Miracle-dz/UniFAR-FTUs huggingface dataset:
Histopathological Survey on Sarcocystis Species Infection in Slaughtered Cattle of Zabol-Iran

Objective Sarcocystosis is an important zoonotic protozoal disease with worldwide distribution and wide range of hosts. The aim of the present study was to determine the intensity of Sarcocystis spp. infection and to show histopathological features of their cystic lesions in slaughtered cattle of Zabol- Iran. Methods From April to September 2018, 500 tissue samples from esophagus, heart, diaphragm, tongue and masticatory muscles were prepared from 100 slaughtered cattle. All samples were fixed in 10% neutral buffered formalin and routine tissue processing protocol was performed. Results The microscopic results showed that 92.2% of specimens had thin-walled cysts of S. cruzi and 14% had thick-walled Sarcocystis (S. hirsuta and S. hominis) but macrocyst was only observed in one cattle. The positivity rate of thin walled cysts was 58.8% for heart, 13.9% for masticatory muscles, 10.2% for tongue, 9.3% for esophagus and 7.8% for diaphragm. The positivity rate of thick walled cysts was 32.8% for esophagus, 28.6% for tongue, 22.9% for heart, 15.7% for masticatory muscles and 0% for diaphragm, which could represent either S. hominis or S. hirsuta. The most infected tissue was heart and the least infected tissue was diaphragm. Thin walled cysts (S. cruzi) were mostly found in heart and were less found in diaphragm. However, thick-walled cysts (S. hirsuta and S. hominis) were mostly detected in esophagus. No thick-walled cysts were found in diaphragm muscle. Conclusion A high positivity rate of sarcocystosis in slaughtered cattle in Zabol abattoir revealed heavily environmental contamination of Sistan region by this important parasitic disease.
In-vitro and In-vivo Anti-hyperglycemic Activities of Taxifolin and Its Derivatives isolated from Pigmented Rice (Oryzae sativa L. cv. Superhongmi).

Superhongmi is a new rice variety, which was developed for the enrichment of bioactive compounds through cross-breeding three varieties of rice breeds in Korea. The HPLC/PDA/QTOF-MS analysis has revealed that superhongmi bran extract contained four taxifolin derivatives as well as cyanidin 3-glucoside. The high-performance countercurrent chromatography (CCC) and reversed-phase HPLC led to the isolation of aforementioned five compounds, and spectroscopic analysis identified cyanidin 3-glucoside (1), along with (2R,3R)-taxifolin 3-O--D-glucopyranoside (2), (2R,3R)-4'-O-methyltaxifolin 3-O--D-glucopyranoside (a novel compound) (3), (2R,3R)-taxifolin (4), and (2R,3R)-4'-O-methyltaxifolin (5). Compound 2 had the highest rat small intestinal sucrase inhibitory activity (0.54 mM) relevant for potentially managing postprandial hyperglycemia, followed by compound 1 (0.97 mM) and compound 4 (1.74 mM, IC50), respectively. The anti-hyperglycemic effect of compound 4 (taxifolin), a main peak in HPLC analysis was investigated using Sprague-Dawley (SD) rat model. Compared to a control, taxifolin treatment (p < 0.001) reduced significantly after sucrose loading the observed postprandial blood-glucose and the maximum blood glucose (Cmax) by 15% (203.60 ± 15.86 to 172.30 ± 12.74). These results indicate that taxifolin derivatives that inhibit the activity of carbohydrate hydrolyzing enzymes resulting to reduced dietary carbohydrate absorption can potential be used as a strategy to manage diabetes.
Connexin43 peptide, TAT-Cx43266–283, selectively targets glioma cells, impairs malignant growth, and enhances survival in mouse models in vivo

Abstract Background Malignant gliomas are the most frequent primary brain tumors and remain among the most incurable cancers. Although the role of the gap junction protein, connexin43 (Cx43), has been deeply investigated in malignant gliomas, no compounds have been reported with the ability to recapitulate the tumor suppressor properties of this protein in in vivo glioma models. Methods TAT-Cx43266–283 a cell-penetrating peptide which mimics the effect of Cx43 on c-Src inhibition, was studied in orthotopic immunocompetent and immunosuppressed models of glioma. The effects of this peptide in brain cells were also analyzed. Results While glioma stem cell malignant features were strongly affected by TAT-Cx43266–283, these properties were not significantly modified in neurons and astrocytes. Intraperitoneally administered TAT-Cx43266–283 decreased the invasion of intracranial tumors generated by GL261 mouse glioma cells in immunocompetent mice. When human glioma stem cells were intracranially injected with TAT-Cx43266–283 into immunodeficient mice, there was reduced expression of the stemness markers nestin and Sox2 in human glioma cells at 7 days post-implantation. Consistent with the role of Sox2 as a transcription factor required for tumorigenicity, TAT-Cx43266–283 reduced the number and stemness of human glioma cells at 30 days post-implantation. Furthermore, TAT-Cx43266–283 enhanced the survival of immunocompetent mice bearing gliomas derived from murine glioma stem cells. Conclusion TAT-Cx43266–283 reduces the growth, invasion, and progression of malignant gliomas and enhances the survival of glioma-bearing mice without exerting toxicity in endogenous brain cells, which suggests that this peptide could be considered as a new clinical therapy for high-grade gliomas.
BRD4-Regulated Molecular Targets in Mantle Cell Lymphoma: Insights into Targeted Therapeutic Approach

Background: Since bromodomain-containing protein 4 (BRD4) facilitates the transcription of genes important for neoplastic cells in a cancer-type specific manner, BRD4-regulated molecules may also include therapeutic targets for mantle cell lymphoma (MCL), a treatment-refractory subtype of malignant lymphoma. Materials and Methods: In order to uncover direct BRD4-regulated targets in MCL, we performed integrated analysis using the pathway database and the results of both gene-expression profiling and chromatin immunoprecipitation with parallel sequencing for BRD4. Results: Treatment with BRD4 inhibitor I-BET151 exerted a dose-dependent inhibitory effect on cell proliferation in MCL cell lines. BRD4 was found to directly regulate series of genes involved in the B-cell receptor (BCR) signaling pathway, including B-cell linker (BLNK), paired box 5 (PAX5), and IKAROS family zinc finger 3 (IKZF3), and several oncogenes, such as MYB. Indeed, the combinatory inhibition of BCR pathway and IKZF showed an additive antitumor effect. Conclusion: Concomitant targeting multiple BRD4-regulated molecules may constitute a rational therapeutic strategy for MCL.
Nicotine Induces Polyspermy in Sea Urchin Eggs through a Non-Cholinergic Pathway Modulating Actin Dynamics

While alkaloids often exert unique pharmacological effects on animal cells, exposure of sea urchin eggs to nicotine causes polyspermy at fertilization in a dose-dependent manner. Here, we studied molecular mechanisms underlying the phenomenon. Although nicotine is an agonist of ionotropic acetylcholine receptors, we found that nicotine-induced polyspermy was neither mimicked by acetylcholine and carbachol nor inhibited by specific antagonists of nicotinic acetylcholine receptors. Unlike acetylcholine and carbachol, nicotine uniquely induced drastic rearrangement of egg cortical microfilaments in a dose-dependent way. Such cytoskeletal changes appeared to render the eggs more receptive to sperm, as judged by the significant alleviation of polyspermy by latrunculin-A and mycalolide-B. In addition, our fluorimetric assay provided the first evidence that nicotine directly accelerates polymerization kinetics of G-actin and attenuates depolymerization of preassembled F-actin. Furthermore, nicotine inhibited cofilin-induced disassembly of F-actin. Unexpectedly, our results suggest that effects of nicotine can also be mediated in some non-cholinergic pathways.
Multiple features within the syntaxin Sed5p mediate its Golgi localization

Protein retention and the transport of proteins and lipids into and out of the Golgi is intimately linked to the biogenesis and homeostasis of this sorting hub of eukaryotic cells. Of particular importance are membrane proteins that mediate membrane fusion events with and within the Golgi—the Soluble N‐ethylmaleimide‐sensitive factor attachment protein receptors (SNAREs). In the Golgi of budding yeast cells, the syntaxin SNARE Sed5p oversees membrane fusion events. Determining how Sed5p is localized to and trafficked within the Golgi is critical to informing our understanding of the mechanism(s) of biogenesis and homeostasis of this organelle. Here we establish that the steady‐state localization of Sed5p to the Golgi appears to be primarily conformation‐based relying on intra‐molecular associations between the Habc domain and SNARE‐motif while its tribasic COPI‐coatomer binding motif plays a role in intra‐Golgi retention.
Beyond “Intent‐to‐treat” and “Per protocol”: Improving assessment of treatment effects in clinical trials through the specification of an estimand

There is a key problem in randomised clinical trials as outcomes can be distorted due to informative post‐randomisation events. This is inadequately addressed by the use of traditional intention‐to‐treat or per protocol analysis sets and often either ignored or wrongly labelled as missing data. As a consequence, the treatment effects of interest in a clinical trial are not well defined and their estimates might be misinterpreted. The estimand framework should help all those planning, conducting and analysing clinical trials as well as those interpreting the results to better define, estimate and understand the treatment effects of interest. This framework is described in the addendum to ICH E9 and addresses precisely this problem. It is relevant for regulatory drug trials and academic‐run trials, as well as for trials of nonpharmacological interventions.
Gender Surgery Beyond Chest and Genitals: Current Insurance Landscape.

BACKGROUND Plastic surgery plays an essential role in the treatment of gender dysphoria. International standards of care currently consider genital and chest surgeries to be medically necessary. Ancillary procedures such as facial surgery, chondrolaryngoplasty, hair restoration/removal, and body contouring are considered cosmetic surgeries except in individual circumstances. OBJECTIVE The authors sought to assess the frequency of coverage provision for ancillary transition-related surgeries through a cross-sectional analysis of US insurance policies. METHODS The authors selected insurance companies based on state enrollment data and market share. Policies were identified through web-based search and telephone interviews. A list of eligible procedures was compiled and grouped into 5 categories: body masculinization, body feminization, facial procedures, hair restoration/removal, and chondrolaryngoplasty. Medical necessity criteria from publicly accessible policies were then abstracted. RESULTS Sixty-one insurance companies held an established policy. One-third of these policies offered favorable coverage for at least 1 ancillary procedure. Chondrolaryngoplasty was the most covered category (26%, n = 16), whereas body masculinization was the least covered (8%, n = 5). Almost two-thirds of the companies with favorable policies listed coverage criteria. We identified 4 recurring requirements: age, hormone therapy, continuous living in a congruent gender role, and referral from a mental health professional. CONCLUSION There is a low prevalence of US insurance coverage for ancillary gender surgeries and wide variability in coverage criteria. Reevaluation of ancillary transition-related procedures from cosmetic to medically necessary based on clinical judgement or establishment of defined coverage criteria may augment coverage and better address the needs of transgender patients.
OsmiR530 acts downstream of OsPIL15 to regulate grain yield in rice

Summary MicroRNAs (miRNAs) are a class of small noncoding RNAs that play important roles in plant growth and development as well as in stress responses. However, little is known about their regulatory functions affecting rice grain yield. We functionally characterized a novel miRNA in rice, OsmiR530, its target OsPL3, and its upstream regulator phytochrome‐interacting factor‐like 15 (OsPIL15). Their effects on rice yield were dissected comprehensively. We determined that OsmiR530 negatively regulates grain yield. Blocking OsmiR530 increases grain yield, whereas OsmiR530 overexpression significantly decreases grain size and panicle branching, leading to yield loss. Additionally, OsPL3, which encodes a PLUS3 domain‐containing protein, is targeted directly by OsmiR530. Knocking out OsPL3 decreases the grain yield. In‐depth analyses indicated that OsPIL15 activates OsMIR530 expression by directly binding to the G‐box elements in the promoter. Analyses of genetic variations suggested that the OsMIR530 locus has likely been subjected to artificial selection during rice breeding. The results presented herein reveal a novel OsPIL15–OsmiR530 module controlling rice grain yield, thus providing researchers with a new target for the breeding of high‐yielding rice.
Utilizing Players’ Playtime Records for Churn Prediction: Mining Playtime Regularity

Churn prediction is an important topic in the free online game industry. Reducing the churn rate of a game significantly helps with the success of the game. Churn prediction helps a game operator identify possible churning players and keep them engaged in the game via appropriate operational strategies, marketing strategies, and/or incentives. Playtime-related features are some of the widely used universal features for most churn prediction models. In this article, we consider developing new universal features for churn predictions for long-term players based on playtime. In particular, we measure playtime regularity using the notion of entropy and cross-entropy from information theory. After computing playtime regularity of players from the datasets of six free online games of different types, we leverage information from the playtime regularity in the form of universal features for churn prediction. Experiments show that the proposed features are better at predicting churners compared to the baseline features, implying that the proposed features could utilize the information extracted from playtime more effectively than the related baseline playtime features.
Efficient Video Semantic Segmentation with Labels Propagation and Refinement

This paper tackles the problem of real-time semantic segmentation of high definition videos using a hybrid GPU-CPU approach. We propose an Efficient Video Segmentation (EVS) pipeline that combines:(i)On the CPU, a very fast optical flow method, that is used to exploit the temporal aspect of the video and propagate semantic information from one frame to the next. It runs in parallel with the GPU. (ii)On the GPU, two Convolutional Neural Networks: A main segmentation network that is used to predict dense semantic labels from scratch, and a Refiner that is designed to improve predictions from previous frames with the help of a fast Inconsistencies Attention Module (IAM). The latter can identify regions that cannot be propagated accurately.We suggest several operating points depending on the desired frame rate and accuracy. Our pipeline achieves accuracy levels competitive to the existing real-time methods for semantic image segmentation (mIoU above 60%), while achieving much higher frame rates. On the popular Cityscapes dataset with high resolution frames (2048 × 1024), the proposed operating points range from 80 to 1000 Hz on a single GPU and CPU.
DADA: A Large-scale Benchmark and Model for Driver Attention Prediction in Accidental Scenarios

Driver attention prediction has recently absorbed increasing attention in traffic scene understanding and is prone to be an essential problem in vision-centered and human-like driving systems. This work, different from other attempts, makes an attempt to predict the driver attention in accidental scenarios containing normal, critical and accidental situations simultaneously. However, challenges tread on the heels of that because of the dynamic traffic scene, intricate and imbalanced accident categories. With the hypothesis that driver attention can provide a selective role of crash-object for assisting driving accident detection or prediction, this paper designs a multi-path semantic-guided attentive fusion network (MSAFNet) that learns the spatio-temporal semantic and scene variation in prediction. For fulfilling this, a large-scale benchmark with 2000 video sequences (named as DADA-2000) is contributed with laborious annotation for driver attention (fixation, saccade, focusing time), accident objects/intervals, as well as the accident categories, and superior performance to state-of-the-arts are provided by thorough evaluations. As far as we know, this is the first comprehensive and quantitative study for the human-eye sensing exploration in accidental scenarios. DADA-2000 is available at this https URL.
Approximating Human Judgment of Generated Image Quality

Generative models have made immense progress in recent years, particularly in their ability to generate high quality images. However, that quality has been difficult to evaluate rigorously, with evaluation dominated by heuristic approaches that do not correlate well with human judgment, such as the Inception Score and Frechet Inception Distance. Real human labels have also been used in evaluation, but are inefficient and expensive to collect for each image. Here, we present a novel method to automatically evaluate images based on their quality as perceived by humans. By not only generating image embeddings from Inception network activations and comparing them to the activations for real images, of which other methods perform a variant, but also regressing the activation statistics to match gold standard human labels, we demonstrate 66% accuracy in predicting human scores of image realism, matching the human inter-rater agreement rate. Our approach also generalizes across generative models, suggesting the potential for capturing a model-agnostic measure of image quality. We open source our dataset of human labels for the advancement of research and techniques in this area.
Characterizing and Detecting Money Laundering Activities on the Bitcoin Network

Bitcoin is by far the most popular crypto-currency solution enabling peer-to-peer payments. Despite some studies highlighting the network does not provide full anonymity, it is still being heavily used for a wide variety of dubious financial activities such as money laundering, ponzi schemes, and ransom-ware payments. In this paper, we explore the landscape of potential money laundering activities occurring across the Bitcoin network. Using data collected over three years, we create transaction graphs and provide an in-depth analysis on various graph characteristics to differentiate money laundering transactions from regular transactions. We found that the main difference between laundering and regular transactions lies in their output values and neighbourhood information. Then, we propose and evaluate a set of classifiers based on four types of graph features: immediate neighbours, curated features, deepwalk embeddings, and node2vec embeddings to classify money laundering and regular transactions. Results show that the node2vec-based classifier outperforms other classifiers in binary classification reaching an average accuracy of 92.29% and an F1-measure of 0.93 and high robustness over a 2.5-year time span. Finally, we demonstrate how effective our classifiers are in discovering unknown laundering services. The classifier performance dropped compared to binary classification, however, the prediction can be improved with simple ensemble techniques for some services.
Toda chain flow in Krylov space

We show in full generality that time-correlation function of a physical observable analytically continued to imaginary time is a tau-function of integrable Toda hierarchy. Using this relation we show that the singularity along the imaginary axis, which is a generic behavior for quantum non-integrable many-body system, is due to delocalization in Krylov space.
Pointwise Attention-Based Atrous Convolutional Neural Networks

With the rapid progress of deep convolutional neural networks, in almost all robotic applications, the availability of 3D point clouds improves the accuracy of 3D semantic segmentation methods. Rendering of these irregular, unstructured, and unordered 3D points to 2D images from multiple viewpoints imposes some issues such as loss of information due to 3D to 2D projection, discretizing artifacts, and high computational costs. To efficiently deal with a large number of points and incorporate more context of each point, a pointwise attention-based atrous convolutional neural network architecture is proposed. It focuses on salient 3D feature points among all feature maps while considering outstanding contextual information via spatial channel-wise attention modules. The proposed model has been evaluated on the two most important 3D point cloud datasets for the 3D semantic segmentation task. It achieves a reasonable performance compared to state-of-the-art models in terms of accuracy, with a much smaller number of parameters.
Simplicial sets with a notion of smallness

We consider simplicial sets equipped with a notion of smallness, and observe that this slight "topological" extension of the "algebraic" simplicial language allows a concise reformulation of a number of classical notions in topology, e.g. continuity, limit of a map or a sequence along a filter, various notions of equicontinuity and uniform convergence of a sequence of functions; completeness and compactness; in algebraic topology, locally trivial bundles as a direct product after base-change and geometric realisation as a space of discontinuous paths. In model theory, we observe that indiscernible sequences in a model form a simplicial set with a notion of smallness which can be seen as an analogue of the Stone space of types. These reformulations are presented as a series of exercises, to emphasise their elementary nature and that they indeed can be used as exercises to make a student familiar with computations in basic simplicial and topological language. (Formally, we consider the category of simplicial objects in the category of filters in the sense of Bourbaki.) This work is unfinished and is likely to remain such for a while, hence we release it as is, in the small hope that our reformulations may provide interesting examples of computations in basic simplicial and topological language on material familiar to a student in a first course of topology or category theory.