Miracle-dz/UniFAR-FTUs huggingface dataset:
How Should Pancreas Transplant Rejection be Treated?

INTRODUCTION Limited published data exists to guide the treatment of pancreas transplant rejection. METHODS We reviewed the treatment and outcomes of 158 1 episodes of biopsy-proven pancreas rejection between 01/01/1997 and 12/31/2016. Within each Banff grade of rejection, we compared response rates and long-term outcomes with steroids alone versus steroids plus ATG. RESULTS Of 158 pancreas recipients with rejection, 65 were treated with steroids alone. 83 % of patients with grade I, 60 % with grade II and 33.33 % with grade III rejection responded to treatment with steroids alone. 93 patients were treated with steroids plus ATG. The response rates were 69 % in grade I, 76% in grade II and 73% in grade III. Response rates and graft survival were not different with grade I rejection treated with steroids alone versus steroids plus ATG. However, response rates and graft survival were significantly better with grade III rejection treated with the addition of ATG, and graft survival rates were significantly better with grade II rejection treated with the addition of ATG. CONCLUSION Grade I pancreas rejection can usually be successfully treated with steroids alone, while grade II and III rejection should usually be treated with steroids plus ATG, as the addition of ATG improves both response rates and graft survival.
Real time hand shape recognition using pipe-line image processor

This paper describes a new hand shape recognition method for man-machine interfaces using a pipeline image process. The basic strategy is to use simple but effective real time dynamical image processing to enhance the reliability of hand shape recognition since motion between frames is minimized. The algorithm for a noncontact-type hand shape recognizer has been developed for incorporation into a virtual reality environment. <<ETX>>
A Survey on Web Usage Mining Techniques

As the size of web increases along with number of users, it is very much essential for the website owners to better understand their customers so that they can provide better service, and also enhance the quality of the website. To achieve this they depend on the web access log files. Users’ accesses are recorded in web logs. Because of the tremendous usage of web, the web log files are growing at a faster rate and the size is becoming huge. The web access log files can be mined to extract interesting pattern so that the user behaviour can be understood. Web data mining is the application of data mining techniques in web data. Web Usage Mining (WUM) applies mining techniques in log data to extract the behaviour of users which is used in various applications like personalized services, adaptive web sites, customer profiling, pre-fetching, creating attractive web sites etc. WUM consists of three phases pre-processing, pattern discovery and pattern analysis. For discovering patterns sessions are to be constructed efficiently. This research paper gives analysis of web usage methods including preprocessing stages used in web mining.
Essential Oils for the Treatment of Herpes Simplex Virus Infections

Infections with herpes simplex virus type (HSV)-1 and HSV-2 are distributed worldwide. Although standard therapies with acyclovir and other synthetic drugs are available, the safety and efficacy of these drugs are limited due to the development of drug resistance and adverse side effects. The literature on essential oils and isolated compounds was reviewed regarding their antiviral activities against HSV-1 and HSV-2. The present overview aims to review experimental data and clinical trials focusing on the antiviral activity of selected essential oils and isolated oil components. HSV was found to be susceptible to many essential oils and their constituents. Whereas some essential oils and compounds exhibit direct virucidal activity or inhibit intracellular replication, many essential oils and compounds interact with HSV particles thereby inhibiting cell adsorption. Ayclovir-resistant HSV strains are also susceptible to essential oils since their mode of action is different from the synthetic drug. There are numerous publications on the antiherpetic activity of essential oils and their isolated active compounds. This field of research is still growing, and more clinical trials are required to explore the full potential of different essential oils for the topical treatment of herpetic infections.
Highlighting relationships between heterogeneous biological data through graphical displays based on regularized canonical correlation analysis

Biological data produced by high throughput technologies are becoming more and more abundant and are arousing many statistical questions. This paper addresses one of them; when gene expression data are jointly observed with other variables with the purpose of highlighting significant relationships between gene expression and these other variables. One relevant statistical method to explore these relationships is Canonical Correlation Analysis (CCA). Unfortunately, in the context of postgenomic data, the number of variables (gene expressions) is usually greater than the number of units (samples) and CCA cannot be directly performed: a regularized version is required. We applied regularized CCA on data sets from two different studies and show that its interpretation evidences both previously validated relationships and new hypothesis. From the first data sets (nutrigenomic study), we generated interesting hypothesis on the transcription factor pathways potentially linking hepatic fatty acids and gene expression. From the second data sets (pharmacogenomic study on the NCI-60 cancer cell line panel), we identified new ABC transporter candidate substrates which relevancy is illustrated by the concomitant identification of several known substrates. In conclusion, the use of regularized CCA is likely to be relevant to a number and a variety of biological experiments involving the generation of high throughput data. We demonstrated here its ability to enhance the range of relevant conclusions that can be drawn from these relatively expensive experiments.
Effect of Fasting on Choroidal Thickness and Its Diurnal Variation

We read with interest the article by Uyar et al. evaluating the effect of fasting on choroidal thickness (CT) and its diurnal variation. The authors reported that fasting and dehydration caused a reduction of CT and increased diurnal variation of CT. These findings are interesting because they elucidate the roles that the choroid plays in normal physiology and ocular diseases, the study of which will be facilitated by the increased scanning depth and width available with swept-source OCT devices. An important consideration when comparing CT between different groups of patients is the topographic variation of the choroid. The choroid is a complex, threedimensional structure comprising an anastomosing network of blood vessels. As several studies had already reported significant variation of mean CT at different macular regions, it will be useful to evaluate differences in mean CT between different groups in various subfields of the Early Treatment Diabetic Retinopathy Study (ETDRS) grid compared with single point thickness measurements along horizontal and vertical OCT B-scans. In this study, point measurements were made at three locations (subfoveal, 1500 mm nasal and temporal to the fovea), at which the magnitude of CT diurnal variation ranged from 3.78 μm to 14.76 μm. It will be interesting to observe variations in various ETDRS sectors in this cohort. In other papers, the difference between the maximum and minimum choroidal thickness exceeded 30 μm. In addition, a sub-analysis of subjects with thicker choroids (defined as ≥ 400 μm) in one paper, demonstrated that the mean amplitude was even larger (43.1 μm) with a maximum of 59 μm. Uyar et al. reported using image registration and tracking. This, in addition to diurnal variation of CT, is an important consideration in longitudinal studies of optical coherence tomography (OCT) scans because of the topographic variation of choroidal thickness. A small change of the OCT scan position may result in changes in CT that may appear to be real. Image registration and tracking will allow subsequent OCT scans to be performed at the same location. Another important consideration regarding the manual CT measurements is intra-observer and inter-observer variability. A previous study demonstrated that a difference of more than 32 μm was likely to represent a real difference in subfoveal CT in healthy eyes. Although Uyar et al. reported a high intraand inter-observer repeatability of CT, the magnitude of diurnal variation reported in their paper ranged from 3.78 μm to 14.76 μm. It is possible that the diurnal variation of CT observed may be affected by variability in CT measurements. In summary, we congratulate the authors on their paper, which increases our understanding of the choroid and its diurnal variation.
Urine albumin and serum uric acid are important determinants of serum 25 hydroxyvitamin D level in pre-dialysis chronic kidney disease patients

Abstract Low serum 25 hydroxyvitamin D (25 OH D) is common among chronic kidney disease (CKD) patients. This cross-sectional study is looking for the different factors associated with serum 25 OH D among pre-dialysis CKD. 1624 adult stage 3–5 CKD patients were studied beside 200 normal control subjects. All candidates were tested for body mass index (BMI), estimated glomerular filtration rate (eGFR), calcium (Ca), phosphorus (P), parathormone (PTH), 25 OH D, albumin, and uric acid (UA), and urine albumin/creatinine ratio (ACR). Multivariate linear regression analysis was done to determine predictors of 25 OH D. 98.6% of CKD patients have inadequate level of 25 OH D vs 48% of normal subjects. Serum 25 OH D was significantly lower in CKD patients (mean ± S.D = 16.54 ± 5.8 vs 37.79 ± 3.58 ng/mL for CKD vs control group respectively, p < .001). Serum level of 25 OH D has significant positive correlation with Ca (r = 0.337, p < .001), and significant negative correlation with P, PTH, UA, and ACR (r = −0.440, −0. 679, −0.724, and −0.781respectively, p < .001 in all). The independent predictors of 25 OH D were Ca, P, UA, PTH, and ACR (R square = 0.7, β = −0.087, −0.226, −0.313, −0.253, and −0.33 respectively, p < .001 in all). In conclusion, pre-dialysis CKD patients frequently suffer low 25 OH D. Among the different abnormalities related to CKD, urine albumin excretion rate and UA are the most important predictors of 25 OH D in these patients.
QseC Signaling in the Outbreak O104:H4 Escherichia coli Strain Combines Multiple Factors during Infection

EAEC is a remarkable etiologic agent of acute and persistent diarrhea worldwide. The isolates harbor specific subsets of virulence genes and their pathogenesis needs to be better understood. Chemical signaling via histidine kinase sensor QseC has been shown as a potential target to elucidate the orchestration of the regulatory cascade of virulence factors. ABSTRACT Enteroaggregative Escherichia coli (EAEC) from the O104:H4 specific serotype caused a large outbreak of bloody diarrhea with some complicated cases of hemolytic-uremic syndrome (HUS) in Europe in 2011. The outbreak strain consisted in an EAEC capable to produce the Shiga toxin (Stx) subtype 2a, a characteristic from enterohemorrhagic E. coli. QseBC two-component system detects AI-3/Epi/NE and mediates the chemical signaling between pathogen and mammalian host. This system coordinates a cascade of virulence genes expression in important human enteropathogens. The blocking of QseC of EAEC C227-11 (Stx+) strain by N-phenyl-4-{[(phenylamino) thioxomethyl]amino}-benzenesulfonamide (also known as LED209) in vivo demonstrated a lower efficiency of colonization. The periplasmic protein VisP, which is related to survival mechanisms in a colitis model of infection, bacterial membrane maintenance, and stress resistance, here presented high levels of expression during the initial infection within the host. Under acid stress conditions, visP expression levels were differentiated in an Stx-dependent way. Together, these results emphasize the important role of VisP and the histidine kinase sensor QseC in the C227-11 (Stx+) outbreak strain for the establishment of the infectious niche process in the C57BL/6 mouse model and of LED209 as a promising antivirulence drug strategy against these enteric pathogens. IMPORTANCE EAEC is a remarkable etiologic agent of acute and persistent diarrhea worldwide. The isolates harbor specific subsets of virulence genes and their pathogenesis needs to be better understood. Chemical signaling via histidine kinase sensor QseC has been shown as a potential target to elucidate the orchestration of the regulatory cascade of virulence factors.
Plant functional traits and climate influence drought intensification and land–atmosphere feedbacks

Significance Terrestrial vegetation can affect climate extremes such as severe drought by mediating fluxes of energy and water from the land surface to the atmosphere. Declines in plant transpiration due to low soil moisture during drought, which is fundamentally determined by plant functional traits, can intensify drought, but this process is not well understood. We examine ecosystem-level eddy flux and satellite remote-sensing estimates of drought intensification and find that both mean climate and plant functional traits, particularly those related to water transport, explain drought intensification patterns across sites. Our findings highlight that plant physiology and water transport functional traits are likely crucial to include in earth system models for capturing land–atmosphere feedbacks and climate extremes. The fluxes of energy, water, and carbon from terrestrial ecosystems influence the atmosphere. Land–atmosphere feedbacks can intensify extreme climate events like severe droughts and heatwaves because low soil moisture decreases both evaporation and plant transpiration and increases local temperature. Here, we combine data from a network of temperate and boreal eddy covariance towers, satellite data, plant trait datasets, and a mechanistic vegetation model to diagnose the controls of soil moisture feedbacks to drought. We find that climate and plant functional traits, particularly those related to maximum leaf gas exchange rate and water transport through the plant hydraulic continuum, jointly affect drought intensification. Our results reveal that plant physiological traits directly affect drought intensification and indicate that inclusion of plant hydraulic transport mechanisms in models may be critical for accurately simulating land–atmosphere feedbacks and climate extremes under climate change.
Life Imprint and meaning reconstruction for young people who have experienced the death of a family member from cancer

The death of a parent or sibling leaves an indelible mark on a young person. Stressful and traumatic, it impacts their psychosocial and physical well‐being. Support during bereavement can be limited, with young people (YP) feeling isolated from peers, and needing support from friends, family and peers in similar situations. To support bereaved YP (12‐25 years) cope adaptively with the death of a parent or sibling from cancer, we developed a manualised residential therapeutic and recreational programme, Good Grief*. Good Grief is informed by the Dual Process Model of Coping with Bereavement, which proposes that adaptive grief coping involves successful transitions between loss and restoration, whereby individuals can revise life narratives following bereavement to re‐engage with their lives. The programme utilises a constructivist framework of Narrative Therapy, whereby meaning reconstruction is central to grief and the narratives that individuals create influence experiences, relationships, actions, and goals. The 3‐day programme has four 90‐minute recreational and six 90‐minute therapeutic group sessions, enabling YP to engage in peer support, receive psychosocial support, develop coping skills, and experience “time‐out” from their grief. The Life Imprint session is a key therapeutic session in Good Grief conceptualised by YP reading and reflecting on a structured letter about the shared values between them and their deceased family member. The Life Imprint session is a novel intervention developed by the authors and adapted from Neimeyer's therapeutic practice of
The role of sleep and wakefulness in myelin plasticity

Myelin plasticity is gaining increasing recognition as an essential partner to synaptic plasticity, which mediates experience‐dependent brain structure and function. However, how neural activity induces adaptive myelination and which mechanisms are involved remain open questions. More than two decades of transcriptomic studies in rodents have revealed that hundreds of brain transcripts change their expression in relation to the sleep–wake cycle. These studies consistently report upregulation of myelin‐related genes during sleep, suggesting that sleep represents a window of opportunity during which myelination occurs. In this review, we summarize recent molecular and morphological studies detailing the dependence of myelin dynamics after sleep, wake, and chronic sleep loss, a condition that can affect myelin substantially. We present novel data about the effects of sleep loss on the node of Ranvier length and provide a hypothetical mechanism through which myelin changes in response to sleep loss. Finally, we discuss the current findings in humans, which appear to confirm the important role of sleep in promoting white matter integrity.
Emotion Analysis of Tourists Based on Domain Ontology

The big data of tourism has exploded with the rapid development of social media, providing a new data source for the emotion analysis of tourism. Based on online comments, this paper proposes an emotion analysis model that combines tourism domain ontology and semantic-based method to mine the fine-grained emotion of tourists and designs specific formulas to quantify the emotion of tourists. Finally, the Palace Museum is used as an example to verify the validity of the model. The analysis results show that: 1) Tourists pay more attention to the attributes such as "scenery", "tourist flow", "ticket", etc. in their travel activities. 2) The emotional score of the attributes such as "lodging environment", "scenery", "culture", "environment quality", etc. are higher, but the attributes such as "safety", "tourist flow", "toilet" and cost-related attributes are lower. The main reasons are: "low security", "massive tourists", "less and small toilets" and "high costs". 3) Due to the excessive number of tourists during the holiday, which leads poor travel experience to the tourists, the emotional score of tourists are lower in the 5th, 7th, 8th and 10th months. The analysis results can provide reference for tourists' travel decisions and the development and optimization of tourism.
ElasticPipe: An Efficient and Dynamic Model-Parallel Solution to DNN Training

Traditional deep neural network (DNN) training is executed with data parallelism, which suffers from significant communication overheads and GPU memory consumption. Considering this, recent pioneering works have attempted to train DNN with model parallelism. However, model partition remains as a major concern and a static partition fails to adapt to the ever-changing computation environment of the cloud cluster. This paper proposes ElasticPipe, which trains the neural network based on pipe-based model parallelism. Unlike data-parallel solutions, each node in ElasticPipe only holds part of the whole model, leading to much lower cost of communication and GPU memory. More importantly, ElasticPipe is able to dynamically tune the workload distribution among different nodes, so that it can mitigate the common straggler effect in cloud environment. Our primary experiment shows, compared to the data-parallel baselines, ElasticPipe can reduce the training time by up to 89.03% without considering straggler effect, and by up to 76.72% with the existence of stragglers. Besides, ElasticPipe also outperforms its static counterpart by up to 28.81% in training performance when stragglers are involved.
Length Spectrum Theory, Non-backtracking Cycles, and Two Graph Analysis Tasks

Two basic tasks in graph analysis are: (1) computing the distance between two graphs and (2) embedding of the graph elements (i.e., nodes or links) into a lower-dimensional space. The former task has numerous applications from k-nearest neighbor search, to clustering a collection of graphs, to transfer learning. Unfortunately, there exists no canonical way of computing the distance between two finite graphs because the dissimilarity problem is ill-defined. Despite this fact, the relevant literature contains many methods for measuring graph distance with different heuristics, computational efficiency, interpretability, and theoretical soundness [1]. We introduce a graph distance, called the Non-Backtracking Spectral Distance (NBD), which is theoretically sound and interpretable. NBD is based on a mathematical construct from algebraic topology (in particular, homotopy) called the length spectrum. The length spectrum of a graph is a function defined on the graph's first homotopy group (a.k.a. the fundamental group); and it uniquely characterizes a graph's 2-core up to isometry [2]. 1 Thus, if two graphs have the same length spectra, then their 2-cores are isometric. We show the relationship between a graph's length spectrum and its non-backtracking cycles; and present a method based on computing the eigenvalues of a graph's non-backtracking matrix. For the second task (i.e., graph embedding), most existing methods are stochastic and depend on black-box models such as deep networks. Both of these characteristics make their output difficult to analyze. We propose the Non-Backtracking Embedding Dimensions (NBED) for finding a graph embedding in low-dimensional space by computing the eigenvectors of the non-backtracking matrix. Both NBD and NBED are interpretable in terms of features of complex networks such as hubs, triangles, edge centrality, and communities. We showcase the usefulness of both NBD and NBED in experiments on synthetic and real-world networks.
Privacy Analysis on Microblogging Online Social Networks

Online Social Networks (OSNs) incorporate different forms of interactive communication, including microblogging services, multimedia sharing, business networking, and so on. They allow users to create profiles, connect with friends, and share their daily activities and thoughts. However, this ease of use of OSNs comes with a cost in terms of users’ privacy and security. The big amount of personal data shared in the users’ profiles or correlated from their activities can be stored, processed, and sold for advertisement or statistical purposes. It attracts also malicious users who can collect and exploit the data and target different types of attacks. In this article, we review the state of the art of OSNs existing either in the literature or deployed for use. We focus on the OSN systems that offer, but not exclusively, microblogging services. We analyze and evaluate each system based on a set of characteristics, and we compare them based on their usability and the level of protection of privacy and security they provide. This study is a first step toward understanding the security and privacy controls and measuring their level in an OSN.