Miracle-dz/UniFAR-FTUs huggingface dataset:
Management of complicated peptic ulcer disease.

Our understanding of the pathophysiological features of peptic ulcer disease has rapidly evolved during the last century. Early understanding of gastric physiologic characteristics led to logical and time-tested surgical procedures aimed at acid reduction and a lowering of ulcer recurrence rates. A dramatic shift in treatment occurred with the recognition and growing knowledge of Helicobacter pylori (HP). Where once surgery dominated therapy for ulcer diathesis, medical therapy has now superseded. Just as gastric resection seemed radical to Dr Mayo, thus was medical treatment of peptic ulcer disease similarly approached with skepticism. What was the balance of medical and surgical management of peptic ulcer disease as we entered the 21st century? Complications of peptic ulcer disease requiring operative intervention have remained important. However, the absolute number of procedures performed has significantly diminished in recent years. 1 The reason for the decrease in surgical intervention, both emergent and elective, is multifactorial. Improvements in therapeutic endoscopy, the introduction of effective antacid therapy, and the recognition and treatment of HP infection have all greatly contributed to the successful nonoperative treatment of patients with peptic ulcer disease. 2-5 With respect to complicated ulcer disease, treatment and eradication of HP infection have arguably led to a shift from treating patients operatively to treating them nonoperatively. This changing management scheme has occurred despite a relative paucity of data regarding the incidence and contribution of HP infection to the etiology of complicated peptic ulcers. Indeed, reports in the literature regarding the incidence of HP infection in a surgical cohort have been sparse. From a surgeon's perspective, data relative to HP infection and the classic indications for surgery-perforation, bleeding, and gastric outlet obstruction (GOO)- have until recently been largely inferential based on treatment of those with uncomplicated peptic ulcers. Deviation from traditional surgical management might prove detrimental should other nonoperative modalities be used. The purpose of this discussion is to review the known pathophysiological features of peptic ulcer disease with a focus on those complications encountered by the surgeon.
A placebo-controlled trial of pioglitazone in subjects with nonalcoholic steatohepatitis.

BACKGROUND No pharmacologic therapy has conclusively proved to be effective for the treatment of nonalcoholic steatohepatitis, which is characterized by insulin resistance, steatosis, and necroinflammation with or without centrilobular fibrosis. Pioglitazone is a thiazolidinedione that ameliorates insulin resistance and improves glucose and lipid metabolism in type 2 diabetes mellitus. METHODS We randomly assigned 55 patients with impaired glucose tolerance or type 2 diabetes and liver biopsy-confirmed nonalcoholic steatohepatitis to 6 months of treatment with a hypocaloric diet (a reduction of 500 kcal per day in relation to the calculated daily intake required to maintain body weight) plus pioglitazone (45 mg daily) or a hypocaloric diet plus placebo. Before and after treatment, we assessed hepatic histologic features, hepatic fat content by means of magnetic resonance spectroscopy, and glucose turnover during an oral glucose tolerance test ([14C]glucose given with the oral glucose load and [3H]glucose given by intravenous infusion). RESULTS Diet plus pioglitazone, as compared with diet plus placebo, improved glycemic control and glucose tolerance (P<0.001), normalized liver aminotransferase levels as it decreased plasma aspartate aminotransferase levels (by 40% vs. 21%, P=0.04), decreased alanine aminotransferase levels (by 58% vs. 34%, P<0.001), decreased hepatic fat content (by 54% vs. 0%, P<0.001), and increased hepatic insulin sensitivity (by 48% vs. 14%, P=0.008). Administration of pioglitazone, as compared with placebo, was associated with improvement in histologic findings with regard to steatosis (P=0.003), ballooning necrosis (P=0.02), and inflammation (P=0.008). Subjects in the pioglitazone group had a greater reduction in necroinflammation (85% vs. 38%, P=0.001), but the reduction in fibrosis did not differ significantly from that in the placebo group (P=0.08). Fatigue and mild lower-extremity edema developed in one subject who received pioglitazone; no other adverse events were observed. CONCLUSIONS In this proof-of-concept study, the administration of pioglitazone led to metabolic and histologic improvement in subjects with nonalcoholic steatohepatitis. Larger controlled trials of longer duration are warranted to assess the long-term clinical benefit of pioglitazone. (ClinicalTrials.gov number, NCT00227110 [ClinicalTrials.gov] .).
Cannabidiol Inhibits Endocannabinoid Signaling in Autaptic Hippocampal Neurons

Δ9-Tetrahydrocannabinol (THC) and cannabidiol (CBD) are two main cannabinoid constituents of marijuana and hashish. The pharmacology of Δ9-THC has been extensively studied, whereas our understanding of the pharmacology of CBD has remained limited, despite excitement in CBD’s potential role in treating certain pediatric epilepsies and its reputation for attenuating some Δ9-THC–induced effects. It was established early on that CBD binds poorly to the orthosteric site of CB1 or CB2 cannabinoid receptors, and its actions were commonly attributed to other noncannabinoid receptor mechanisms. However, recent evidence suggests that CBD does indeed act at cannabinoid CB1 receptors as a negative allosteric modulator (NAM) of CB1 signaling. By altering the orthosteric signaling of a G protein–coupled receptor, allosteric modulators greatly increase the richness of G protein–coupled receptor pharmacology. We have recently surveyed candidate CB1 NAMs in autaptic hippocampal neurons, a well-characterized neuronal model of endogenous cannabinoid signaling, and have now tested CBD in this model. We find that although CBD has no direct effect on excitatory transmission, it does inhibit two forms of endogenous cannabinoid-mediated retrograde synaptic plasticity: depolarization-induced suppression of excitation and metabotropic suppression of excitation, while not affecting signaling via GABA-B receptors. These results are consistent with the recently described NAM activity of CBD and suggest interesting possible mechanisms for CBD’s therapeutic actions.
Macrophage Migration Inhibitory Factor Promotes Proliferation and Neuronal Differentiation of Neural Stem/Precursor Cells through Wnt/β-Catenin Signal Pathway

Macrophage migration inhibitory factor (MIF) is a highly conserved and evolutionarily ancient mediator with pleiotropic effects. Recent studies demonstrated that the receptors of MIF, including CD44, CXCR2, CXCR4 and CD74, are expressed in the neural stem/progenitor cells (NSPCs). The potential regulatory effect of MIF on NSPCs proliferation and neuronal differentiation, however, is largely unknown. Here, we investigated the effect of MIF on NSPC proliferation and neuronal differentiation, and further examined the signal pathway by which MIF transduced these signal effects in mouse NSPCs in vitro. The results showed that both Ki67-positive cells and neurosphere volumes were increased in a dose-dependent manner following MIF treatment. Furthermore, the expression of nuclear β-catenin was significantly stronger in MIF-stimulated groups than that in control groups. Conversely, administration of IWR-1, the inhibitor of Wnt/β-catenin pathway, significantly inhibited the proliferative effect of MIF on NSPCs. Immunostaining and Western blot further indicated that doublecortin (DCX) and Tuj 1, two neuronal markers, were evidently increased with MIF stimulation during NSPC differentiation, and there were more Tuj1-positive cells migrated out from neurospheres in MIF-stimulated groups than those in control groups. During NSPC differentiation, MIF increased the activity of β-galactosidase that responds to Wnt/β-catenin signaling. Wnt1 and β-catenin proteins were also up-regulated with MIF stimulation. Moreover, the expression of DCX and Tuj 1 was inhibited significantly by IWR-1. Taken together, the present study indicated that MIF enhances NSPC proliferation and promotes the neuronal differentiation, by activating Wnt/β-catenin signal pathway. The interaction between MIF and Wnt/β-catenin signal pathway may play an important role in modulating NSPC renewal and fate during brain development.
An unsupervised automatic segmentation algorithm for breast tissue classification of dedicated breast computed tomography images

Purpose To develop and evaluate a new automatic classification algorithm to identify voxels containing skin, vasculature, adipose, and fibroglandular tissue in dedicated breast CT images. Methods The proposed algorithm combines intensity‐ and region‐based segmentation methods with energy minimizing splines and unsupervised data mining approaches for classifying and segmenting the different tissue types. Breast skin segmentation is achieved by a region‐growing method which uses constraints from the previously extracted skin centerline to add robustness to the model and to reduce the false positive rate. An energy minimizing active contour model is then used to classify adipose tissue voxels by including gradient flow and region‐based features. Finally, blood vessels are separated from fibroglandular tissue by a k‐means clustering algorithm based on automatically extracted shape‐based features. To evaluate the accuracy of the algorithm, two sets of 15 different patient breast CT scans, each acquired with different breast CT systems and acquisition settings were obtained. Three slices from each scan were manually segmented under the supervision of an experienced breast radiologist and considered the gold standard. Comparisons with manual segmentation were quantified using five similarity metrics: Dice similarity coefficient (DSC), sensitivity, conformity coefficient, and two Hausdorff distance measures. To evaluate the robustness to image noise, the segmentation was repeated after separately adding Gaussian noise with increasing standard deviation (in four steps, from 0.01 to 0.04) to an additional 15 slices from the first dataset. In addition, to evaluate vasculature classification, three different pre‐ and postcontrast injection patient breast CT images were classified and compared. Finally, DSC was also used for quantitative comparisons with previously proposed approaches for breast CT tissue classification using 10 images from the first dataset. Results The algorithm showed a high accuracy in classifying the different tissue types for both breast CT systems, with an average DSC of 95% and 90% for the first and second image dataset, respectively. Furthermore, it demonstrated to be robust to image noise with a robustness to image noise of 85%, 83%, 79%, and 71% for the images corrupted with the four increasing noise levels. Previous methods for breast tissues classification resulted, for the tested dataset, in an average global DSC of 87%, while our approach resulted in a global average DSC of 94.5%. Conclusions The proposed algorithm resulted in accurate and robust breast tissue classification, with no prior training or threshold setting. Potential applications include breast density quantification and tissue pattern characterization (both biomarkers of cancer development), simulation‐based radiation dose analysis, and patient data‐based phantom design, which could be used for further breast imaging research.
Symposium on S. Butterfill and I. Apperly, "How to Construct a Minimal Theory of Mind"

What could someone represent that would enable her to track, at least within limits, others' perceptions, knowledge states and beliefs including false beliefs? An obvious possibility is that she might represent these very attitudes as such. It is sometimes tacitly or explicitly assumed that this is the only possible answer. However, we argue that several recent discoveries in developmental, cognitive, and comparative psychology indicate the need for other, less obvious possibilities. Our aim is to meet this need by describing the construction of a minimal theory of mind. Minimal theory of mind is rich enough to explain systematic success on tasks held to be acid tests for theory of mind cognition including many false belief tasks. Yet minimal theory of mind does not require representing propositional attitudes, or any other kind of representation, as such. Minimal theory of mind may be what enables those with limited cognitive resources or little conceptual sophistication, such as infants, chimpanzees, scrub-jays and human adults under load, to track others' perceptions, knowledge states and beliefs.
Colour polymorphism in birds: causes and functions

We studied polymorphism in all species of birds that are presently known to show intraspecific variation in plumage colour. At least three main mechanisms have been put forward to explain the maintenance of polymorphism: apostatic, disruptive and sexual selection. All of them make partly different predictions. Our aims were to investigate evolutionary causes and adaptive functions of colour polymorphism by taking into account a number of ecological and morphological features of polymorphic species. Overall, we found 334 species showing colour polymorphism, which is 3.5% of all bird species. The occurrence of colour polymorphism was very high in Strigiformes, Ciconiiformes, Cuculiformes and Galliformes. Phylogenetically corrected analysis using independent contrasts revealed that colour polymorphism was maximally expressed in species showing a daily activity rhythm extended to day/night, living in both open and closed habitats. All these findings support the hypothesis that colour polymorphism probably evolved under selective pressures linked to bird detectability as affected by variable light conditions during activity period. Thus, we conclude that selective agents may be prey, predators and competitors, and that colour polymorphism in birds may be maintained by disruptive selection.
Modeling LIDAR Detection of Biological Aerosols to Determine Optimum Implementation Strategy

This report summarizes work performed for a larger multi-laboratory project named the Background Interferent Measurement and Standards project. While originally tasked to develop algorithms to optimize biological warfare agent detection using UV fluorescence LIDAR, the current uncertainties in the reported fluorescence profiles and cross sections the development of any meaningful models. It was decided that a better approach would be to model the wavelength-dependent elastic backscattering from a number of ambient background aerosol types, and compare this with that generated from representative sporulated and vegetative bacterial systems. Calculations in this report show that a 266, 355, 532 and 1064 nm elastic backscatter LIDAR experiment will allow an operator to immediately recognize when sulfate, VOC-based or road dust (silicate) aerosols are approaching, independent of humidity changes. It will be more difficult to distinguish soot aerosols from biological aerosols, or vegetative bacteria from sporulated bacteria. In these latter cases, the elastic scattering data will most likely have to be combined with UV fluorescence data to enable a more robust categorization.
The origin and evolution of language: a plausible, strong-AI account

Framework In this chapter I show in outline how human language as we know it could have evolved incrementally from mental capacities it is reasonable to attribute to lower primates and other mammals. I do so within the framework of a formal computational theory of language understanding (Hobbs et al. , 1993). In the first section I describe some of the key elements in the theory, especially as it relates to the evolution of linguistic capabilities. In the next two sections I describe plausible incremental paths to two key aspects of language − meaning and syntax. In the final section I discuss various considerations of the time course of these processes. Strong AI It is desirable for psychology to provide a reduction in principle of intelligent, or intentional, behavior to neurophysiology. Because of the extreme complexity of the human brain, more than the sketchiest account is not likely to be possible in the near future. Nevertheless, the central metaphor of cognitive science, “The brain is a computer,” gives us hope. Prior to the computer metaphor, we had no idea of what could possibly be the bridge between beliefs and ion transport. Now we have an idea. In the long history of inquiry into the nature of mind, the computer metaphor gives us, for the first time, the promise of linking the entities and processes of intentional psychology to the underlying biological processes of neurons, and hence to physical processes.
A Robust Resolution-Enhancement Scheme for Video Transmission Over Mobile Ad-Hoc Networks

Historically, Error-Resilient (ER) video transmission and Super-Resolution (SR) image reconstruction techniques have evolved separately. In this paper, we propose a coordinated application of ER and SR to enhance the resolution of image transmitted over mobile ad-hoc networks. In order to combat error propagation, a flexible multiple description coding method based on shifted 3-D SPIHT (3-D Set Partitioning In Hierarchical Trees) algorithm is presented to generate variable independent descriptions (substreams) according to the network condition. And then, a novel unequal error protection strategy based on the priority level is provided to assign a higher level of error protection to more important parts of bitstream. Moreover, a robust SR algorithm is proposed in the presence of different kinds of packet loss rate to enhance the image resolution. Experimental results indicate that the proposed robust resolution-enhancement scheme outperforms the competing methods from the aspects of PSNR (Peak-Signal-to-Noise Ratio) and visual quality under different packet loss rates.
Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions.
Frequency of Congenital Heart Diseases in Prelingual Sensory-Neural Deaf Children

Introduction: Hearing impairment is the most frequent sensorial congenital defect in newborns and has increased to 2–4 cases per 1,000 live births. Sensory-neural hearing loss (SNHL) accounts for more than 90% of all hearing loss. This disorder is associated with other congenital disorders such as renal, skeletal, ocular, and cardiac disorders. Given that congenital heart diseases are life-threatening, we decided to study the frequency of congenital heart diseases in children with congenital sensory-neural deafness. Materials and Methods: All children who had undergone cochlear implantation surgery due to SNHL and who had attended our hospital for speech therapy during 2008–2011 were evaluated by Doppler echocardiography. Results: Thirty-one children (15 boys and 16 girls) with a mean age of 55.70 months were examined, and underwent electrocardiography (ECG) and echocardiography. None of the children had any signs of heart problems in their medical records. Most of their heart examinations were normal, one patient had expiratory wheeze, four (12%) had mid-systolic click, and four (12%) had an intensified S1 sound. In echocardiography, 15 children (46%) had mitral valve prolapse (MVP) and two (6%) had minimal mitral regurgitation (MR). Mean ejection fraction (EF) was 69% and the mean fractional shortening (FS) was 38%. Conclusion: This study indicates the need for echocardiography and heart examinations in children with SNHL.
Dunye Guanxinning Improves Acute Myocardial Ischemia-Reperfusion Injury by Inhibiting Neutrophil Infiltration and Caspase-1 Activity

Acute myocardial infarction is the most serious manifestation of cardiovascular disease, and it is a life-threatening condition. Dunye Guanxinning (DG) is a protective traditional Chinese patent herbal medicine with high clinical efficacy and suitable for the treatment of myocardial infarction. However, the mechanism through which it is beneficial is unclear. In this study, we hypothesized that DG improves acute myocardial ischemia-reperfusion injury by inhibiting neutrophil infiltration and caspase-1 activity. We found that DG administration decreased infarct size and cardiomyocyte apoptosis and improved left ventricular ejection fraction, fractional shortening, end-systolic volume index, end-systolic diameter, and carotid arterial blood flow output in rats. DG administration also improved hemorheological parameters, myocardial damage biomarkers, and oxidative stress indexes. The findings showed that DG administration inhibited neutrophil infiltration and reduced the serum interleukin-1 beta (IL-1β) level and myocardial IL-1β maturation. Moreover, DG administration inhibited caspase-1 activity and activated adenosine monophosphate-activated protein kinase (AMPK) phosphorylation in rat hearts. These results suggested that DG administration inhibits inflammasome activity and IL-1β release through the AMPK pathway. Our findings support the clinical efficacy of DG and partially reveal its mechanism, which is beneficial for understanding the therapeutic effects of this protective traditional Chinese patent drug.