it was shown that for hollow glass microsphere composites the effect of surface treatment can be quantitatively described using extant models. Changes in the reinforcing effect and stress concentration factor caused by the presence of the microspheres are discussed, and the experimental results explained.
Joint Hybrid Precoder and Combiner Design for mmWave Spatial Multiplexing Transmission

Millimeter-wave (mmWave) communications have been considered as a key technology for future 5G wireless networks because of the orders-of-magnitude wider bandwidth than current cellular bands. In this paper, we consider the problem of codebook-based joint analog-digital hybrid precoder and combiner design for spatial multiplexing transmission in a mmWave multiple-input multiple-output (MIMO) system. We propose to jointly select analog precoder and combiner pair for each data stream successively aiming at maximizing the channel gain while suppressing the interference between different data streams. After all analog precoder/combiner pairs have been determined, we can obtain the effective baseband channel. Then, the digital precoder and combiner are computed based on the obtained effective baseband channel to further mitigate the interference and maximize the sum-rate. Simulation results demonstrate that our proposed algorithm exhibits prominent advantages in combating interference between different data streams and offer satisfactory performance improvement compared to the existing codebook-based hybrid beamforming schemes.
Assortative mating and differential fertility by phenotype and genotype across the 20th century

Significance We describe dynamics in assortative mating and fertility patterns by polygenic scores associated with anthropometric traits, depression, and educational attainment across birth cohorts from 1920 to 1955. We find that, for example, increases in assortative mating at the phenotypic level for education are not matched at the genotypic level. We also show that genes related to height are positively associated with fertility and that, despite a widening gap between the more and less educated with respect to fertility, there is no evidence that this trend is associated with genes. These findings are important to our understanding of the roots of shifting distributions of health and behavior across generations in US society. This study asks two related questions about the shifting landscape of marriage and reproduction in US society over the course of the last century with respect to a range of health and behavioral phenotypes and their associated genetic architecture: (i) Has assortment on measured genetic factors influencing reproductive and social fitness traits changed over the course of the 20th century? (ii) Has the genetic covariance between fitness (as measured by total fertility) and other traits changed over time? The answers to these questions inform our understanding of how the genetic landscape of American society has changed over the past century and have implications for population trends. We show that husbands and wives carry similar loadings for genetic factors related to education and height. However, the magnitude of this similarity is modest and has been fairly consistent over the course of the 20th century. This consistency is particularly notable in the case of education, for which phenotypic similarity among spouses has increased in recent years. Likewise, changing patterns of the number of children ever born by phenotype are not matched by shifts in genotype–fertility relationships over time. Taken together, these trends provide no evidence that social sorting is becoming increasingly genetic in nature or that dysgenic dynamics have accelerated.
Combining statistical techniques to predict postsurgical risk of 1-year mortality for patients with colon cancer

Introduction Colorectal cancer is one of the most frequently diagnosed malignancies and a common cause of cancer-related mortality. The aim of this study was to develop and validate a clinical predictive model for 1-year mortality among patients with colon cancer who survive for at least 30 days after surgery. Methods Patients diagnosed with colon cancer who had surgery for the first time and who survived 30 days after the surgery were selected prospectively. The outcome was mortality within 1 year. Random forest, genetic algorithms and classification and regression trees were combined in order to identify the variables and partition points that optimally classify patients by risk of mortality. The resulting decision tree was categorized into four risk categories. Split-sample and bootstrap validation were performed. ClinicalTrials.gov Identifier: NCT02488161. Results A total of 1945 patients were enrolled in the study. The variables identified as the main predictors of 1-year mortality were presence of residual tumor, American Society of Anesthesiologists Physical Status Classification System risk score, pathologic tumor staging, Charlson Comorbidity Index, intraoperative complications, adjuvant chemotherapy and recurrence of tumor. The model was internally validated; area under the receiver operating characteristic curve (AUC) was 0.896 in the derivation sample and 0.835 in the validation sample. Risk categorization leads to AUC values of 0.875 and 0.832 in the derivation and validation samples, respectively. Optimal cut-off point of estimated risk had a sensitivity of 0.889 and a specificity of 0.758. Conclusion The decision tree was a simple, interpretable, valid and accurate prediction rule of 1-year mortality among colon cancer patients who survived for at least 30 days after surgery.
Isolation and Characterization of a Novel Endoglucanase from a Bursaphelenchus xylophilus Metagenomic Library

A novel gene (designated as cen219) encoding endoglucanase was isolated from a Bursaphelenchus xylophilus metagenomic library by functional screening. Sequence analysis revealed that cen219 encoded a protein of 367 amino acids. SDS-PAGE analysis of purified endoglucanase suggested that Cen219 was a monomeric enzyme with a molecular mass of 40 kDa. The optimum temperature and pH for endoglucanase activity of Cen219 was separately 50°C and 6.0. It was stable from 30 to 50°C, and from pH 4.0 to 7.0. The activity was significantly enhanced by Mn2+ and dramatically reduced by detergent SDS and metals Fe3+, Cu2+ or Hg2+. The enzyme hydrolyzed a wide range of β-1, 3-, and β-1, 4-linked polysaccharides, with varying activities. Activities towards microcrystalline cellulose and filter paper were relatively high, while the highest activity was towards oat gum. The Km and Vmax of Cen219 towards CMC was 17.37 mg/ml and 333.33 U/mg, respectively. The findings have an insight into understanding the molecular basis of host–parasite interactions in B. xylophilus species. The properties also make Cen219 an interesting enzyme for biotechnological application.
Towards General Evaluation of Intelligent Systems: Lessons Learned from Reproducing AIQ Test Results

Abstract This paper attempts to replicate the results of evaluating several artificial agents using the Algorithmic Intelligence Quotient test originally reported by Legg and Veness. Three experiments were conducted: One using default settings, one in which the action space was varied and one in which the observation space was varied. While the performance of freq, Q0, Qλ, and HLQλ corresponded well with the original results, the resulting values differed, when using MC-AIXI. Varying the observation space seems to have no qualitative impact on the results as reported, while (contrary to the original results) varying the action space seems to have some impact. An analysis of the impact of modifying parameters of MC-AIXI on its performance in the default settings was carried out with the help of data mining techniques used to identifying highly performing configurations. Overall, the Algorithmic Intelligence Quotient test seems to be reliable, however as a general artificial intelligence evaluation method it has several limits. The test is dependent on the chosen reference machine and also sensitive to changes to its settings. It brings out some differences among agents, however, since they are limited in size, the test setting may not yet be sufficiently complex. A demanding parameter sweep is needed to thoroughly evaluate configurable agents that, together with the test format, further highlights computational requirements of an agent. These and other issues are discussed in the paper along with proposals suggesting how to alleviate them. An implementation of some of the proposals is also demonstrated.
Assessing the Effect of Early Visual Cortex Transcranial Magnetic Stimulation on Working Memory Consolidation

Maintaining visual working memory (VWM) representations recruits a network of brain regions, including the frontal, posterior parietal, and occipital cortices; however, it is unclear to what extent the occipital cortex is engaged in VWM after sensory encoding is completed. Noninvasive brain stimulation data show that stimulation of this region can affect working memory (WM) during the early consolidation time period, but it remains unclear whether it does so by influencing the number of items that are stored or their precision. In this study, we investigated whether single-pulse transcranial magnetic stimulation (spTMS) to the occipital cortex during VWM consolidation affects the quantity or quality of VWM representations. In three experiments, we disrupted VWM consolidation with either a visual mask or spTMS to retinotopic early visual cortex. We found robust masking effects on the quantity of VWM representations up to 200 msec poststimulus offset and smaller, more variable effects on WM quality. Similarly, spTMS decreased the quantity of VWM representations, but only when it was applied immediately following stimulus offset. Like visual masks, spTMS also produced small and variable effects on WM precision. The disruptive effects of both masks and TMS were greatly reduced or entirely absent within 200 msec of stimulus offset. However, there was a reduction in swap rate across all time intervals, which may indicate a sustained role of the early visual cortex in maintaining spatial information.
Transgenerational Transmission of the Glossina pallidipes Hytrosavirus Depends on the Presence of a Functional Symbiome

The vertically transmitted endosymbionts (Sodalis glossinidius and Wigglesworthia glossinidia) of the tsetse fly (Diptera: Glossinidae) are known to supplement dietary deficiencies and modulate the reproductive fitness and the defense system of the fly. Some tsetse fly species are also infected with the bacterium, Wolbachia and with the Glossina hytrosavirus (GpSGHV). Laboratory-bred G. pallidipes exhibit chronic asymptomatic and acute symptomatic GpSGHV infection, with the former being the most common in these colonies. However, under as yet undefined conditions, the asymptomatic state can convert to the symptomatic state, leading to detectable salivary gland hypertrophy (SGH+) syndrome. In this study, we investigated the interplay between the bacterial symbiome and GpSGHV during development of G. pallidipes by knocking down the symbionts with antibiotic. Intrahaemocoelic injection of GpSGHV led to high virus titre (109 virus copies), but was not accompanied by either the onset of detectable SGH+, or release of detectable virus particles into the blood meals during feeding events. When the F1 generations of GpSGHV-challenged mothers were dissected within 24 h post-eclosion, SGH+ was observed to increase from 4.5% in the first larviposition cycle to >95% in the fourth cycle. Despite being sterile, these F1 SGH+ progeny mated readily. Removal of the tsetse symbiome, however, suppressed transgenerational transfer of the virus via milk secretions and blocked the ability of GpSGHV to infect salivary glands of the F1 progeny. Whereas GpSGHV infects and replicates in salivary glands of developing pupa, the virus is unable to induce SGH+ within fully differentiated adult salivary glands. The F1 SGH+ adults are responsible for the GpSGHV-induced colony collapse in tsetse factories. Our data suggest that GpSGHV has co-evolved with the tsetse symbiome and that the symbionts play key roles in the virus transmission from mother to progeny.
Predicting Outcome after Traumatic Brain Injury: Development and International Validation of Prognostic Scores Based on Admission Characteristics

Background Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable prediction of outcome on admission is of great clinical relevance. We aimed to develop prognostic models with readily available traditional and novel predictors. Methods and Findings Prospectively collected individual patient data were analyzed from 11 studies. We considered predictors available at admission in logistic regression models to predict mortality and unfavorable outcome according to the Glasgow Outcome Scale at 6 mo after injury. Prognostic models were developed in 8,509 patients with severe or moderate TBI, with cross-validation by omission of each of the 11 studies in turn. External validation was on 6,681 patients from the recent Medical Research Council Corticosteroid Randomisation after Significant Head Injury (MRC CRASH) trial. We found that the strongest predictors of outcome were age, motor score, pupillary reactivity, and CT characteristics, including the presence of traumatic subarachnoid hemorrhage. A prognostic model that combined age, motor score, and pupillary reactivity had an area under the receiver operating characteristic curve (AUC) between 0.66 and 0.84 at cross-validation. This performance could be improved (AUC increased by approximately 0.05) by considering CT characteristics, secondary insults (hypotension and hypoxia), and laboratory parameters (glucose and hemoglobin). External validation confirmed that the discriminative ability of the model was adequate (AUC 0.80). Outcomes were systematically worse than predicted, but less so in 1,588 patients who were from high-income countries in the CRASH trial. Conclusions Prognostic models using baseline characteristics provide adequate discrimination between patients with good and poor 6 mo outcomes after TBI, especially if CT and laboratory findings are considered in addition to traditional predictors. The model predictions may support clinical practice and research, including the design and analysis of randomized controlled trials.
Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study.

OBJECTIVE Explore the automated acquisition of knowledge in biomedical and clinical documents using text mining and statistical techniques to identify disease-drug associations. DESIGN Biomedical literature and clinical narratives from the patient record were mined to gather knowledge about disease-drug associations. Two NLP systems, BioMedLEE and MedLEE, were applied to Medline articles and discharge summaries, respectively. Disease and drug entities were identified using the NLP systems in addition to MeSH annotations for the Medline articles. Focusing on eight diseases, co-occurrence statistics were applied to compute and evaluate the strength of association between each disease and relevant drugs. RESULTS Ranked lists of disease-drug pairs were generated and cutoffs calculated for identifying stronger associations among these pairs for further analysis. Differences and similarities between the text sources (i.e., biomedical literature and patient record) and annotations (i.e., MeSH and NLP-extracted UMLS concepts) with regards to disease-drug knowledge were observed. CONCLUSION This paper presents a method for acquiring disease-specific knowledge and a feasibility study of the method. The method is based on applying a combination of NLP and statistical techniques to both biomedical and clinical documents. The approach enabled extraction of knowledge about the drugs clinicians are using for patients with specific diseases based on the patient record, while it is also acquired knowledge of drugs frequently involved in controlled trials for those same diseases. In comparing the disease-drug associations, we found the results to be appropriate: the two text sources contained consistent as well as complementary knowledge, and manual review of the top five disease-drug associations by a medical expert supported their correctness across the diseases.