Miracle-dz/UniFAR-FTUs huggingface dataset:
Dissociable Network Properties of Anesthetic State Transitions

Background:It is still unknown whether anesthetic state transitions are continuous or binary. Mathematical graph theory is one method by which to assess whether brain networks change gradually or abruptly upon anesthetic induction and emergence. Methods:Twenty healthy males were anesthetized with an induction dose of propofol, with continuous measurement of 21-channel electroencephalogram at baseline, during anesthesia, and during recovery. From these electroencephalographic data a “genuine network” was reconstructed based on the surrogate data method. The effects of topologic structure and connection strength on information transfer through the network were measured independently across different states. Results:Loss of consciousness was consistently associated with a disruption of network topology. However, recovery of consciousness was associated with complex patterns of altered connection strength after the initial topologic structure had slowly recovered. In one group of subjects, there was a precipitous increase of connection strength that was associated with reduced variability of emergence time. Analysis of regional effects on brain networks demonstrated that the parietal network was significantly disrupted, whereas the frontal network was minimally affected. Conclusions:By dissociating the effects of network structure and connection strength, both continuous and discrete elements of anesthetic state transitions were identified. The study also supports a critical role of parietal networks as a target of general anesthetics.
The differential effect of background music on memory for verbal and visuospatial information

Abstract Background music is a part of our everyday activities. Considerable evidence suggests that listening to music while performing cognitive tasks may negatively influence performance. However, other studies have shown that it can benefit memory when the music played during the encoding of information is also provided during the retrieval of that information, in the so-called context dependent memory effect. Since controversial results may be attributed to the nature of the material to be memorized, the aim of the present study is to compare the potential effect of consistent background music on the immediate and long-term recall of verbal and visuospatial information. Experiment 1 showed that instrumental background music does not benefit nor decrease recall of a list of unrelated words, both at the immediate and the 48-hours-delayed tests. By contrast, Experiment 2 revealed that the same background music can impair immediate and therefore long-term memory for visuospatial information. Results are interpreted in terms of competition for neurocognitive resources, with tasks mostly relying on the same brain hemisphere competing for a limited set of resources. Hence, background music might impair visuospatial memory to a greater extent than verbal memory, in the context of limited capacity cognitive system. In conclusion, the nature of the material to be learnt must be considered to fully understand the effect of background music on memory.
Survivin Promoter Polymorphism (-31 C/G): A Genetic Risk Factor for Oral Cancer

Background: The polymorphism of survivin gene at its promoter region is one of the risk factors for OSCC . This polymorphism involves substitution of G for C (9904341), and it is present at the cell cycle dependent elements and cell cycle homology region repressor binding motif of promoter. This study aimed to find the association between survivin -31C/G polymorphism and prevalence of OSCC in a subset of Pakistani population. Methodology: This case-control study was conducted on 47 cases with and 101 healthy individuals with no family history of cancer. We used polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) protocols. Results: The most common site of oral cancer in our research was the buccal mucosa followed by tongue and the least one was the labial mucosa. The histological tumor type of all 47 cases was squamous cell type. In our research, stage II had the highest prevalence, accounting for 34% of patients, while the prevalence of stage I was 31% in the case group. The prevalence of stage III and IV was 25% and 8%, respectively. The numbers of moderately and poorly differentiated tumors were equal. We found a significant association between the CC genotype of survivin and OSCC prevalence (OR was 9.395 at 95% CI: 1.0202-86.5251, p-value= 0.04). The GG genotype also showed significant P value (OR: 0.4709 with 95% CI: 0.2323- 0.9546 at a P VALUE of 0.0367). while no significant P value was noted for CG genotype (OR: 1.4317 with 95% CI: 0.7513 -2.8658, p- value= 0.31). Conclusion: Survivin -31G/C polymorphism was strongly associated with OSCC prevalence. The C allele was more common in case group as compared to healthy individuals living in Pakistan.
Optimization of drying process and pressurized liquid extraction for recovery of bioactive compounds from avocado peel by‐product

The aim of the present study was to optimize the extraction of phenolic compounds in avocado peel using pressurized liquid extraction (PLE) with GRAS solvents. Response surface methodology (RSM) based on Central Composite Design 22 model was used in order to optimize PLE conditions. Moreover, the effect of air drying temperature on the total polyphenol content (TPC) and individual phenolic compounds concentration were evaluated. The quantification of individual compounds was performed by HPLC‐DAD‐ESI‐TOF‐MS. The optimized extraction conditions were 200°C as extraction temperature and 1:1 v/v as ethanol/water ratio. Regarding to the effect of drying, the highest TPC was obtained with a drying temperature of 85°C. Forty seven phenolic compounds were quantified in the obtained extracts, showing that phenolic acids found to be the more stables compounds to drying process, while procyanidins were the more thermolabiles analytes. To our knowledge, this is the first available study in which phenolic compounds extraction was optimized using PLE and such amount of phenolic compounds was quantified in avocado peel. These results confirm that PLE represents a powerful tool to obtain avocado peel extracts with high concentration in bioactive compounds suitable for its use in the food, cosmetic or pharmaceutical sector.
Additive Effects of Rebamipide Plus Proton Pump Inhibitors on the Expression of Tight Junction Proteins in a Rat Model of Gastro-Esophageal Reflux Disease

Background/Aims The aim of this study was to investigate the effects of rebamipide on tight junction proteins in the esophageal mucosa in a rat model of gastroesophageal reflux disease (GERD). Methods GERD was created in rats by tying the proximal stomach. The rats were divided into a control group, a proton pump inhibitor (PPI) group, and a PPI plus rebamipide (PPI+R) group. Pantoprazole (5 mg/kg) was administered intraperitoneally to the PPI and PPI+R groups. An additional dose of rebamipide (100 mg/kg) was administered orally to the PPI+R group. Mucosal erosions, epithelial thickness, and leukocyte infiltration into the esophageal mucosa were measured in isolated esophagi 14 days after the procedure. A Western blot analysis was conducted to measure the expression of claudin-1, -3, and -4. Results The mean surface area of mucosal erosions, epithelial thickness, and leukocyte infiltration were lower in the PPI group and the PPI+R group than in the control group. Western blot analysis revealed that the expression of claudin-3 and -4 was significantly higher in the PPI+R group than in the control group. Conclusions Rebamipide may exert an additive effect in combination with PPI to modify the tight junction proteins of the esophageal mucosa in a rat model of GERD. This treatment might be associated with the relief of GERD symptoms.
Development of the thalamus: From early patterning to regulation of cortical functions

The thalamus is a brain structure of the vertebrate diencephalon that plays a central role in regulating diverse functions of the cerebral cortex. In traditional view of vertebrate neuroanatomy, the thalamus includes three regions, dorsal thalamus, ventral thalamus, and epithalamus. Recent molecular embryological studies have redefined the thalamus and the associated axial nomenclature of the diencephalon in the context of forebrain patterning. This new view has provided a useful conceptual framework for studies on molecular mechanisms of patterning, neurogenesis and fate specification in the thalamus as well as the guidance mechanisms for thalamocortical axons. Additionally, the availability of genetic tools in mice has led to important findings on how thalamic development is linked to the development of other brain regions, particularly the cerebral cortex. This article will give an overview of the organization of the embryonic thalamus and how progenitor cells in the thalamus generate neurons that are organized into discrete nuclei. I will then discuss how thalamic development is orchestrated with the development of the cerebral cortex and other brain regions.
The effects of sedentary behavior on memory and markers of memory function: a systematic review

ABSTRACT Objective: To evaluate the association of sedentary behavior on memory and markers of memory among humans of all ages. Methods: PubMed, PsychInfo, Sports Discus and Google Scholar databases were searched. Inclusionary criteria included: Published in English; conducted among humans (children to older adults); employ a cross-sectional, prospective or experimental design; include a measure of sedentary behavior as the independent variable (e.g. time spent sitting or watching television); and include a memory-related outcome measure (e.g. behavioral performance on a memory task, brain tissue volume in a memory structure). Information on participant characteristics, study design, sedentary behavior measure, memory outcome measure, and hypothesized mechanisms were extracted. The relationship between sedentary behavior and memory was synthesized while considering the data extraction parameters. Results: In total, 25 articles met the inclusionary criteria, including 8 studies among children/adolescents and 17 among adults. Sedentary behavior was assessed subjectively (e.g. TV viewing, computer use, reading) and objectively (e.g. accelerometry). Outcome measures included behavioral performance on various memory tasks (e.g. episodic and working memory), BDNF levels, brain volumetric measures of the temporal lobe, and hippocampal glucose metabolism. Overall, for both the child and adult studies, findings were mixed, with studies demonstrating null, inverse, and positive associations between sedentary behavior and memory. Sedentary behavior type may play a distinct role in the relationship between sedentary behavior and memory, as computer use, in particular, appeared to favorably influence memory when compared to other sedentary types (e.g. TV viewing, which showed in inverse association with memory in select studies). Conclusion: There is conflicting evidence of the relationship between sedentary behavior and memory-related outcomes among children and adults. Future studies are needed to further disentangle these complex interrelationships. Such studies should also carefully consider how physical activity may or may not moderate these relationships.
Structurally optimized shells

Shells, i.e., objects made of a thin layer of material following a surface, are among the most common structures in use. They are highly efficient, in terms of material required to maintain strength, but also prone to deformation and failure. We introduce an efficient method for reinforcing shells, that is, adding material to the shell to increase its resilience to external loads. Our goal is to produce a reinforcement structure of minimal weight. It has been demonstrated that optimal reinforcement structures may be qualitatively different, depending on external loads and surface shape. In some cases, it naturally consists of discrete protruding ribs; in other cases, a smooth shell thickness variation allows to save more material. Most previously proposed solutions, starting from classical Michell trusses, are not able to handle a full range of shells (e.g., are restricted to self-supporting structures) or are unable to reproduce this range of behaviors, resulting in suboptimal structures. We propose a new method that works for any input surface with any load configurations, taking into account both in-plane (tensile/compression) and out-of-plane (bending) forces. By using a more precise volume model, we are capable of producing optimized structures with the full range of qualitative behaviors. Our method includes new algorithms for determining the layout of reinforcement structure elements, and an efficient algorithm to optimize their shape, minimizing a non-linear non-convex functional at a fraction of the cost and with better optimality compared to standard solvers. We demonstrate the optimization results for a variety of shapes, and the improvements it yields in the strength of 3D-printed objects.
Unsupervised Data Augmentation

Despite its success, deep learning still needs large labeled datasets to succeed. Data augmentation has shown much promise in alleviating the need for more labeled data, but it so far has mostly been applied in supervised settings and achieved limited gains. In this work, we propose to apply data augmentation to unlabeled data in a semi-supervised learning setting. Our method, named Unsupervised Data Augmentation or UDA, encourages the model predictions to be consistent between an unlabeled example and an augmented unlabeled example. Unlike previous methods that use random noise such as Gaussian noise or dropout noise, UDA has a small twist in that it makes use of harder and more realistic noise generated by state-of-the-art data augmentation methods. This small twist leads to substantial improvements on six language tasks and three vision tasks even when the labeled set is extremely small. For example, on the IMDb text classiﬁcation dataset, with only 20 labeled examples, UDA outperforms the state-of-the-art model trained on 25,000 labeled examples. On standard semi-supervised learning benchmarks, CIFAR-10 with 4,000 examples and SVHN with 1,000 examples, UDA outperforms all previous approaches and reduces more than 30% of the error rates of state-of-the-art methods: going from 7.66% to 5.27% and from 3.53% to 2.46% respectively. UDA also works well on datasets that have a lot of labeled data. For example, on ImageNet, with 1.3M extra unlabeled data, UDA improves the top-1/top-5 accuracy from 78.28/94.36% to 79.04/94.45% when compared to AutoAugment.
Endoplasmic Reticulum Stress-induced Upregulation of STARD1 Promotes Acetaminophen-induced Acute Liver Failure.

BACKGROUND & AIMS Acetaminophen overdose is a major cause of acute liver failure (ALF). Mitochondrial SH3BP5 (also called SAB) and phosphorylation of JNK mediate the hepatotoxic effects of acetaminophen. We investigated the involvement of steroidogenic acute regulatory protein (STARD1), a mitochondrial cholesterol transporter, in this process and sensitization by valproic acid (VPA), which depletes glutathione and stimulates steroidogenesis. METHODS Non-fasted C57BL/6J mice (control) and mice with liver-specific deletion of STARD1 (Stard1ΔHep), (SabΔHep), or JNK1 and JNK2 (Jnk1+2ΔHep) were given VPA with or without acetaminophen. Liver tissues were collected and analyzed by histology and immunohistochemistry and for SH3BP5 acetaminophen metabolism, endoplasmic reticulum (ER) stress, and mitochondrial function. Adult human hepatocytes were transplanted into FRGN mice to create mice with humanized livers. RESULTS Administration of VPA before administration of acetaminophen increased the severity of liver damage in control mice. The combination of VPA and acetaminophen increased expression of CYP2E1, formation of NAPQI protein adducts, and depletion of glutathione from liver tissues of control mice, resulting in ER stress and the upregulation of STARD1. Livers from control mice given VPA and acetaminophen accumulated cholesterol in the mitochondria and had sustained mitochondrial depletion of glutathione and mitochondrial dysfunction. Inhibition of ER stress, by administration of tauroursodeoxycholic acid to control mice, prevented upregulation of STARD1 in liver and protected the mice from hepatoxicity following administration of VPA and acetaminophen. Administration of N-acetylcysteine to control mice prevented VPA- and acetaminophen-induced ER stress and liver injury. Stard1ΔHep mice were resistant to induction of ALF by VPA and acetaminophen, despite increased mitochondrial levels of glutathione and phosphorylated JNK; we made similar observations in fasted Stard1ΔHep mice given acetaminophen alone. SabΔHep mice or Jnk1+2ΔHep mice did not develop ALF following administration of VPA and acetaminophen. The ability of VPA to increase the severity of acetaminophen-induced liver damage was observed in FRGN mice with humanized liver. CONCLUSIONS In studies of mice, we found that upregulation of STARD1 following ER stress mediates acetaminophen hepatoxicity via SH3BP5 and phosphorylation of JNK1 and JNK2.
Deep Fitting Degree Scoring Network for Monocular 3D Object Detection

In this paper, we propose to learn a deep fitting degree scoring network for monocular 3D object detection, which aims to score fitting degree between proposals and object conclusively. Different from most existing monocular frameworks which use tight constraint to get 3D location, our approach achieves high-precision localization through measuring the visual fitting degree between the projected 3D proposals and the object. We first regress the dimension and orientation of the object using an anchor-based method so that a suitable 3D proposal can be constructed. We propose FQNet, which can infer the 3D IoU between the 3D proposals and the object solely based on 2D cues. Therefore, during the detection process, we sample a large number of candidates in the 3D space and project these 3D bounding boxes on 2D image individually. The best candidate can be picked out by simply exploring the spatial overlap between proposals and the object, in the form of the output 3D IoU score of FQNet. Experiments on the KITTI dataset demonstrate the effectiveness of our framework.
Picophytoplankton size and biomass around equatorial eastern Indian Ocean

The cellular size and biomass of picophytoplankton were studied by flow cytometer during spring monsoon (March–May of 2015) in equatorial eastern Indian Ocean. We established an empirical relationship between forward scatter and cellular size to address the size and biomass of picophytoplankton. Results indicated that mean cell diameter of Prochlorococcus (0.60 μm) was the smallest, and then followed by Synechococcus (0.98 μm) and picoeukaryotic phytoplankton (1.05 μm). Thereafter, the biomass converted by abundance reached 0.64 μg·C·L−1 for Prochlorococcus, 0.34 μg·C·L−1 for Synechococcus, and 0.20 μg·C·L−1 for picoeukaryotic phytoplankton. Additionally, the distinct biomass contribution of picophytoplankton appeared to be affected by abundance, but not changes in cellular size. Vertically, the cellular sizes of picophytoplankton were remarkably small in upper waters, which was predominantly controlled by the nutrient availability. In contrast, they were larger in deeper waters, which was primarily attributed to the combined effects of low temperature and reduced light availability. Spatially, under the influence of high nutrient concentration induced by the different circulations and coastal upwelling, slightly high carbon biomass of picophytoplankton was observed around the coastal zones of Sri Lanka island and Sumatra, as well as the southern Bay of Bengal.
Blended Matching Pursuit

Matching pursuit algorithms are an important class of algorithms in signal processing and machine learning. We present a blended matching pursuit algorithm, combining coordinate descent-like steps with stronger gradient descent steps, for minimizing a smooth convex function over a linear space spanned by a set of atoms. We derive sublinear to linear convergence rates according to the smoothness and sharpness orders of the function and demonstrate computational superiority of our approach. In particular, we derive linear rates for a wide class of non-strongly convex functions, and we demonstrate in experiments that our algorithm enjoys very fast rates of convergence and wall-clock speed while maintaining a sparsity of iterates very comparable to that of the (much slower) orthogonal matching pursuit.
β-catenin nuclear translocation induced by HIF-1α overexpression leads to the radioresistance of prostate cancer

Hypoxia-inducible factor-1α (HIF-1α) is known to play crucial roles in tumor radioresistance; however, the molecular mechanisms responsible for the promotion of tumor radioresistance by HIF-1α remain unclear. β-catenin is known to be involved in the metastatic potential of prostate cancer (PCa). In this study, to investigate the role of HIF-1α and β-catenin in the radioresistance of PCa, two PCa cell lines, LNCaP and C4-2B, were grouped as follows: Negative control (no treatment), HIF-1α overexpression group (transfected with HIF-1α overexpression plasmid) and β-catenin silenced group (transfected with HIF-1α plasmids and β-catenin-shRNA). Cell proliferation, cell cycle, cell invasion and radiosensitivity were examined under normal or hypoxic conditions. In addition, radiosensitivity was examined in two mouse PCa models (the LNCaP orthotopic BALB/c-nu mice model and the C4-2B subcutaneous SCID mice model). Our results revealed that in both the LNCaP and C4-2B cells, transfection with HIF-1α overexpression plasmid led to an enhanced β-catenin nuclear translocation, while β-catenin silencing inhibited β-catenin nuclear translocation. The enhanced β-catenin nuclear translocation induced by HIF-1α overexpression resulted in an enhanced cell proliferation and cell invasion, an altered cell cycle distribution, decreased apoptosis, and improved non-homologous end joining (NHEJ) repair under normal and irradiation conditions. Similar results were observed in the animal models. HIF-1α overexpression enhanced β-catenin nuclear translocation, which led to the activation of the β-catenin/NHEJ signaling pathway and increased cell proliferation, cell invasion and DNA repair. These results thus suggest that HIF-1α overexpression promotes the radioresistance of PCa cells.