Miracle-dz/UniFAR-FTUs huggingface dataset:
Subtle Immunoreactivity Differences in the Fractal Patterns of Membrane E-Cadherin in Gastric Adenocarcinoma

Gastric cancer continues to be a significant malignancy worldwide, accounting for approximately one million new cases in 2020. Scientists are focusing on the cancerous cells' plasma membrane (PM) as a potential therapeutic target in cancer because it functions as the cell's interface with its environment through a variety of mechanisms. The capacity of membrane shape and its structures to influence biological processes frequently occurs through the regulation of enzymes or preferential protein binding to membranes via membrane shape changes. We aimed here to assess the morphological irregularities of the cellular membranes in gastric adenocarcinoma tumors, and to find any putative differences from normal gastric mucosae epithelial cells. We analyzed the pattern of E-cadherin at the level of the cell membrane using the fractal dimension (FD) analysis on fluorescence immunohistochemistry samples labeled with E-cadherin in gastric well/moderate and solid gastric adenocarcinoma from patients without any associated chemotherapeutic treatment or radiotherapy. Images were binarized based on a fixed threshold of the E-cadherin fluorescence channel, and then the FD of the binarized image outlines has been calculated in order to assess the ruggedness of the cellular membranes. Overall assessment of the FD revealed that the subtle membrane variations were evident enough to deem a statistically significant difference and the complexity of the membrane roughness was clearly higher for adenocarcinoma cases. We intended to evaluate if separating adenocarcinoma cases as low grade (G1 and G2) and high grade (G3 and solid), FD analysis could still differentiate membrane patterns and check if the available clinical parameters like age, gender, tumor location, lymph ganglia involved might correlate with FD values for adenocarcinoma patients. Altogether, the morphological analysis of a simple marker for the cell membrane can identify and distinguish tumor cells. Although there was a limited correlation between this analysis and the main clinical and pathological indicators of the disease, it will be very useful in the future for automatic computer-assisted diagnosis on slides, as well as for evaluating cellular adhesion and inter-cellular trafficking in cancer cells
Acute meningitis complicated with ventriculitis caused by Streptococcus dysgalactiae subsp. dysgalactiae

ABSTRACT Streptococcus dysgalactiae subspecies dysgalactiae (SDSD), also known as Lancefield group C streptococcus, is a pathogen found in animals. It is known to cause pyogenic infections in animals and is one of the most common pathogens that can cause mastitis in cattle. Very few reports of SDSD causing human diseases to have been reported in the literature, but we report a case of community-acquired meningitis and pyogenic ventriculitis caused by SDSD. This report is the first case of SDSD causing a central nervous system (CNS) infection in humans and aims to raise awareness about the role of SDSD in CNS infections. It also seeks to promote the recognition of this bacteria as a potential cause of invasive diseases.
Combined Effects of Doxorubicin and Temozolomide in Cultured Glioblastoma Cells

The oncological field benefits of extensive medical research and various types of cancer notice improvements, however glioblastoma multiforme remains one of the deadliest cancers in humans with virtually no advance in survival and clinical outcome. Temozolomide, the FDA approved drug for glioblastoma, faces numerous challenges such as resistance and side effects. To overcome these challenges, many combination therapies are currently studied. The present study analyses the effects of temozolomide in combination with doxorubicin on a glioblastoma cell line. Our results showed that both drugs displayed a cytotoxic effect on the studied cells in single administration (55% for 100μM temozolomide at 14 days, 53% for 100μM doxorubicin at 14 days), but without a synergistic effect in dual therapy. Although the results failed to produce the expected effect, they propose new research perspectives in the future.
Interactive association of chronic illness and food insecurity with emergency department utilization among school‐age children in the United States: A cross‐sectional study

Food insecurity combined with chronic disease conditions is a risk factor for Emergency Department (ED) utilization, an indicator of poor quality of care. However, such an association is not certain among school‐age children with chronic conditions. Therefore, we aim to determine the association of food insecurity, chronic conditions, and ED utilization among school‐age children in the United States.
Artifacts and artifact reduction in sonoelastography

A technique for reducing vibration artifacts encountered when using pure tone vibration in vibration amplitude sonoelastography is presented. Multi-tone signals were designed to synchronize with the pulse repetition frequency and packet size of the scanner. When applied to phantoms with known uniform elasticity it was found that noise levels using the multi-tone signals were 28 to 35% less than when pure tone vibration was used. Images of a hard phantom lesion made using multi-tone vibration compared favorably with those using pure tone vibration.
Volumetric segmentation of medical images by three-dimensional bubbles

The segmentation of structure from images is an inherently difficult problem in computer vision and a bottleneck to its widespread application, e.g., in medical imaging. This paper presents an approach for integrating local evidence such as regional homogeneity and edge response to form global structure for figure? ground segmentation. This approach is motivated by a shock-based morphogenetic language, where the growth of four types of shocks results in a complete description of shape. Specifically, objects are randomly hypothesized in the form of fourth-order shocks (seeds) which then grow, merge, split, shrink, and, in general, deform under physically motivated “forces,” but slow down and come to a halt near differential structures. Two major issues arise in the segmentation of 3D images using this approach. First, it is shown that the segmentation of 3D images by 3D bubbles is superior to a slice-by-slice segmentation by 2D bubbles or by “212D bubbles” which are inherently 2D but use 3D information for their deformation. Specifically, the advantages lie in an intrinsic treatment of the underlying geometry and accuracy of reconstruction. Second, gaps and weak edges, which frequently present a significant problem for 2D and 3D segmentation, are regularized by curvature-dependent curve and surface deformations which constitute diffusion processes. The 3D bubbles evolving in the 3D reaction? diffusion space are a powerful tool in the segmentation of medical and other images, as illustrated for several realistic examples.
European Economic

We provide a novel modeling framework to decompose euro area sovereign bond yields into five distinct components: ( 𝑖 ) expected future short-term risk-free rates and a term premium, ( 𝑖𝑖 ) a default risk premium, ( 𝑖𝑖𝑖 ) redenomination risk premium, ( 𝑖𝑣 ) liquidity risk premium, and ( 𝑣 ) segmentation (convenience) premium. Identification is achieved by considering sovereign yields jointly with other rates, including sovereign credit default swap spreads with and without redenomination as a credit event trigger. We illustrate our model by studying yield components embedded in German, French, Italian, and Spanish sovereign bonds, before and after the onset of the Covid-19 pandemic in 2020, and by examining the impact of European Central Bank (ECB) monetary policy and European Union (EU) fiscal policy announcements in response to the pandemic. We find that all five risk premia became sizable following the onset of the pandemic, and that both monetary and fiscal policy announcements had a pronounced effect on yields, mostly through default, redenomination, and segmentation (convenience) premia.
Chirality and polarization effects in nonlinear optics

Polarization effects play an even more important role in nonlinear optics than in linear optics because of the richer set of phenomena describable by higher-order tensor relations. The present contribution surveys some recent research on polarization aspects of nonlinear optical interactions, paying special attention to nonlinear optical interactions in chiral isotropic optical materials. We especially address the question of the existence of a linear electro-optic effect in chiral isotropic materials and analyse some of the conflicting statements that have recently been made in the scientific literature.
Taurocholic acid promotes hepatic stellate cell activation via S1PR2/p38 MAPK/YAP signaling under cholestatic conditions

Background/Aims Disrupted bile acid regulation and accumulation in the liver can contribute to progressive liver damage and fibrosis. However, the effects of bile acids on the activation of hepatic stellate cells (HSCs) remain unclear. This study investigated the effects of bile acids on HSC activation during liver fibrosis, and examined the underlying mechanisms. Methods The immortalized HSCs, LX-2 and JS-1cells were used for the in vitro study. in vitro, the adeno-associated viruses adeno-associated virus-sh-S1PR2 and JTE-013 were used to pharmacologically inhibit the activity of S1PR2 in a murine model of fibrosis induced by a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) diet. Histological and biochemical analyses were performed to study the involvement of S1PR2 in the regulation of fibrogenic factors as well as the activation properties of HSCs. Results S1PR2 was the predominant S1PR expressed in HSCs and was upregulated during taurocholic acid (TCA) stimulation and in cholestatic liver fibrosis mice. TCA-induced HSC proliferation, migration and contraction and extracellular matrix protein secretion were inhibited by JTE-013 and a specific shRNA targeting S1PR2 in LX-2 and JS-1 cells. Meanwhile, treatment with JTE-013 or S1PR2 deficiency significantly attenuated liver histopathological injury, collagen accumulation, and the expression of fibrogenesis-associated genes in mice fed a DDC diet. Furthermore, TCA-mediated activation of HSCs through S1PR2 was closely related to the yes-associated protein (YAP) signaling pathway via p38 mitogen-activated protein kinase (p38 MAPK). Conclusions TCA-induced activation of the S1PR2/p38 MAPK/YAP signaling pathways plays a vital role in regulating HSC activation, which might be therapeutically relevant for targeting cholestatic liver fibrosis.
A Mummers Farce - Retractions of Medical Papers conducted in Egyptian Institutions

Abstract: Rationale and Objective Egypt currently holds a record for the most retractions in the continent of Africa according to the Retraction Watch database, and the 2nd highest of countries in the Middle East. The purpose of this study was to perform a specific analysis on retracted medical publications from Egyptian affiliations to outline or delineate specific problems and solutions. Materials and Methods The Retraction Watch Database, Google Scholar, SCOPUS, PubMed, and journals sponsored by the Egyptian Knowledge Bank were searched for all Egypt affiliated retracted medical publications up to the date of August 31st 2022. We observed for the reason(s) for retraction, number of citations, the length of time between publication and retraction and more. Results 68 retractions were identified that could be linked directly to a known Egyptian institution listed in the study methodology. Most retractions originated from the speciality of Obstetrics and Gynecology (n=22), followed by Anesthesia (n=7). The top 3 reasons for retraction included unreliable results, FFP level misconduct, and duplicate publication. The number of retractions significantly increased over the years, especially in 2022. When taking into account the number of medical publications per institution, the institute with the highest rate of retractions was Mansoura University, while the lowest rate was Cairo University. Conclusion The number of retracted medical Egyptian publications continues to increase over time, as more issues are uncovered in research coming from this region. Medical papers from this area have been the focus of investigations that have suggested that many results are statistically unlikely to have occurred. Authors must employ a higher ethical standard in their work, while institutions must be openly collaborative with investigations and enact penalties where needed to deter future misconduct. Future studies on retracted articles should employ a methodology that considers the institutions where the studies were conducted in order to obtain a better understanding of specific problems in certain countries or regions. Keywords: Retracted Publication, Ethics, Misconduct, Egypt, Plagiarism, RetractionWatch
Safety Outcomes of Mechanical Thrombectomy Versus Combined Thrombectomy and Intravenous Thrombolysis in Tandem Lesions

BACKGROUND: We aimed to describe the safety and efficacy of mechanical thrombectomy (MT) with or without intravenous thrombolysis (IVT) for patients with tandem lesions and whether using intraprocedural antiplatelet therapy influences MT’s safety with IVT treatment. METHODS: This is a subanalysis of a pooled, multicenter cohort of patients with acute anterior circulation tandem lesions treated with MT from 16 stroke centers between January 2015 and December 2020. Primary outcomes included symptomatic intracranial hemorrhage (sICH) and parenchymal hematoma type 2. Additional outcomes included hemorrhagic transformation, successful reperfusion (modified Thrombolysis in Cerebral Infarction score 2b-3), complete reperfusion (modified Thrombolysis in Cerebral Infarction score 3), favorable functional outcome (90-day modified Rankin Scale score 0–2), excellent functional outcome (90-day modified Rankin Scale score 0–1), in-hospital mortality, and 90-day mortality. RESULTS: Of 691 patients, 512 were included (218 underwent IVT+MT and 294 MT alone). There was no difference in the risk of sICH (adjusted odds ratio [aOR], 1.22 [95% CI, 0.60–2.51]; P=0.583), parenchymal hematoma type 2 (aOR, 0.99 [95% CI, 0.47–2.08]; P=0.985), and hemorrhagic transformation (aOR, 0.95 [95% CI, 0.62–1.46]; P=0.817) between the IVT+MT and MT alone groups after adjusting for confounders. Administration of IVT was associated with an increased risk of sICH in patients who received intravenous antiplatelet therapy (aOR, 3.04 [95% CI, 0.99–9.37]; P=0.05). The IVT+MT group had higher odds of a 90-day modified Rankin Scale score 0 to 2 (aOR, 1.72 [95% CI, 1.01–2.91]; P=0.04). The odds of successful reperfusion, complete reperfusion, 90-day modified Rankin Scale score 0 to 1, in-hospital mortality, or 90-day mortality did not differ between the IVT+MT versus MT alone groups. CONCLUSIONS: Our study showed that the combination of IVT with MT for tandem lesions did not increase the overall risk of sICH, parenchymal hematoma type 2, or overall hemorrhagic transformation independently of the cervical revascularization technique used. However, intraprocedural intravenous antiplatelet therapy during acute stent implantation might be associated with an increased risk of sICH in patients who received IVT before MT. Importantly, IVT+MT treatment was associated with a higher rate of favorable functional outcomes at 90 days.
Turbulent Unsteady Flow Analysis of Horizontal Axis Wind Turbine Airfoil Aerodynamics Based on the Harmonic Balance Reynolds-Averaged Navier-Stokes Equations

Several horizontal axis wind turbine unsteady ﬂows, such as that associated with the yawed wind regime, are predominantly periodic. Harmonic balance Reynolds-averaged Navier-Stokes solvers can be used to accurately analyze such ﬂows substantially faster than what their time-domain counterparts can do. The paper presents the mathematical and numerical features of a new turbulent harmonic balance Navier-Stokes solver using Menter’s shear stress transport model for the turbulence closure. The effectiveness of the developed technology is demonstrated by using two-dimensional harmonic balance ﬂow simulations to determine the periodic aerodynamic loads acting on a blade section of a 164 m-diameter wind turbine rotor in yawed wind. Presented results highlight that the turbulent harmonic balance solver can compute the sectional hysteresis force cycles more than 10 times faster than its time-domain counterpart, and with an accuracy comparable to that of the time-domain solver.
Characterization of the array modes of high-power gain-guided GaAs single-quantum-well laser arrays

The characteristics of gain-guided GaAs single-quantum-well laser arrays, using proton bombardment to confine the current flow to 11 stripes on 9-/spl mu/m centers, are described. The longitudinal-mode spectrum, the spectrally resolved far-field, and the near-field of this laser array were studied experimentally up to three times threshold current. The laser arrays are found to emit at /spl sim/10 longitudinal modes corresponding to the Fabry-Perot modes of the laser. The longitudinal spectrum is current dependent. Near threshold current, the spectrum consists of a number of longitudinal modes where only the fundamental mode of the array laser. At larger current, each of the longitudinal modes is broadened and the spectrum of each longitudinal mode consists of many individual emission lines of the array modes. For each longitudinal mode, the lowest order array mode emits at the longest wavelength and the highest order array mode emits at the shortest wavelength. The wavelength separation between neighboring array modes increases with increasing mode order. Fourteen array modes are found to emit simultaneously at three times threshold current. The experimental results are in good agreement with direct array-mode analysis based on the finite-difference method.
Dynamic Named Entity Recognition

Named Entity Recognition (NER) is a challenging and widely studied task that involves detecting and typing entities in text. So far, NER still approaches entity typing as a task of classification into universal classes (e.g. date, person, or location). Recent advances in natural language processing focus on architectures of increasing complexity that may lead to overfitting and memorization, and thus, underuse of context. Our work targets situations where the type of entities depends on the context and cannot be solved solely by memorization. We hence introduce a new task: Dynamic Named Entity Recognition (DNER), providing a framework to better evaluate the ability of algorithms to extract entities by exploiting the context. The DNER benchmark is based on two datasets, DNER-RotoWire and DNER-IMDb, respectively aiming at detecting winning/losing players in different basketball match summaries and predicting actors' credit orders within different movie synopsis. We evaluate baseline models and present experiments reflecting issues and research axes related to this novel task.
Coronal Magnetic Fields Derived with Images Acquired during the 2017 August 21 Total Solar Eclipse

The coronal magnetic field, despite its overwhelming importance to the physics and dynamics of the corona, has only rarely been measured. Here, electron density maps derived from images acquired during the total solar eclipse of 2017 August 21 are employed to demonstrate a new technique to measure coronal magnetic fields. The strength of the coronal magnetic fields is derived with a semiempirical formula relating the plasma magnetic energy density to the gravitational potential energy. The resulting values are compared with those provided by more advanced coronal field reconstruction methods based on MHD simulations of the whole corona starting from photospheric field measurements, finding very good agreement. Other parameters such as the plasma β and Alfvén velocity are also derived and compared with those of MHD simulations. Moreover, the plane-of-sky (POS) orientation of the coronal magnetic fields is derived from the observed inclination of the coronal features in filtered images, also finding close agreement with magnetic field reconstructions. Hence, this work demonstrates for the first time that the 2D distribution of coronal electron densities measured during total solar eclipses is sufficient to provide coronal magnetic field strengths and inclinations projected on the POS. These are among the main missing pieces of information that have limited so far our understanding of physical phenomena going on in the solar corona.
LiT Tuned Models for Efficient Species Detection

Recent advances in training vision-language models have demonstrated unprecedented robustness and transfer learning effectiveness; however, standard computer vision datasets are image-only, and therefore not well adapted to such training methods. Our paper introduces a simple methodology for adapting any fine-grained image classification dataset for distributed vision-language pretraining. We implement this methodology on the challenging iNaturalist-2021 dataset, comprised of approximately 2.7 million images of macro-organisms across 10,000 classes, and achieve a new state-of-the art model in terms of zero-shot classification accuracy. Somewhat surprisingly, our model (trained using a new method called locked-image text tuning) uses a pre-trained, frozen vision representation, proving that language alignment alone can attain strong transfer learning performance, even on fractious, long-tailed datasets. Our approach opens the door for utilizing high quality vision-language pretrained models in agriculturally relevant applications involving species detection.
Deep Convolutional Framelet Denoising for Panoramic by Mixed Wavelet Integration

Enhancing quality and removing noise during preprocessing is one of the most critical steps in image processing. X-ray images are created by photons colliding with atoms and the variation in scattered noise absorption. This noise causes the graph's quality of medical to decline and, occasionally, causes it to repeat itself, causing an elevation in the patient's effective dose. One of the most critical challenges in this area has consistently been lowering the image noise. Techniques like BM3d, low-pass filters, and Autoencoder have taken this step. Due to the algorithm's structure and high repetition rate, neural networks using various architectures have reduced noise with acceptable results over the past ten years compared to the traditional BM3D and low-pass filters. The Hankel matrix combined with neural networks is one of these configurations. The Hankel matrix seeks a local circle by splitting up individual values into local and non-local components using a non-local matrix. A non-local matrix can be created using the wave or DCT. This paper proposes combining the waveform with the Daubechies (D4) wavelength because it has more energy and uses the u-Net neural network structure, which uses the waveform alone at each stage. The outcomes were evaluated using the PSNR and SSIM criteria, and the outcomes were verified by using various waves. The effectiveness of a one-wave network has increased from 0.5% to 1.2%, according to studies done on other datasets.
Inclusion relations among fractional Orlicz-Sobolev spaces and a Littlewood-Paley characterization

Embeddings among fractional Orlicz-Sobolev spaces with different smoothness are characterized. The equivalence of their Gagliardo-Slobodeckij norms to norms defined via Littlewood-Paley decompostions, via oscillations, or via Besov type difference quotients is also established. These equivalences, of independent interest, are a key tool in the proof of the relevant embeddings. They also rest upon a new optimal inequality for convolutions in Orlicz spaces.