Miracle-dz/UniFAR-FTUs huggingface dataset:
Salvia Hypoleuca; Aew Source of Compounds which are Useful for Treatment of Ocular Inflammation

Summary The aim of the present study was to determine the effects of Salvia hypoleuca extract on endotoxin*induced uveitis (EIU) in rats. In addition, the endotoxin*induced expression of the inducible nitric oxide synthase (iNOS) and cyclooxygenase (COX)*2 proteins was determined in a mouse macrophage cell line (RAW 264.7 ) treated with Salvia hypoleuca extract in vitro, to clarify the anti*inflammatory properties. EIU was induced in male Wistar rats by a footpad injection of lipopolysaccharide (LPS). Immediately after the LPS injection, 1, 10, or 100 mg extract or 10 mg prednisolone was injected intravenously. After 24 hours, the aqueous humor was collected from both eyes, and the number of infiltrating cells, protein concentration, nitric oxide (NO), prostaglandin (PG)*E2, and TNF levels in the aqueous humor were determined. RAW 264.7 cells treated with various concentrations of extract were incubated with 10 µg/mL LPS for 24 hours. Levels of NO, PGE2, and TNF were determined. The expression of iNOS and COX*2 proteins was analyzed by Western blot analysis. The number of inflammatory cells, the protein concentrations, and the levels of NO, PGE2, and TNF in the aqueous humor in the groups treated with Salvia hypoleuca were significantly decreased in a dose*dependent manner. In addition, the anti inflammatory effect of 100 mg Salvia hypoleuca was as strong as that of 10 mg prednisolone. The anti*inflammatory action of Salvia hypoleuca was stronger than that of either quercetin or anthocyanin administered alone. Extract also suppressed LPS*induced iNOS and COX*2 protein expressions in RAW 264.7 cells in vitro in a dosedependent manner. The results suggest that Salvia hypoleuca has a dose*dependent anti– ocular inflammatory effect that is due to the direct blocking of the expression of the iNOS and COX*2 enzymes and leads to the suppression of the production of NO, PGE2, and TNF .
Association of Ankle Brachial Index with Clinical Outcomes Following Percutaneous Coronary Intervention in Patients with Aortic Aneurysm

Objective Since patients with thoracic aortic aneurysm (TAA)/abdominal aortic aneurysm (AAA) are often complicated with coronary artery disease, it is common for those patients to undergo percutaneous coronary intervention (PCI). The ankle brachial index (ABI) is usually measured in patients with TAA/AAA to screen the presence of peripheral arterial disease. The present study investigated the association between the ABI and clinical outcomes following PCI in patients with TAA/AAA. Methods We divided 200 TAA/AAA patients who underwent PCI into a normal ABI group (n=137) and an abnormal ABI group (n=63) according to the ABI cut-off level of 1.00. The primary endpoint was one-year major adverse cardiovascular events (MACE), defined as the composite of cardiovascular death, non-fetal myocardial infarction, stroke, target vessel revascularization, and hospitalization for heart failure. Results Mean ABIs in the normal and abnormal ABI groups were 1.12±0.09 and 0.86±0.11, respectively (p<0.01). Kaplan-Meier curves showed MACE were more frequent in the abnormal ABI group than in the normal ABI group (p=0.01). A multivariate Cox hazard analysis revealed that an abnormal ABI was significantly associated with 1-year MACE (vs. ABI ≥1.0: HR 3.02, 95% confidence interval 1.00-9.08, p=0.049). Conclusion Among patients with TAA/AAA who underwent PCI, abnormal ABI was significantly associated with 1-year MACE, suggesting the utility of the ABI measurement in this high-risk population.
Phylogeny and abiotic conditions shape the diel floral emission patterns of desert Brassicaceae species.

A key facet of floral scent is diel fluctuations in emission, often studied in the context of plant-pollinator interactions, while contributions of environment and phylogeny remain overlooked. Here, we ask if these factors are involved in shaping temporal variations in scent emission. To that end, we coupled light/dark floral emission measurements of 17 desert Brassicaceae species with environmental and phylogenetic data to explore the individual/combined impacts of these predictors on diel emission patterns. We further investigated these patterns by conducting high-resolution emission measurements in a subset of genetically distant species with contrasting temporal dynamics. While diel shifts in magnitude and richness of emission were strongly affected by genetic relatedness, they also reflect the environmental conditions under which the species grow. Specifically, light/dark emission ratios were negatively affected by an increase in winter temperatures, known to impact both plant physiology and insect locomotion, and sandy soil fractions, previously shown to exert stress that tempers with diel metabolic rhythms. Additionally, the biosynthetic origins of the compounds were associated with their corresponding production patterns, possibly to maximize emission efficacy. Using a multidisciplinary chemical/ecological approach, we uncover and differentiate the main factors shaping floral scent diel fluctuations, highlighting their consequences under changing global climate. This article is protected by copyright. All rights reserved.
Expansion of the ophthalmic phenotype of SPINT2‐related syndromic congenital sodium diarrhea

A 5‐year‐old girl presented with treatment‐refractory dry eye and recurrent episodes of eye pain. She had been previously diagnosed with syndromic congenital sodium diarrhea (SCSD) caused by a pathogenic variant in SPINT2. Her local pediatric ophthalmologist had made the diagnosis of severe dry eye with corneal erosions, based on which, we arranged an eye exam under anesthesia (EUA) and punctal plug placement. Anterior segment optical coherence tomography (OCT) and corneal photographs were taken during the procedure. There are reports describing similar ophthalmic findings in this syndrome. However, to the best of our knowledge, this is the first case report to document OCT imaging and corneal photographs in a patient with SCSD, which we feel expands the ophthalmic phenotype of this rare genetic disorder.
Mechanistic insight on the inhibition of D, D-carboxypeptidase from Mycobacterium tuberculosis by β-lactam antibiotics: an ONIOM acylation study

Abstract Mycobacterium tuberculosis cell wall is intricate and impermeable to many agents. A D, D-carboxypeptidase (DacB1) is one of the enzymes involved in the biosynthesis of cell wall peptidoglycan and catalyzes the terminal D-alanine cleavage from pentapeptide precursors. Catalytic activity and mechanism by which DacB1 functions is poorly understood. Herein, we investigated the acylation mechanism of DacB1 by β-lactams using a 6-membered ring transition state model that involves a catalytic water molecule in the reaction pathway. The full transition states (TS) optimization plus frequency were achieved using the ONIOM (B3LYP/6-31 + G(d): AMBER) method. Subsequently, the activation free energies were computed via single-point calculations on fully optimized structures using B3LYP/6-311++(d,p): AMBER and M06-2X/6-311++(d,p): AMBER with an electronic embedding scheme. The 6-membered ring transition state is an effective model to examine the inactivation of DacB1 via acylation by β-lactams antibiotics (imipenem, meropenem, and faropenem) in the presence of the catalytic water. The ΔG# values obtained suggest that the nucleophilic attack on the carbonyl carbon is the rate-limiting step with 13.62, 19.60 and 30.29 kcal mol−1 for Imi–DacB1, Mero–DacB1 and Faro–DacB1, respectively. The electrostatic potential (ESP) and natural bond orbital (NBO) analysis provided significant electronic details of the electron-rich region and charge delocalization, respectively, based on the concerted 6-membered ring transition state. The stabilization energies of charge transfer within the catalytic reaction pathway concurred with the obtained activation free energies. The outcomes of this study provide important molecular insight into the inactivation of D, D-carboxypeptidase by β-lactams. Communicated by Ramaswamy H. Sarma
'Lost time'. Patients with early inflammatory/rheumatoid arthritis and their experiences of delays in Primary Care.

BACKGROUND Early referral forms a crucial part in early inflammatory/rheumatoid arthritis (EI/RA) recovery. Delayed decisions to refer can lead to severe incapacity and emotional distress for individuals and family and feelings of lost time. How patients with EI/RA experience early referral decisions in Primary Care is an under explored area and warrants further investigation. AIM To explore how patients newly diagnosed with EI/RA experienced their early contacts with Primary Care as they negotiated their journey through the referral process into secondary care. DESIGN AND SETTING Qualitative face-to-face interviews with newly diagnosed EI/RA patients. METHODS In-depth semi-structured interviews were conducted to explore patients' experiences of referral from first symptoms to General Practitioner referral. All participants were interviewed within 2 weeks of being diagnosed in Secondary Care. Data analysis was conducted using interpretative phenomenological analysis. FINDINGS All participants in this study described having experienced struggles with their navigation through Primary Care towards diagnosis and specialist EI/RA services. This struggle comprised five key elements: 'family persuasion', 'lack of continuity in care', 'pushing for referral', 'strained relations' and 'lost time'. CONCLUSION The delays experienced by patients when attempting to reach an early referral decision in Primary Care cause frustration for those presenting with EI/RA, partly because they do not feel heard. There is a significant impact on patients and their families when referral to specialist care is delayed.
Sinapic acid mitigates methotrexate‐induced hepatic injuries in rats through modulation of Nrf‐2/HO‐1 signaling

The present research has been investigated to study the protective outcomes of sinapic acid (SA) against methotrexate (MTX) encouraged liver damage in rats by modulating the Nrf2/HO‐1 and NF‐κB signaling pathways. The animals were arbitrarily allocated into four groups: group I rats administered a 0.5% carboxymethyl cellulose (CMC) vehicle orally for 15 consecutive days with a single intravenous standard saline injection (0.9% NaCl) on day seven. Groups II, III, and IV were injected intraperitoneally with 20 mg MTX/kg on 7th day. Animals in group III and IV were treated orally for 14 days with 20 mg of SA/kg dissolved daily in 0.5% CMC respectively. In all experimental groups, liver function, biochemical, histopathological and molecular changes were evaluated. MTX‐induced changes in liver function indices like ALT, AST, and ALP are substantially restored with SA pretreatment. Moreover, antioxidant defense mechanisms (GSH, SOD, and CAT) and oxidative/nitrostative stress (MDA and NO) and inflammatory cytokine (TNF‐α, IL‐β and MPO) were also substantially restored. Furthermore, the conclusions indicate that SA prevents the hepatic damage caused by MTX through apoptosis inhibition and stimulation of Nrf2/HO‐1‐medial antioxidant enzymes by NF‐κB inhibition. Histological findings have shown that SA therapy has greatly protected liver damage caused by MTX.
Bone Mineral Density Loss in Parkinson’s Disease: Impact of Clinical Subtypes

ABSTRACT Background: This study aimed to compare the BMD status among the clinical subtypes of PD and healthy controls. Methods: Sixty patients with PD and 30 healthy age- and sex-matched controls were included in this study. The patients were divided into postural instability gait difficulty-dominant type (PIGDDT) group and tremor-dominant type (TDT) group based on the Unified Parkinson’s Disease Rating Scale (UPDRS) score. BMD was measured using dual-energy X-ray absorptiometry scans in femoral and lumbar regions. Results: The T-scores in femoral and lumbar regions were similar in all groups. The prevalence of osteopenia was higher than the prevalence of osteoporosis in all three groups for femoral regions. The prevalence of osteoporosis in the intertrochanteric region and total femur in the PIGDDT group was higher than in the TDT group and controls. Our data showed a trend toward higher prevalence of osteoporosis in the PIGDDT group. Conclusion: The prevalence of osteopenia and osteoporosis may differ between clinical subtypes of PD and healthy controls. Osteopenia is more common than osteoporosis for all groups. The patients with PIGDDT of PD tended to have higher prevalence of osteoporosis, even at early stages of disease, compared to those with TDT and healthy controls.
The new classification method in ACEF score is more useful in patients with acute coronary syndrome without ST segment elevation.

Goal In this study, it was investigated whether the age, creatinine, and ejection fraction (ACEF) score [age (years) / ejection fraction (%) +1 (if creatinine >2 mg / dL)] could predict in-hospital mortality in patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) and its relationship with the Global Record of Acute Coronary Events (GRACE) risk score were investigated.Material and methods The study enrolled 658 NSTE-ACS patients from January 2016 to August 2020. The patients were divided into two groups according to the ACEF score with an optimum cut-off value of 1.283 who were divided into two groups according to the ACEF score: low ACEF (≤1.283, n:382) and high ACEF (>1.283, n: 276). The primary outcome of the study was in-hospital all-cause mortality. The primary outcome of the study was in-hospital all-cause mortality. Statistically accuracy was defined with area under the curve by receiver-operating characteristic curve analysis.Results In total, 13 (4.71 %) patients had in-hospital mortality. The ACEF score was significantly higher in the group with higher mortality than in the group with low mortality (2.1±0.53 vs. 1.34±0.56 p=0.001). The ACEF score was positively correlated with GRACE risk score (r=0.188 p<0.0001). In ROC curve analysis, the AUC of the ACEF score for predicting in-hospital mortality was 0.849 (95 % CI, 0.820 to 0.876; p<0.0001); sensitivity, 92.3 %; specificity, 59.2 %, and the optimum cut-off value was >1.283. Conclusion The ACEF score presented excellent discrimination in predicting in-hospital mortality. We obtained an easier and more useful result by dividing the ACEF score into two groups instead of three in NSTE-ACS patients. As a simple, useful, and easily applicable risk stratification in the evaluation of an emergency event such as the ACEF score, it can significantly contribute to the identification of patients at high risk.
Deep neural network-based detection and segmentation of intracranial aneurysms on 3D rotational DSA

Objective Accurate diagnosis and measurement of intracranial aneurysms are challenging. This study aimed to develop a 3D convolutional neural network (CNN) model to detect and segment intracranial aneurysms (IA) on 3D rotational DSA (3D-RA) images. Methods 3D-RA images were collected and annotated by 5 neuroradiologists. The annotated images were then divided into three datasets: training, validation, and test. A 3D Dense-UNet-like CNN (3D-Dense-UNet) segmentation algorithm was constructed and trained using the training dataset. Diagnostic performance to detect aneurysms and segmentation accuracy was assessed for the final model on the test dataset using the free-response receiver operating characteristic (FROC). Finally, the CNN-inferred maximum diameter was compared against expert measurements by Pearson’s correlation and Bland-Altman limits of agreement (LOA). Results A total of 451 patients with 3D-RA images were split into n = 347/41/63 training/validation/test datasets, respectively. For aneurysm detection, observed FROC analysis showed that the model managed to attain a sensitivity of 0.710 at 0.159 false positives (FP)/case, and 0.986 at 1.49 FP/case. The proposed method had good agreement with reference manual aneurysmal maximum diameter measurements (8.3 ± 4.3 mm vs. 7.8 ± 4.8 mm), with a correlation coefficient r = 0.77, small bias of 0.24 mm, and LOA of -6.2 to 5.71 mm. 37.0% and 77% of diameter measurements were within ±1 mm and ±2.5 mm of expert measurements. Conclusions A 3D-Dense-UNet model can detect and segment aneurysms with relatively high accuracy using 3D-RA images. The automatically measured maximum diameter has potential clinical application value.
Clay dispersion in relation to changes in the electrolyte composition of dialysed red-brown earths

Summary Dialysis and re-suspension of red-brown earths showed dispersion in distilled water independent of the adsorbed cations. Whenever the electrolyte concentration is below the critical coagulation concentration the soil and clay will disperse. Mechanical disturbance greatly enhances the dispersion process. The experiments suggest that the dispersion was influenced by the released salt in the suspensions. The changes with time in the electrolyte composition of dialysed soils and clays showed that the ‘homoionic’ systems are unstable with possible interference with clay dispersion by the generated electrolytes. The importance of free electrolytes, especially calcium, in the management of dispersive red-brown earths is indicated.
Dipolar response and hydrogen-bond kinetics in liquid water in square-wave time-varying electric fields

Non-equilibrium molecular dynamics simulations of liquid water have been performed at 298 K in the presence of external time-varying electric fields, approximating a square wave, of varying peak intensity (0.005–0.1 V/Å) in the microwave to far-infrared frequency range (20–500 GHz). Significant non-thermal field effects were noted in terms of dipolar response and acceleration of hydrogen-bond kinetics. The coupling between the total dipole moment and the external field has been investigated and autocorrelation functions (ACFs) of both the total dipole moment and the average of the individual molecular dipole moment along the laboratory axis of the applied fields exhibited coupling, with the former showing a stronger coupling and the latter showing coupling to lower magnitude fields. The maximum alignment achieved has been computed as a function of field intensities and frequencies: the lower frequencies show a greater maximum alignment as the system had more time within each field cycle to respond. The normalised probability distribution and the hydrogen-bond ACFs have been computed: the ACF showed a clear effect over shortening the hydrogen-bond relaxation time. The field effects over the molecules’ transitions from four to five hydrogen bonds have been computed. There was an enhancement of fewer molecules undergoing transitions and a dampening for a larger proportion of molecules, depending on the external fields’ periods.
Isometric Universal Graphs

A subgraph H of a graph G is isometric if the distances between vertices in H coincide with the distances between the corresponding vertices in G. We show that for any integer n > 1, there is a graph on 3 2 n) vertices that contains all n-vertex graphs as isometric subgraphs. Our main tool is a new type of distance labelling scheme, whose study might be of independent interest.
Thickness dependence of work function, ionization energy, and electron affinity of Mo and W dichalcogenides from DFT and GW calculations

Transition-metal dichalcogenides (TMDs) are promising for two-dimensional (2D) semiconducting devices and novel phenomena. For 2D applications, their work function, ionization energy, and electron affinity are required as a function of thickness, but research on this is yet to cover the full family of compounds. Here, we present the work function, ionization energy, and electron affinity of few-layer and bulk MX2 (M = Mo, W and X = S, Se, Te) in 2H phase obtained accurately by the density functional theory and GW calculations. For each compound, we consider one-, two-, three-, four-layer, and bulk geometry. In GW calculations, accurate results are obtained by nonuniform q sampling for two-dimensional geometry. From band energies including the GW self-energy correction, we estimate the work function, band gap, ionization energy, and electron affinity as functions of the number of layers. We compare our results with available theoretical and experimental reports, and we discuss types of band alignments in in-plane and out-of-plane junctions of these few-layer and bulk TMDs.
RoRD: Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching

The use of local detectors and descriptors in typical computer vision pipelines works well until variations in viewpoint and appearance change become extreme. Past research in this area has typically focused on one of two approaches to this challenge: the use of projections into spaces more suitable for feature matching under extreme viewpoint changes, and attempting to learn features that are inherently more robust to viewpoint change. In this paper, we present a novel framework that combines the learning of invariant descriptors through data augmentation and orthographic viewpoint projection. We propose rotation-robust local descriptors, learnt through training data augmentation based on rotation homographies, and a correspondence ensemble technique that combines vanilla feature correspondences with those obtained through rotation-robust features. Using a range of benchmark datasets as well as contributing a new bespoke dataset for this research domain, we evaluate the effectiveness of the proposed approach on key tasks including pose estimation and visual place recognition. Our system outperforms a range of baseline and state-of-the-art techniques, including enabling higher levels of place recognition precision across opposing place viewpoints, and achieves practically useful performance levels even under extreme viewpoint changes. We reduce pose estimation error by 86.72% relative to state of the art.
Meta-Solver for Neural Ordinary Differential Equations

A conventional approach to train neural ordinary differential equations (ODEs) is to fix an ODE solver and then learn the neural network's weights to optimize a target loss function. However, such an approach is tailored for a specific discretization method and its properties, which may not be optimal for the selected application and yield the overfitting to the given solver. In our paper, we investigate how the variability in solvers' space can improve neural ODEs performance. We consider a family of Runge-Kutta methods that are parameterized by no more than two scalar variables. Based on the solvers' properties, we propose an approach to decrease neural ODEs overfitting to the pre-defined solver, along with a criterion to evaluate such behaviour. Moreover, we show that the right choice of solver parameterization can significantly affect neural ODEs models in terms of robustness to adversarial attacks. Recently it was shown that neural ODEs demonstrate superiority over conventional CNNs in terms of robustness. Our work demonstrates that the model robustness can be further improved by optimizing solver choice for a given task. The source code to reproduce our experiments is available at https://github.com/juliagusak/neural-ode-metasolver.