Miracle-dz/UniFAR-FTUs huggingface dataset:
ANTIBACTERIAL ACTIONS OF WHOLE HERB TINCTURES

Two whole cell Escherichia coli luminescent biosensors were used to determine the antibacterial actions of 16 herbal tinctures. These bioassays can detect genotoxic (strain DPD2794) and general oxidative stress (DE135) events when challenged with antibacterial substances. Many of the herbal tinctures were active against these Gram-negative bacteria, affecting their metabolism without, in some cases, arresting cell growth or causing cell death. Antibacterial activity ranged from undetectable for Curcuma longa, Cinnamomum zeylanicum and Apium graveolens to highly effective against both E. coli strains in the case of Rosmarinus officinalis. Some of the results were unexpected. Althaea officinalis affected microbial metabolism in spite of the lack of literature precedent, and Cinnamomum zeylanicum did not appear to be antimicrobial, as claimed in some literature. It is concluded that studies using luminescent bacterial biosensors can provide important new insights into the potency and modes of the lethal and sub-lethal antibacterial action of whole herbs, and thereby provide crucial evidence for efficacy demanded by modern science and medicine. Copyright © 2007 John Wiley & Sons, Ltd.
MUTATION IN BRIEF Three Novel Receptor Gene in Northern Irish Patients With Familial Hypercholesterolemia tations in the EGF Precursor Domain of the Low-Densiw Lipoprotein

Familial hypercholesterolemia (FH) is a common autosomal dominant disorder of lipid metabolism characterised by tendinous xanthomas ( TX) and a twoto threefold elevation in serum lowdensity lipoprotein (LDL)-cholesterol. Of more clinical significance is the increased risk of premature coronary artery disease (CAD) conferred on patients. A report by the scientific steering committee of the Simon Broome Register Group (1991) assessed the increased risk in CAD mortality of a group of treated heterozygote FH patients aged 20-39 to be 100-fold that of the general population. Homozygous FH patients present with a more severe clinical picture, a sixto eightfold elevation in LDL-cholesterol levels, and they often die of CAD during the first two decades of life (Goldstein and Brown, 1989). The disorder is caused by dysfunctional low density lipoprotein receptor (LDLR), the gene of which has been localised to chromosome 19~13.1-13.3 (Lindgren et al., 1985). To date, 150 LDLR gene defects have been characterised, of which 44% are missense mutations (Hobbs et al., 1992). These are spread across the entire length of the gene, and no convincing “hotspots” have emerged. Therefore, mutational analysis in FH patients requires an total gene approach. In this report, we present three novel mutations in the epidermal growth factor (EGF)-precursor homology domain (exons 7-14) of the LDLR gene: K369X (exon 8), D461N (exon lo), and W462R (exon 10). These mutations were identified as part of a study to sequence the entire coding region in 30 heterozygous probands from unrelated FH families. MATERIALS AND METHODS Genomic DNA was extracted from the peripheral blood of 10 probands, all clinically assessed to have heterozygous FH. Each proband was negative for a Southern blotting screen for gross rearrangements using LDLR cDNA probes. DNA was amplified using primers specific for each of the 18 exons. The primers used were truncated versions, in each case the first 20 bases (renamed SP90”, SP91”, etc.), of those published by Leitersdorf et al. (1990), thus allowing the splice sites to be sequenced. The polymerase chain reaction (PCR) products produced were sequenced, in both directions, on an Applied Biosystems 373A DNA fluorescent sequencer using Taq. dye-terminator cycle sequencing chemistry, according to the manufacturer’s instructions. Three pmoles of the exon primers were used as sequencing primers.
0-0 XI % 0 Yeast Sequencing Reports o o o o The RH 04 a and NUDI Genes on Saccharomyces cerevisiae Chromosome XI

Sequence analysis of a 4 kb fragment from the right arm of Saccharomyces cerevisiae chromosome XI, in combination with Northern hybridization experiments revealed the presence of two genes, designated RH04a and N U D l . The first gene encodes a 32 kDa protein showing significant sequence similarity with members of the ras family. Its 3'-terminal sequence is virtually identical to a sequence published previously as the RHO4 gene [Matsui and Toh-e, Gene 114 (1992), 43-49], which, however, appears to start at an internal ATG codon. The RH04a sequence also overlaps the 5'-terminal sequence of the RNCl gene [Chow et al., Nucl. Acids Res. 20 (1992), 5215-52211 proposed to encode the yeast yNucR endo/exonuclease. The remainder of this RNCl gene overlaps with the 5'-end of the NUDl gene. However, the RNCI sequence lacks a portion of 276 bp that in our fragment is part of the intergenic region separating RH04a and N U D l . From these results we conclude that the proposed RNCl gene is the result of a cloning artefact and that the yNucR protein is instead encoded by the NUDI gene.
The limited role of large-scale environment compared with optical AGN in nearby isolated elliptical galaxies

The formation and evolution of elliptical galaxies in low-density environments is less clear compared to classical elliptical galaxies in high-density environments. Isolated galaxies are defined as galaxies without massive neighbors within scales of galaxy groups. The impact of environment at several Mpc scales on the their properties has been barely explored. Here we study the role of large-scale environment in 573 isolated elliptical galaxies out to z=0.08. The aim is to explore whether the large-scale environment affects some of their physical properties. We use three environmental estimators of the large-scale structure within a projected radius of 5 Mpc around isolated galaxies: the tidal strength parameter, the projected density eta_k, and the distance to the fifth nearest neighbor galaxy. We find that 80% of galaxies at lower densities correspond to 'red and dead' elliptical galaxies. Blue and red galaxies do not tend to be located in different environments according to eta_k. Almost all the isolated ellipticals in the densest large-scale environments are red and/or quenched, where a third of them are low-mass galaxies. We have identified 33 blue, star-forming isolated ellipticals, which are in low density environments. A half of them are star-forming nuclei, whereas 92% of the isolated ellipticals with emission lines corresponds to AGN or composite objects. The large-scale environment is not playing the main role to determine the color and sSFR of isolated elliptical galaxies. The large-scale environment seems to be negligible from a stellar mass scale around 10^10.6 Msun, probably due to the dominant presence of AGN at larger masses. For lower masses, the processes of cooling and infall of gas from large scales are very inefficient in ellipticals. AGN might be also an important ingredient to keep most of the low-mass isolated elliptical galaxies quenched.
Application of conditional random fields and sparse polynomial chaos expansions in structural reliability analysis

Random field theory is often used to describe spatial variability in engineering applications. Using discretization algorithms, realizations of random fields are generated, which may be used subsequently in e.g. structural reliability analysis. Furthermore, sparse polynomial chaos expansions can reduce the total computational costs and allow for an efficient estimation of failure probabilities. The proposed approach is illustrated on a geotechnical engineering problem.
ADENOSINE DEAMINASE IN PLASMA OF PATIENTS CORRELATION BETWEEN ENZYME ACTIVITY A N D THE ATL SUBTYPES WITH ADULT T-CELL LEUKEMIA (ATL)

SUMMARY Adenosine deaminase (ADA) was assayed in plasma from 14 patients with adult T-cell leukemia (ATL) (eight with acute ATL and six with smoldering or chronic ATL), 20 male family members (ten were anti-ATLA antibody positive and the other ten negative), and 25 normal individuals. ADA activity was uniformly higher in plasma from patients with ATL than normal controls. This enzyme activity significantly increased in acute ATL in comparison to smoldering or chronic ATL. In families of ATL patients, no statistical difference in ADA activity between the anti-ATLA antibody-positive group and -negative group could be discerned. The enzyme activity in a patient with acute ATL, after a bone-marrow transplant, rapidly increased as leukemic cells increased in peripheral blood. These findings indicate that the levels of ADA activities in plasma from ATL patients reflect the condition of this disease. Thus, measurement of this enzyme activity offers a further parameter to distinguish subtypes of ATL, and is of prognostic and therapeutic value.
Design of a Bandwidth-Enhanced Planar Printed Antenna with Two Dipoles

This paper presents a broadband planar printed antenna comprising two dipoles with different lengths and a transition structure of microstrip (MS) to coplanar stripline (CPS). These two dipoles are serially connected through CPS. By adding trapezoid and stepped patches, the dipole elements are modified for enhancing the impedance matching of the antenna. In addition, a tapered transition is adopted in the CPS to achieve improved impedance matching. The current work shows a good agreement between measured and simulated results. The measured bandwidth is from 2.43 to 8.04 GHz for VSWR ≤ 2, corresponding to 107.2% fractional bandwidth. Measured peak gain ≥ 4.0 dBi is obtained in the whole operating band.
THE USAGE OF STATISTICAL FEATURES IN THE APPROXIMATION COMPONENTS OF WAVELET DECOMPOSITION FOR ECG CLASSIFICATION: A CASE STUDY FOR STANDING, WALKING AND SINGLE JUMP CONDITIONS

The purpose of this study is to classify electrocardiogram (ECG) signals with a high accuracy rate. The ECG signals used are obtained from the Physiobank archive. These signals are preprocessed to remove noise. Features with distinctiveness in classification are obtained both in the time domain and the frequency domain. The Discrete Wavelet Transform method is used for feature extraction in frequency domain. ECG signals are classified by the Naive Bayes method after the required features are extracted.
3D reconstructions from spectral light fields

The parametrization of light rays in form of light fields (LF) have become the standard and probably the most common way for the representation, analysis and processing of rays emitted from 3D objects or from 3D displays. Essentially, the LFs are 4D maps representing the spatial and angular distribution of the intensity of the rays. Nowadays, with the increasing availability of spectral imagers, the conventional LF can be augmented with the spectral information, yielding to what we call spectral light fields (SLFs). Spectral light fields refer to a 5D distribution of spatial, angular and spectral ray’s distribution. Thus, the SLF can be viewed as spectral radiance over a 2D manifold, or as 5D parameterization of a plenoptic function. In this paper we show the utility of the SLFs for digital 3D reconstruction. We show that the additional spectral domain provides important information that can be utilized to overcome 3D reconstruction artefacts caused by ambiguities in commonly captured LFs. We demonstrate the utilization of the SLFs for profilomety and refocusing.
Hundred Years of Einstein's Cosmological Constant

It was little over a hundred years ago that Einstein introduced the ‘cosmological constant’ in his General Theory of Relativity in order to obtain a static universe, to conform to the philosophical view of the universe at that time. What Einstein subsequently dubbed as the ‘biggest blunder’ of his life (after Hubble’s discovery of the expanding universe) has come back in vogue in cosmology. Here we look at the evolution of the concept of the cosmological constant from its inception to it possibly making up close to about 70% of the energy density of the universe.
Nonparametric estimation of mean residual quantile function under right censoring

ABSTRACT In this paper, we develop non-parametric estimation of the mean residual quantile function based on right-censored data. Two non-parametric estimators, one based on the empirical quantile function and the other using the kernel smoothing method, are proposed. Asymptotic properties of the estimators are discussed. Monte Carlo simulation studies are conducted to compare the two estimators. The method is illustrated with the aid of two real data sets.
A N EXPERIMENTAL ASSESSMENT O F MACROSCOPIC STRATION

MACROSCOPIC enzyme methods are widely used for the delineation and detection of myocardial infarction at autopsy. Although these methods will clearly delineate an established infarct their ability to detect infarcts which have occurred shortly before death is questionable. In this study we investigated five of these methods and with none was it possible to detect an experimental infarct that had been produced less than 5 hr before death. The nitro-blue tetrazolium test (dehydrogenase with substrate) performed better than specific substrate methods (Lactic, succinic and malic dehydrogenase) but was inferior to a method which uses the enzyme creatine phosphokinase. We conclude that these methods are of limited value to the forensic pathologist wishing to document or exclude myocardial infarction in cases of sudden unexpected death. In patients dying with acute myocardial infarction it is usually accepted that a minimal time interval of between 12 and 18 hr must elapse from the onset of chest pain to death if the pathologist is to recognise with certainty macroscopic evidence of myocardial necrosis. Simple macroscopic techniques allowing the demolistration of myocardial necrosis of shorter duration would be of practical use in the autopsy room. The techniques usually adopted depend on the reduction or loss of enzyme activity in the necrotic area (Nachlas and Shnitka, 1963) although other criteria such as alteration of Ph, binding of fluorescent dyes and alteration of Na/K ratios, have been tried (Zugibe et al., 1966; Camps, 1969; Rammer and Jansson, 1976). Exact assessment of the efficiency of these techniques is limited in man by the inevitable uncertainty about the exact time at which muscle necrosis began; this may not coincide with the onset of pain. The experimental animal is ideally suited to test the techniques since myocardial necrosis can be taken to begin within 15 min. of ligation of a major coronary artery.
Fight or Flight: Emergency Healthcare Workers Willingness to Work during Crises and Disasters: A cross-sectional multicentre study in the Netherlands

Objective: Expanding staff levels is a strategy for hospitals to increase surge capacity. This study aimed to evaluate whether emergency healthcare workers (HCWs) are willing to work (WTW) during a crises or disaster and which working conditions would influence their decision. Methods: HCWs of emergency departments (ED) and intensive care units (ICU) of five Dutch hospitals were surveyed about elevens disaster scenarios. For each scenario, HCWs were asked about their WTW and which conditions would influence their decision. Knowledge and perceived risk and danger was assessed per scenario. Results: 306/630 HCWs completed the survey. An influenza epidemic, SARS-CoV-2 pandemic and natural disaster were associated with highest WTW rates (69.0%, 63.7% and 53.3% respectively). WTW was lowest in nuclear incident (4.6%) and dirty bomb (3.3%) scenarios. WTW was higher in physicians than in nurses. Male ED HCWS, single HCWs and childless HCWs were more often WTW. Personal protective equipment (PPE) and safety of HCWs family were the most important working conditions. Perceived knowledge scored lowest in dirty bomb, biological and nuclear incident scenarios. These scenarios rated highest with regards to perceived danger. Conclusions: WTW depended on disaster type, profession and working department. Provision of PPE and safety of HCWs family were found to be predominant working conditions.
Integrating polarization conversion and nearly perfect absorption with multifunctional metasurfaces

Manipulating electromagnetic waves with artificial nanostructures has garnered great interest for their properties and potential applications. However, existing devices performing various desired operations at different wavelengths usually require cascading with different geometry patterns, which does not offer satisfactory simplicity. Here, we theoretically and experimentally demonstrate that an ultrathin, multifunctional metasurface, consisting of an array of nanorods, can perform various functions at different wavelengths. Simulated and experimental results indicate that nearly perfect absorption, linear-to-circular conversion, and linear cross-polarization conversion can be integrated into one multifunctional metasurface. Furthermore, the multifunctional metasurface can maintain very high performance across a large range of incident angles. The proposed configuration is extremely compact and easy to fabricate; these qualities should support the development of practical applications.
LigaNET: A multi-modal deep learning approach to predict the risk of subsequent anterior cruciate ligament injury after surgery

Anterior cruciate ligament (ACL) injuries are a common cause of soft tissue injuries in young active individuals, leading to a significant risk of premature joint degeneration. Postoperative management of such injuries, in particular returning patients to athletic activities, is a challenge with immediate and long-term implications including the risk of subsequent injury. In this study, we present LigaNET, a multi-modal deep learning pipeline that predicts the risk of subsequent ACL injury following surgical treatment. Postoperative MRIs (n=1,762) obtained longitudinally between 3 to 24 months after ACL surgery from a cohort of 159 patients along with 11 non-imaging outcomes were used to train and test: 1) a 3D CNN to predict subsequent ACL injury from segmented ACLs, 2) a 3D CNN to predict injury from the whole MRI, 3) a logistic regression classifier predict injury from non-imaging data, and 4) a multi-modal pipeline by fusing the predictions of each classifier. The CNN using the segmented ACL achieved an accuracy of 77.6% and AUROC of 0.84, which was significantly better than the CNN using the whole knee MRI (accuracy: 66.6%, AUROC: 0.70; P<.001) and the non-imaging classifier (accuracy: 70.1%, AUROC: 0.75; P=.039). The fusion of all three classifiers resulted in highest classification performance (accuracy: 80.6%, AUROC: 0.89), which was significantly better than each individual classifier (P<.001). The developed multi-modal approach had similar performance in predicting the risk of subsequent ACL injury from any of the imaging sequences (P>.10). Our results demonstrate that a deep learning approach can achieve high performance in identifying patients at high risk of subsequent ACL injury after surgery and may be used in clinical decision making to improve postoperative management (e.g., safe return to sports) of ACL injured patients.
Calibrated prediction intervals for polygenic scores across diverse contexts

Polygenic scores (PGS) have emerged as the tool of choice for genomic prediction in a wide range of fields from agriculture to personalized medicine. We analyze data from two large biobanks in the US (All of Us) and the UK (UK Biobank) to find widespread variability in PGS performance across contexts. Many contexts, including age, sex, and income, impact PGS accuracies with similar magnitudes as genetic ancestry. PGSs trained in single versus multi-ancestry cohorts show similar context-specificity in their accuracies. We introduce trait prediction intervals that are allowed to vary across contexts as a principled approach to account for context-specific PGS accuracy in genomic prediction. We model the impact of all contexts in a joint framework to enable PGS-based trait predictions that are well-calibrated (contain the trait value with 90% probability in all contexts), whereas methods that ignore context are mis-calibrated. We show that prediction intervals need to be adjusted for all considered traits ranging from 10% for diastolic blood pressure to 80% for waist circumference. Adjustment of prediction intervals depends on the dataset; for example, prediction intervals for education years need to be adjusted by 90% in All of Us versus 8% in UK Biobank. Our results provide a path forward towards utilization of PGS as a prediction tool across all individuals regardless of their contexts while highlighting the importance of comprehensive profile of context information in study design and data collection.
Heart Rate as a Predictor of Mortality in Heart Failure Patients at the Time of Discharge from the Intensive Care Unit

Objective: Heart rate serves as a critical prognostic factor in heart failure patients. We hypothesize that elevated heart rate in critically ill heart failure patients upon discharge from the intensive care unit (ICU) could be linked to adverse outcomes. Design: We implemented a retrospective cohort study using data collected between 2008 and 2019 from the Medical Information Mart for Intensive Care IV (MIMIC-IV version 2.0) database. We examined the association between the last heart rate prior to ICU discharge and in-hospital mortality, total mortality, and ICU readmission. Setting: ICU at Beth Israel Deaconess Medical Center Patients: Adult patients admitted to the ICU diagnosed with heart failure. Interventions: None Measurements and Main Results: From the 76,943 ICU stays, we enrolled 2,365 patients in this study. We observed correlations between in-hospital mortality and ICU discharge heart rate of 83.56{+/-}15.81 bpm (survivors) vs. 93.84{+/-}17.28 bpm (nonsurvivors, p<0.001). Total mortality showed similar trends, with 83.67{+/-}15.36 bpm (survivors) vs. 85.23{+/-}17.25 bpm (nonsurvivors, p=0.027), as did ICU readmissions at 83.55{+/-}15.77 bpm (nonreadmitted) vs. 88.64{+/-}17.49 bpm (readmitted, p<0.001). Given multivariate analysis, the ICU discharge heart rate strongly predicted in-hospital mortality (OR 1.035 [95% CI 1.024-1.046], p < 0.001), total mortality (OR 1.007 [95% CI 1.001-1.014], p = 0.027) and ICU readmission (OR 1.015 [95% CI 1.007-1.023], p < 0.001). Patients with an ICU discharge heart rate >90 bpm demonstrated significantly higher in-hospital mortality (OR 2.986 [95% CI 2.066-4.315], p < 0.001), total mortality (OR 1.341 [95% CI 1.083-1.661], p = 0.007), and ICU readmission rates (OR 1.638 [95% CI 1.270-2.114], p < 0.001). Conclusions: The findings suggest that heart failure patients with an elevated heart rate (>90 bpm) at ICU discharge are more likely to experience increased in-hospital mortality, total mortality, and ICU readmissions, indicating potential negative outcomes.