Miracle-dz/UniFAR-FTUs huggingface dataset:
Blocking Autophagy Prevents Bortezomib-Induced NF-κB Activation by Reducing I-κBα Degradation in Lymphoma Cells

Here we show that bortezomib induces effective proteasome inhibition and accumulation of poly-ubiquitinated proteins in diffuse large B-cell lymphoma (DLBCL) cells. This leads to induction of endoplasmic reticulum (ER) stress as demonstrated by accumulation of the protein CHOP, as well as autophagy, as demonstrated by accumulation of LC3-II proteins. Our data suggest that recruitment of both ubiquitinated proteins and LC3-II by p62 directs ubiquitinated proteins, including I-κBα, to the autophagosome. Degradation of I-κBα results in increased NF-κB nuclear translocation and transcription activity. Since bortezomib treatment promoted I-κBα phosphorylation, ubiquitination and degradation, this suggests that the route of I-κBα degradation was not via the ubiquitin-proteasome degradation system. The autophagy inhibitor chloroquine (CQ) significantly inhibited bortezomib-induced I-κBα degradation, increased complex formation with NF-κB and reduced NF-κB nuclear translocation and DNA binding activity. Importantly, the combination of proteasome and autophagy inhibitors showed synergy in killing DLBCL cells. In summary, bortezomib-induced autophagy confers relative DLBCL cell drug resistance by eliminating I-κBα. Inhibition of both autophagy and the proteasome has great potential to kill apoptosis-resistant lymphoma cells.
Pressure Boundaries for Implicit Incompressible SPH

Implicit incompressible SPH (IISPH) solves a pressure Poisson equation (PPE). While the solution of the PPE provides pressure at fluid samples, the embedded boundary handling does not compute pressure at boundary samples. Instead, IISPH uses various approximations to remedy this deficiency. In this article, we illustrate the issues of these IISPH approximations. We particularly derive Pressure Boundaries, a novel boundary handling that overcomes previous IISPH issues by the computation of physically meaningful pressure values at boundary samples. This is basically achieved with an extended PPE. We provide a detailed description of the approach that focuses on additional technical challenges due to the incorporation of boundary samples into the PPE. We therefore use volume-centric SPH discretizations instead of typically used density-centric ones. We further analyze the properties of the proposed boundary handling and compare it to the previous IISPH boundary handling. In addition to the fact that the proposed boundary handling provides physically meaningful pressure and pressure gradients at boundary samples, we show further benefits, such as reduced pressure oscillations, improved solver convergence, and larger possible time steps. The memory footprint of fluid samples is reduced and performance gain factors of up to five compared to IISPH are presented.
The rate of visual field change in the ocular hypertension treatment study.

PURPOSE To assess the rate of change of visual field (VF) mean deviation (MD) in the Ocular Hypertension Treatment Study (OHTS). METHODS OHTS data were filtered to exclude eyes that had fewer than 10 reliable VFs or less than 5 years of follow-up or that reached a nonglaucomatous endpoint. The rate of change of MD (MDR) was calculated for each eye. Differences were sought between groups of eyes differing in primary open angle glaucoma (POAG) outcome, how POAG was determined, and original randomization. RESULTS In total, 2609 eyes (1379 participants) met the selection criteria. The mean MDR was -0.08 ± 0.20 dB/y (±SD). POAG eyes (n = 359) had significantly worse MDRs (-0.26 ± 0.36 dB/y) than non-POAG eyes (n = 2250; -0.05 ± 0.14 dB/y; P < 0.001). Eyes that reached POAG endpoints based on only VF change (n = 74; -0.29 ± 0.31 dB/y) or only optic disc change (n = 158; -0.12 ± 0.19 dB/y) had significantly worse MDRs than non-POAG eyes (both P < 0.001). Eyes that reached POAG endpoints for both VF and optic disc change (n = 127) deteriorated more rapidly (-0.42 ± 0.46 dB/y) than eyes showing only VF change (P = 0.017) or only optic disc change (P < 0.001). There was not a significant association between MDR and original OHTS randomization (observe vs. treat, P = 0.168). CONCLUSIONS Eyes that develop POAG have significantly worse MDRs than eyes that do not. Eyes that reached endpoints due to both VF and optic disc change had worse MDRs than eyes displaying change in only one of these. MDR was not significantly associated with randomization, suggesting that MDR may not be the best measure of VF change in early-stage POAG. (ClinicalTrials.gov number, NCT00000125.).
Dairy product consumption is associated with pre-diabetes and newly diagnosed type 2 diabetes in the Lifelines Cohort Study

Abstract Previous studies show associations between dairy product consumption and type 2 diabetes, but only a few studies conducted detailed analyses for a variety of dairy subgroups. Therefore, we examined cross-sectional associations of a broad variety of dairy subgroups with pre-diabetes and newly diagnosed type 2 diabetes (ND-T2DM) among Dutch adults. In total, 112 086 adults without diabetes completed a semi-quantitative FFQ and donated blood. Pre-diabetes was defined as fasting plasma glucose (FPG) between 5·6 and 6·9 mmol/l or HbA1c% of 5·7–6·4 %. ND-T2DM was defined as FPG ≥7·0 mmol/l or HbA1c ≥6·5 %. Logistic regression analyses were conducted by 100 g or serving increase and dairy tertiles (T1ref), while adjusting for demographic, lifestyle and dietary covariates. Median dairy product intake was 324 (interquartile range 227) g/d; 25 549 (23 %) participants had pre-diabetes; and 1305 (1 %) had ND-T2DM. After full adjustment, inverse associations were observed of skimmed dairy (OR100 g 0·98; 95 % CI 0·97, 1·00), fermented dairy (OR100 g 0·98; 95 % CI 0·97, 0·99) and buttermilk (OR150 g 0·97; 95 % CI 0·94, 1·00) with pre-diabetes. Positive associations were observed for full-fat dairy (OR100 g 1·003; 95 % CI 1·01, 1·06), non-fermented dairy products (OR100 g 1·01; 95 % CI 1·00, 1·02) and custard (ORserving/150 g 1·13; 95 % CI 1·03, 1·24) with pre-diabetes. Moreover, full-fat dairy products (ORT3 1·16; 95 % CI 0·99, 1·35), non-fermented dairy products (OR100 g 1·05; 95 % CI 1·01, 1·09) and milk (ORserving/150 g 1·08; 95 % CI 1·02, 1·15) were positively associated with ND-T2DM. In conclusion, our data showed inverse associations of skimmed and fermented dairy products with pre-diabetes. Positive associations were observed for full-fat and non-fermented dairy products with pre-diabetes and ND-T2DM.
Multiple sequence alignment methods

In Chapter 5, we assumed that a reasonable multiple sequence alignment was already known and provided the starting point for constructing a profile HMM. We now look at what a reasonable multiple alignment is, and at ways to construct one automatically from unaligned sequences. Biologists produce high quality multiple sequence alignments by hand using expert knowledge of protein sequence evolution. Importance factors include: specific sorts of columns in alignments, such as highly conserved residues or buried hydrophobic residues; the influence of secondary and tertiary structure; and expected patterns of insertions and deletions. Furthermore, the phylogenetic relationships between sequences dictate constraints on the changes that occur in columns and in the patterns of gaps. Manual multiple alignment is tedious. Automatic multiple sequence alignment methods are a topic of extensive research in computational biology. In general, an automatic method must have a way to assign a score so that better multiple alignments get better scores. One of our goals in probabilistic modeling is to incorporate as many of an expert's evaluation criteria as possible into our scoring procedure. 6.1 What a multiple alignment means In a multiple sequence alignment, homologous residues among a set of sequences are aligned together in columns. Homologous is meant in both the structural and evolutionary sense. Ideally, a column of aligned residues occupy similar three-dimensional structural positions and all diverge from a common ancestral residue. However, except for trivial cases of highly identical sequences, it is not possible to unambiguously identify structurally or evolutionarily homologous positions and create a single correct multiple alignment. Since protein structures also evolve, we do not expect two protein structures with different sequences to be entirely superposable. An evolutionary correct alignment can be even more difficult to infer than a structural alignment. While structural alignment has an independent point of reference (superposition of crystal or NMR structures), the evolutionary history of the residues of a sequence family is not independently known from any source; it must itself be inferred from sequence alignment. Thus, our ability to define a single 'correct' alignment will vary with relatedness of the sequences being aligned. An alignment of very similar sequences will generally be unambiguous, but these alignments are not of great interest to us. For cases of interest, e.g. for a family of proteins sharing perhaps only 30% average pairwise sequence identity, there is no objective way to define an unambiguously correct alignment. We should focus …
Degree of recurrence of generic diffeomorphisms

We study spatial discretizations of dynamical systems: is it possible to recover some dynamical features of a system from numerical simulations? Here, we tackle this issue for the simplest algorithm possible: we compute long segments of orbits with a fixed number of digits. We show that for every $r\ge 1$, the dynamics of the discretizations of a $C^r$ generic conservative diffeomorphism of the torus is very different from that observed in the $C^0$ regularity. The proof of our results involves in particular a local-global formula for discretizations, as well as a study of the corresponding linear case, which uses ideas from the theory of quasicrystals.
Performance Comparison of R-PHY and R-MACPHY Modular Cable Access Network Architectures

Emerging modular cable network architectures distribute some cable headend functions to remote nodes that are located close to the broadcast cable links reaching the cable modems (CMs) in the subscriber homes and businesses. In the remote-PHY (R-PHY) architecture, an R-PHY device conducts the physical layer processing for the analog cable transmissions, while the headend runs the data over cable service interface specification (DOCSIS) medium access control (MAC) for the upstream transmissions of the distributed CMs over the shared cable link. In contrast, in the remote MACPHY (R-MACPHY) architecture, an R-MACPHY device (RMD) conducts both the physical and MAC layer processing. In this paper, we conduct a comprehensive performance comparison of the R-PHY and R-MACPHY architectures. We first develop analytical delay models for the polling-based MAC with gated bandwidth allocation of Poisson traffic in the R-PHY and R-MACPHY architectures. We then conduct extensive simulations to assess the accuracy of the analytical model and to evaluate the delay-throughput performance of the R-PHY and R-MACPHY architectures for a wide range of deployment and operating scenarios. Our evaluations include long converged interconnect network (CIN) distances between remote nodes and headend, bursty self-similar traffic, and double-phase polling to mask long CIN propagation distances. We find that for long CIN distances above 100 miles, the R-MACPHY architecture achieves significantly shorter mean upstream packet delays than the R-PHY architecture, especially for bursty traffic. Our extensive comparative R-PHY and R-MACPHY evaluation can serve as a basis for the planning of modular broadcast cable based access networks.
The course and prognosis of hip complaints in general practice

Background: The general practitioner needs to discriminate complaints with need of specialist care from those that can be managed in primary care. However, no previous research has studied prognostic indicators for the course of hip complaints in a primary care population.Purpose: The purpose of this study was to investigate the course of hip complaints presented in general practice and to identify relevant prognostic indicators of outcome.Methods: Data were collected by means of self-administered questionnaires containing questions about sociodemographic variables, characteristics of the complaints, and several intraindividual and extraindividual factors, including several psychosocial variables (e.g., pain coping, distress, and kinesiophobia). After 3 and 12 months of follow-up perceived recovery, change in pain intensity and change in functioning were assessed. Multiple regression analyses were performed to investigate the association between the potential prognostic indicators and the 3 outcome measures.Results: We included 139 patients with hip complaints, presented in general practice. Only 24% reported recovery after 3 months, increasing to 37% after 12 months. A history of hip complaints, a longer duration of the current episode of hip complaints, or more severe complaints, were associated with a less favorable prognosis. Furthermore, more vital patients and patients who met the Norm for Healthy Activity had a higher probability of a favorable outcome. Pain transformation and worrying were significant associated with recovery and changes in functioning after 3 months.Conclusions: Different prognostic indicators were found to be associated with perceived recovery, changes in pain intensity, and changes in functioning. Future research should aim at investigating the mechanisms that can underlie these associations.
Prognosis prediction of human breast cancer by integrating deep neural network and support vector machine: Supervised feature extraction and classification for breast cancer prognosis prediction

Breast cancer is the second most common cancer, which accounts for about 16% of all female cancers and 18.2% of all cancer deaths worldwide including both males and females. Therefore, accurate prognosis prediction of breast cancer is one of the most crucial works in follow-up treatment. In this work, we introduced a novel deep learning (DL) method named D-SVM for the prediction of human breast cancer prognosis. D-SVM was a supervised feature extraction and classification method integrating deep neural network and traditional support vector machine (SVM) classifier. This novel algorithm effectively learned hierarchical and abstract representation from raw input data and successfully integrated traditional classification method. Our experimental results clearly indicated that the proposed method could enable us to train a model that yielded reasonably good performance than traditional classification approaches on a small-scale gene expression dataset for breast cancer.
Removal of Arsenic from Potable Water by Adsorptive Media Treatment Techniques

This study was conducted to investigate the arsenic removal efficiency of different adsorptive media from water. Different naturally occurring materials such as bauxite, plastic clay, plaster of Paris, lime, alum, and alumina etc. were used for the development of media to remove arsenic As present in the artificially contaminated water. Different ratios of the selected materials were combined and ignited at 900C to enhance its arsenic removing efficiency. It was found that the media bauxite, plastic clay, lime (1:1:1) has a maximum removal (99%) of As species from aqueous media and can be used onsite to reduce the arsenic contamination of potable water. Furthermore, the materials used in this experiment were cheaply and abundantly available within the country. The method is very simple and economically viable, for removal of arsenic from potable water.
NANOINDENTATION DATA ANALYSIS OF RING STRUCTURED SCAFFOLDS USING BERKOVICH AND CONOSPHERICAL TIPS

Scaffolds are promising biomaterials for tissue regeneration and much attention has been given in the development of engineered structures that promote cell adhesion, growth and mechanical stability. Fabrication of three-dimensional (3D) scaffolds with appropriate geometry, which combine nano- and micro-features, and present the above mentioned characteristics, is a challenge. Recent research activity focuses on the mechanical properties testing of scaffolds to investigate the substrate effect on cell growth and provide a comparison of the mechanical properties of the reconstructed tissue to the physiological one. However, measuring the mechanical properties of soft matter is a challenge, since the observed heterogeneities affect the accuracy of the obtained results and the final estimation of the materials’ efficiency. In the study, we investigated the nanomechanical properties of 3D ring structured scaffolds suitable for bone tissue engineering with two different tip geometries. Different applied tests were performed in order to investigate the creep response and timedependency of the structure, which are affected by the viscous behavior of the synthesized material. Finally, new experimental testing processes were performed in order to eliminate the viscous response and calculate the dissipated energy.
Thermal Reactions and Industrial Uses of Bark

A kinetic study indicated that the phenolic substances in Douglas-fir and red alder bark can be polymerized by high-temperature heating. Organic extractives that may be leached out by the action of water are condensed to water insolubles. Heat-treated bark is shown to be an appropriate material for the cleaning up of oil spills on water without contributing to high BOD and possible toxieity to fish. The oil absorption of bark, depending on its particle size, is two to seven times its weight. A vacuum system was developed for hot pressing bark boards, which technnique avoids blister formation caused by the evolution of gases from condensation and dehydration reactions in thick boards. Bark boards made under an appropriate time-temperature schedule have both internal bond strength and bending modulus of rupture similar to bark boards made with 4.5% phenolic resin and subsequently pressed at a moderate time-temperature schedule, precluding polymerization of the bark extractives. Hot stacking increased the internal bond strength of boards. Dimensional stability is the most significant property of these bark boards. Properly made bark boards have a much smaller thickness swelling and linear expansion than bark boards made with 4.5% phenolic resin after soaking in water for 72 hr.
An improved fusion method for infrared and low-light level visible image

In this paper, we propose an improved image fusion algorithm for infrared and visible images acquired under low illumination. Firstly, single scaled Retinex (SSR) algorithm is applied to enhance visible images. And then, both infrared image and the enhanced visible image are decomposed into multilayer images by Laplacian pyramid algorithm. Finally, the decomposed images are fused with the method based on regional features measurement. The experiment results show that even the source images are with low contrast and low illumination, the proposed algorithm can obtain fused images with highly enhanced contrast, which can easily distinguish targets from background, and is better able to preserve texture and detail from source images. Moreover, this SSR-Laplacian algorithm is universal for near-infrared images as well as thermal-infrared images.
Crimean-Congo Hemorrhagic Fever: Tick-Host-Virus Interactions

Crimean-Congo hemorrhagic fever virus (CCHFV) is transmitted to humans by bite of infected ticks or by direct contact with blood or tissues of viremic patients or animals. It causes to humans a severe disease with fatality up to 30%. The current knowledge about the vector-host-CCHFV interactions is very limited due to the high-level containment required for CCHFV studies. Among ticks, Hyalomma spp. are considered the most competent virus vectors. CCHFV evades the tick immune response, and following its replication in the lining of the tick's midgut, it is disseminated by the hemolymph in the salivary glands and reproductive organs. The introduction of salivary gland secretions into the host cells is the major route via which CCHFV enters the host. Following an initial amplification at the site of inoculation, the virus is spread to the target organs. Apoptosis is induced via both intrinsic and extrinsic pathways. Genetic factors and immune status of the host may affect the release of cytokines which play a major role in disease progression and outcome. It is expected that the use of new technology of metabolomics, transcriptomics and proteomics will lead to improved understanding of CCHFV-host interactions and identify potential targets for blocking the CCHFV transmission.
Predicting customer behavior in online shopping using SVM classifier

Customer buying behavior is identified by people's personality and character. These personality characters vary from person to person. The character includes quality, motivation, occupation and income level, perception, psychological, personality, reference groups and demographic reasons learning, beliefs, attitude, Culture and social forces. Nowadays, Data mining normally used to investigate the customer activities on shopping by using various algorithms and methods. Data mining has gradually raised and it gains numerous industries which applies this technology. Each and every activity of a customer is stored as a byte of data in a database to collect information such as how the customer spends their valuable time, day in buying decision. Most frequents items bought and quantity of buy is also considered. These data are collected without the knowledge of the customer. In this paper, the dataset is used to analyze and categorize the customer based on their purchase behavior. The classification is performed by SVM algorithm. The inventory data set and sales data set which is available in the internet is used in this work and the performance is evaluated by using the algorithms. The experimental results are analyzed and it shows that the proposed methodology analyze a customer behavior in a better way.
A Smartphone-Driven Thermometer Application for Real-time Population- and Individual-Level Influenza Surveillance

Background Smartphone-based sensors may enable real-time surveillance of infectious diseases at population and household levels. This study evaluates the use of data from commercially available "smart thermometers," connected to a mobile phone application, for surveillance of influenza-like illness (ILI). Methods At a population level, we analyzed the correlation between thermometer recordings and Centers for Disease Control and Prevention-reported ILI activity nationally and by age group and region. We developed time-series models to forecast ILI activity in real time and up to 3 weeks in advance. We analyzed the ability of thermometer readings to track the duration of fevers and identify biphasic fever patterns. We also investigated potential transmission of febrile illness within households among device users. Results Thermometer readings were highly correlated with national ILI activity (r > 0.95) and activity patterns across regions and age groups. Thermometer readings also significantly improved forecasts of ILI activity in real time and up to 3 weeks in advance. We found that fevers lasting between 3 and 6 days and biphasic fever episodes occurred more frequently during the influenza season. In addition, potential cases of in-household transmission of febrile illness originated more frequently from children than adults. Conclusions Smart thermometers represent a novel source of information for influenza surveillance and forecasting. Thermometer readings capture real-time ILI activity at a population level, and they can also be used to generate improved forecasts. Moreover, the widespread deployment of these smart thermometers may also allow for more rapid and efficient surveillance at the household level.