Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss of USP28-mediated BRAF degradation drives resistance to RAF cancer therapies

RAF kinase inhibitors are clinically active in patients with BRAF (V600E) mutant melanoma. However, rarely do tumors regress completely, with the majority of responses being short-lived. This is partially mediated through the loss of negative feedback loops after MAPK inhibition and reactivation of upstream signaling. Here, we demonstrate that the deubiquitinating enzyme USP28 functions through a feedback loop to destabilize RAF family members. Loss of USP28 stabilizes BRAF enhancing downstream MAPK activation and promotes resistance to RAF inhibitor therapy in culture and in vivo models. Importantly, we demonstrate that USP28 is deleted in a proportion of melanoma patients and may act as a biomarker for response to BRAF inhibitor therapy in patients. Furthermore, we identify Rigosertib as a possible therapeutic strategy for USP28-depleted tumors. Our results show that loss of USP28 enhances MAPK activity through the stabilization of RAF family members and is a key factor in BRAF inhibitor resistance.
Coordinated decentralized protocols for failure diagnosis of discrete event systems

We address the problem of failure diagnosis in discrete event systems with decentralized information. We propose a coordinated decentralized architecture consisting of local sites communicating with a coordinator that is responsible for diagnosing the failures occurring in the system. We extend the notion of diagnosability, originally introduced in Sampath et al. (1995) for centralized systems, to the proposed coordinated decentralized architecture. We specify three protocols, i.e. the diagnostic information generated at the local sites, the communication rules used by the local sites, and the coordinator's decision rule, that realize the proposed architecture. We analyze the diagnostic properties of each protocol. We also state and prove necessary and sufficient conditions for a language to be diagnosable under each protocol. These conditions are checkable off-line. The online diagnostic process is carried out using the diagnosers introduced in the above article or a slight variation of these diagnosers. The key features of the proposed protocols are: (i) they achieve, each under a set of assumptions, the same diagnostic performance as the centralized diagnoser; and (ii) they highlight the performance vs. complexity tradeoff that arises in coordinated decentralized architectures. The correctness of two of the protocols relies on some stringent global ordering assumptions on message reception at the coordinator's site, the relaxation of which is briefly discussed.
Effect of Sintering Pressure on the Porosity and the Shear Strength of the Pressure-Assisted Silver Sintering Bonding

The microstructure, thickness, porosity, and shear performance of the silver (Ag) sintering layers under different sintering pressures were investigated. Experimental results demonstrated that the thickness and the porosity of the sintering layer decreased when the sintering pressure varied from 5 MPa to 30 MPa. This densification phenomenon facilitated the enhancement of the Ag sintering layers. The shear strength was improved significantly from 44.19 MPa to 69.41 MPa when the sintering pressure increased from 5 MPa to 10 MPa. When the sintering pressure ranged from 10 MPa to 30 MPa, the shear strength presented a slow increase from 69.41 MPa to 73.38 MPa. According to the results of the failure analysis, fracture mode transformation was considered as the basic reason for this phenomenon. The increasing sintering pressure promoted the bonding of the nano-Ag particles during the sintering process. Consequently, the fracture of the sintered-Ag layer transformed from brittle fracture to ductile fracture because of the increasing sintering pressure. The delamination area between Cu and Ni layers coated on the bottom Mo plate was clearly enlarged with the increasing sintering pressure. The delamination between Cu and Ni layers coated on the bottom Mo plate turned to be the main failure mode when the sintering pressure was higher than 10 MPa.
The Solar Twin Planet Search. I. Fundamental parameters of the stellar sample

Context. We are carrying out a search for planets around a sample of solar twin stars using the HARPS spectrograph. The goal of this project is to exploit the advantage offered by solar twins to obtain chemical abundances of unmatched precision. This survey will enable new studies of the stellar composition – planet connection. Aims. We determine the fundamental parameters of the 88 solar twin stars that have been chosen as targets for our experiment. Methods. We used the MIKE spectrograph on the Magellan Clay Telescope to acquire high resolution, high signal-to-noise ratio spectra of our sample stars. We measured the equivalent widths of iron lines and used strict differential excitation/ionization balance analysis to determine atmospheric parameters of unprecedented internal precision: σ(Teff) = 7K ,σ(log g) = 0.019, σ([Fe/H]) = 0.006 dex, σ(vt) = 0.016 km s −1 . Reliable relative ages and highly precise masses were then estimated using theoretical isochrones. Results. The spectroscopic parameters we derived are in good agreement with those measured using other independent techniques. There is even better agreement if the sample is restricted to those stars with the most internally precise determinations of stellar parameters in every technique involved. The root-mean-square scatter of the differences seen is fully compatible with the observational errors, demonstrating, as assumed thus far, that systematic uncertainties in the stellar parameters are negligible in the study of solar twins. We find a tight activity-age relation for our sample stars, which validates the internal precision of our dating method. Furthermore, we find that the solar cycle is perfectly consistent both with this trend and its star-to-star scatter. Conclusions. We present the largest sample of solar twins analyzed homogeneously using high quality spectra. The fundamental parameters derived from this work will be employed in subsequent work that aims to explore the connections between planet formation and stellar chemical composition.
Risk factors associated with overweight and obesity in HIV-infected people

Abstract Identifying risk factors associated with overweight and obesity in HIV-infected patients. A cross-sectional study analyzing data from patients attending an HIV outpatient unit. Overweight was defined as body mass index (BMI) ≥25 kg/m2; <30 kg/m2, obesity was ≥30 kg/m2. Patients’ characteristics contemporary to BMI assessment were collected. Multivariate logistic regression identified risk factors associated with overweight/obesity. Eight hundred sixty-two patients, median age 51 years, 21.5 years of HIV infection follow-up, 585 (68%) male, 829 (96%) receiving combined antiretroviral therapy (cART) for median 16.7 years, 768 (91%) HIV load <40 copies/mL, 618 (73%) CD4+ ≥500 cells/mm3; 266 (31%) HCV+ serology, 110 (13%) had detectable HCV-RNA. Overweight affected 191 (22%) patients and obesity 46 (5%). Overweight and obesity were associated with age, HIV follow-up duration, and HIV transmission risk group. Overweight was also associated with gender and HCV status. In patients with substance use data, overweight was associated with alcohol and nonsmoking status. Obesity was associated with nonsmoking and ex-smoker status. Overweight/obesity were not found associated with cART or immune cell counts. In HIV-infected people, aging, alcohol consumption, nonsmoking, and ex-smoker status, the absence of HCV coinfection and to have cleared HCV infection are associated with overweight and/or obesity. Clinicians should be aware of these trends and consider introducing weight management programs as part of routine HIV care.
Exploring the Impact of Video on Inferred Difficulty Awareness

An important issue in many forms of collaboration technology is how video can help the technology better meet its goals. This paper explores this question for difficulty awareness, which is motivated by academic and industrial collaboration scenarios in which unsolicited help is offered to programmers in difficulty. We performed experiments to determine how well difficulty can be automatically inferred by mining the interaction log and/or videos of programmers. Our observations show that: (a) it is more effective to mine the videos to detect programmer postures rather than facial features; (b) posturemining benefits from an individual model (training data for a developer is used only for that developer), while in contrast, log-mining benefits from a group model (data of all users are used for each user); (b) posture-mining alone (using an individual model) does not detect difficulties of “calm” programmers, who do not change postures when they are in difficulty; (c) log-mining alone (using a group model) does not detect difficulties of programmers who pause interaction when they are either in difficulty or taking a break; (d) overall, log-mining alone is more effective than posture-mining, alone; (e) both forms of mining have high false negative rates; and (g) multimedia/multimodal detection that mines postures and logs using a group model gives both low false positive and negatives. These results imply that (a) when collaborators can be seen, either directly or through a video, posture changes, though idiosyncratic, are important cues for inferring difficulty; (b) automatically inferred difficulty, using both interaction-logs and postures, when possible and available, is an even more reliable indication of difficulty; (c) video can play an important role in providing unsolicited help in both face-to-face and distributed collaboration; and (d) controlled public environments such as labs and war-rooms should be equipped with cameras that support posture mining.
The Effect of Learning on Ambiguity Attitudes

This paper studies the effect of learning information on people's attitudes toward ambiguity. We propose a method to separate ambiguity attitudes from subjective probabilities and to decompose ambiguity attitudes into two components. Under models like prospect theory that represent ambiguity through nonadditive decision weights, these components reflect pessimism and likelihood insensitivity. Under multiple priors models, they reflect ambiguity aversion and perceived ambiguity. We apply our method in an experiment where we elicit the ask prices of options with payoffs depending on the returns of initial public offerings (IPOs) on the New York Stock Exchange. IPOs are a natural context to study the effect of learning, as prior information about their returns is unavailable. Subjects perceived substantial ambiguity and they were insensitive to likelihood information. We observed only little pessimism and ambiguity aversion. Subjective probabilities were well calibrated and close to the true frequencies. Subjects' behavior moved toward expected utility with more information, but substantial deviations remained even in the maximum information condition.
Densely Connected Discriminative Correlation Filters for Visual Tracking

Discriminative Correlation Filters (DCFs)-based approaches have recently achieved competitive performance in visual tracking. However, such conventional DCF-based trackers often lack the discriminative ability due to the shallow architecture. As a result, they can hardly tackle drastic appearance variations and easily drift when the target suffers heavy occlusions. To address this issue, a novel densely connected DCFs framework is proposed for visual tracking. We incorporate multiple nested DCFs into the deep learning architecture, and then train the compact network with the data-specific target. Specifically, feature maps and interim response maps are shared and reused throughout the whole network. By doing so, the implicit information carried out by each DCF is fully exploited to enhance the model representation ability during the tracking process. Moreover, a multiscale estimation scheme is developed to account for scale variations. Experimental results on the benchmarks demonstrate that the proposed approach achieves outstanding performance compared to the existing state-of-the-art trackers.
A theoretical analysis of antecedents of young couples’ fertility decisions and outcomes

Longitudinal survey data from 509 couples who at Time 1 interview had recently married or had their first child did not support the hypothesis that demographic factors influence fertility intentions, decisions, and outcomes only indirectly through their effects on attitudes and motivations. Husbands’ and wives’ attitudes exerted reciprocal influence on one another. However, while husbands’ sex-role traditionalism and motivation for parenthood strongly influenced wives’ traditionalism and motivation in the case of recently married couples, this pattern was reversed for riew parents. Birth control use was directly affected by wives’ fertility intentions, but not by husbands’ intentions. Difficulties in examining couple interaction variables such as relative power and the possible limitations of fitting these data to a complex theoretical model using LISREL are discussed.
How Social Media Is Changing Conflict

Social media increasingly plays a role in conflict and contentious politics. Politicians, leaders, insurgents, and protestors all have used it as a tool for communication. At the same time, scholars have turned to social media as a source of new data on conflict. I provide a framework for understanding social media’s influence on conflict through four interrelated points: (1) social media reduces the costs of communication, (2) it increases the speed and dissemination of information, (3) scholars should focus on the strategic interaction and competitive adaption of actors in response to communication technology changes, and (4) the new data that social media provides are not only an important resource, but also fundamentally change the information available to conflict actors, thereby shaping the conflict itself. In sum, social media’s influence on conflict defies simplistic explanations that argue that it privileges incumbents or challengers.
Effect of cell culture medium additives on color and acidic charge variants of a monoclonal antibody

This manuscript summarizes the effect of certain cell culture medium additives on antibody drug substance coloration and acidic charge variants. It has been shown previously that B‐vitamins and iron in the cell culture medium could significantly impact color intensity. In this manuscript, we detail the effect of several other cell culture components that have been shown to impact coloration. It is shown that if cystine is used instead of cysteine in the cell culture medium, coloration was reduced. Hydrocortisone has been shown to reduce coloration and boost specific productivity. The effect of a peptone/hydrolysate on coloration was investigated in cell culture experiments, which showed its use can lead to reduced coloration. Mechanisms by which these compounds influence coloration will be briefly discussed. Since it has been previously shown that antibody oxidation could potentially lead to coloration, the current effort was focused on screening for specific antioxidant additives to the culture medium to reduce coloration. An in‐vitro incubation model was used to screen antioxidant compounds, several of which were found to significantly reduce antibody color, while some led to significantly increased color. Hypotaurine and carboxymethylcysteine, which had the most significant color reducing effect in the incubation study, were further tested in small‐scale bioreactor cell culture experiments. These studies demonstrated that these compounds lead to reduced coloration in cell culture without affecting cell growth and titer. Hypotaurine, hydrocortisone, peptone, and cystine were also shown to reduce the acidic charge variant levels, which was previously shown to correlate with color. © 2018 American Institute of Chemical Engineers Biotechnol. Prog. , 2018 © 2018 American Institute of Chemical Engineers Biotechnol. Prog. , 34:1298–1307, 2018
Inclusion of alternative marine by-products in aquafeeds with different levels of plant-based sources for on-growing gilthead sea bream (Sparus aurata, L.): effects on digestibility, amino acid retention, ammonia excretion and enzyme activity

ABSTRACT The search for new sustainable aquafeeds for the species with greater economic importance, such as the gilthead sea bream in Europe, is one of the main challenges in the aquaculture sector. The present work tested fishmeal replacement by a mixture of plant meals at different levels, as well as the use of marine by-products with attractant properties and high-quality protein in high plant protein diets. In order to do that, effects on growth and biometric parameters, digestibility, amino acid retention, excreted ammonia and proteases and amylase activity were assessed, using six different diets: FM100 (100% of protein provided by fishmeal), FM50 (50% of replacement), FM25 (75% of replacement) and FM0 (100% of replacement), but also FM25+ (75% of replacement and 15% of squid and krill meal inclusion), and FM0+ (100% of replacement and 15% of squid and krill meal inclusion). In group FM0, a clear impact of dietary changes was observed on growth, survival and ammonia excretion. Amino acid retention in group FM0+ was also significantly affected, which can be explained by the limited content of certain amino acids in this diet. On the other hand, no significant differences were observed in most biometric parameters or in enzyme activity. In conclusion, complete fishmeal replacement can be achieved by using a mixture of plant-based sources, but supplementation with complementary marine ingredients can prevent detrimental effects on growth, survival, nutritional parameters and protein metabolism.
Lower Expression of Ndfip1 Is Associated With Alzheimer Disease Pathogenesis Through Decreasing DMT1 Degradation and Increasing Iron Influx

We have previously reported that high expression of divalent metal transporter 1 (DMT1) plays a crucial role in iron dyshomeostasis and β-amyloid (Aβ) peptide generation in the brain of Alzheimer’s disease (AD). Recent studies have shown that Nedd4 family interacting protein 1 (Ndfip1) can degrade DMT1 through ubiquitination pathway and reduce the accumulation of intracellular iron. The present study aims to evaluate whether Ndfip1 is involved in AD pathogenesis through mediating DMT1 degradation and iron metabolism. β-amyloid precursor protein/presenilin 1 (APP/PS1) transgenic mouse and Ndfip1 transfected SH-SY5Y cells were used in this study. Immunohistochemistry and Western blot were performed to examine the distribution and expression levels of Ndfip1 and DMT1. In addition, ELISA and calcein fluorescence were carried out for analyzing the levels of Aβ peptide and iron influx, respectively. The results showed that Ndfip1 immunoreactivity was decreased in the cortex and hippocampus of APP/PS1 mice, compared with wild type (WT) controls. Colocalization of Ndfip1 and Aβ within senile plaques could be observed. Immunoblot analyses showed that low expression of Ndfip1 and high expression of DMT1 proteins were detected in APP/PS1 mouse brain, compared with age-matched WT animals. Overexpression of Ndfip1 down-regulated DMT1 expression, and reduced iron influx and Aβ secretion in SH-SY5Y cells. Further, overexpressed Ndfip1 significantly attenuated iron-induced cell damage in Ndfip1 transfected cells. The present study suggests that lower expression of Ndfip1 might be associated with the pathogenesis of AD, through decreasing DMT1 degradation and increasing iron accumulation in the brain.
Obesity treatment by epigallocatechin‐3‐gallate−regulated bile acid signaling and its enriched Akkermansia muciniphila

Dysregulated bile acid (BA) synthesis is accompanied by dysbiosis, leading to compromised metabolism. This study analyzes the effect of epigallocatechin‐3‐gallate (EGCG) on diet‐induced obesity through regulation of BA signaling and gut microbiota. The data revealed that EGCG effectively reduced diet‐increased obesity, visceral fat, and insulin resistance. Gene profiling data showed that EGCG had a significant impact on regulating genes implicated in fatty acid uptake, adipogenesis, and metabolism in the adipose tissue. In addition, metabolomics analysis revealed that EGCG altered the lipid and sugar metabolic pathways. In the intestine, EGCG reduced the FXR agonist chenodeoxycholic acid, as well as the FXR‐regulated pathway, suggesting intestinal FXR deactivation. However, in the liver, EGCG increased the concentration of FXR and TGR‐5 agonists and their regulated signaling. Furthermore, our data suggested that EGCG activated Takeda G protein receptor (TGR)‐5 based on increased GLP‐1 release and elevated serum PYY level. EGCG and antibiotics had distinct antibacterial effects. They also differentially altered body weight and BA composition. EGCG, but not antibiotics, increased Verrucomicrobiaceae, under which EGCG promoted intestinal bloom of Akkermansia muciniphila. Excitingly, A. muciniphila was as effective as EGCG in treating diet‐induced obesity. Together, EGCG shifts gut microbiota and regulates BA signaling thereby having a metabolic beneficial effect. —Sheng, L. , Jena, P. K. , Liu, H. ‐X. , Hu, Y. , Nagar, N. , Bronner, D. N. , Settles, M. L. , Baumler, A. J., Wan, Y. ‐J. Y. Obesity treatment by epigallocatechin‐3‐gallate−regulated bile acid signaling and its enriched Akkermansia muciniphila. FASEB J. 32, 6371–6384 (2018). www.fasebj. org
Screen Dependency Disorders: a new challenge for child neurology

Children’s neurological development is influenced by what they do and do not experience. Early experiences and the environments in which they occur can alter gene expression and affect long-term neural development. Today, discretionary screen time (DST), often involving multiple devices, is the single main experience and environment of children. Various screen activities are reported to induce structural and functional brain plasticity in adults. However, childhood is a time of significantly greater changes in brain anatomical structure and connectivity. Digital natives exhibit a higher prevalence of screen-related ‘addictive’ behaviours that reflect impaired neurological reward-processing and impulse-control mechanisms. Associations are emerging between screen dependency disorders (SDD) such as Internet Addiction Disorder and specific neurogenetic polymorphisms, abnormal neural tissue and neural function. Although abnormal neural structural and functional characteristics may be a precondition rather than a consequence of addiction, there may also be a bidirectional relationship. As is the case with substance addictions, it is possible that intensive routine exposure to certain screen activities during critical stages of neural development may alter gene expression resulting in structural, synaptic and functional changes in the developing brain leading to SDD, particularly in children with predisposing neurogenetic profiles. There may also be compound/secondary effects on paediatric neural development. Screen dependency disorders, even at subclinical levels, involve high levels of discretionary screen time, inducing greater child sedentary behaviour thereby reducing vital aerobic fitness, which plays an important role in the neurological health of children, particularly in brain structure and function. Child health policy must therefore adhere to the principle of precaution as a prudent approach to protecting child neurological integrity and well-being. This paper explains the basis of current paediatric neurological concerns surrounding SDD and proposes preventive strategies for child neurology and allied professions.