Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy and Pharmacodynamic Modeling of the BTK Inhibitor Evobrutinib in Autoimmune Disease Models

Key Points The covalent BTK inhibitor evobrutinib blocks B cell and myeloid cell activation. Evobrutinib is efficacious in mouse models for RA, SLE, and cutaneous anaphylaxis. Covalent binding allows modeling the relationship between BTK occupancy and efficacy. Because of its role in mediating both B cell and Fc receptor signaling, Bruton’s tyrosine kinase (BTK) is a promising target for the treatment of autoimmune diseases such as rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Evobrutinib is a novel, highly selective, irreversible BTK inhibitor that potently inhibits BCR- and Fc receptor–mediated signaling and, thus, subsequent activation and function of human B cells and innate immune cells such as monocytes and basophils. We evaluated evobrutinib in preclinical models of RA and SLE and characterized the relationship between BTK occupancy and inhibition of disease activity. In mouse models of RA and SLE, orally administered evobrutinib displayed robust efficacy, as demonstrated by reduction of disease severity and histological damage. In the SLE model, evobrutinib inhibited B cell activation, reduced autoantibody production and plasma cell numbers, and normalized B and T cell subsets. In the RA model, efficacy was achieved despite failure to reduce autoantibodies. Pharmacokinetic/pharmacodynamic modeling showed that mean BTK occupancy in blood cells of 80% was linked to near-complete disease inhibition in both RA and SLE mouse models. In addition, evobrutinib inhibited mast cell activation in a passive cutaneous anaphylaxis model. Thus, evobrutinib achieves efficacy by acting both on B cells and innate immune cells. Taken together, our data show that evobrutinib is a promising molecule for the chronic treatment of B cell–driven autoimmune disorders. Visual Abstract
Feature Fusion of Deep Spatial Features and Handcrafted Spatiotemporal Features for Human Action Recognition

Human action recognition plays a significant part in the research community due to its emerging applications. A variety of approaches have been proposed to resolve this problem, however, several issues still need to be addressed. In action recognition, effectively extracting and aggregating the spatial-temporal information plays a vital role to describe a video. In this research, we propose a novel approach to recognize human actions by considering both deep spatial features and handcrafted spatiotemporal features. Firstly, we extract the deep spatial features by employing a state-of-the-art deep convolutional network, namely Inception-Resnet-v2. Secondly, we introduce a novel handcrafted feature descriptor, namely Weber’s law based Volume Local Gradient Ternary Pattern (WVLGTP), which brings out the spatiotemporal features. It also considers the shape information by using gradient operation. Furthermore, Weber’s law based threshold value and the ternary pattern based on an adaptive local threshold is presented to effectively handle the noisy center pixel value. Besides, a multi-resolution approach for WVLGTP based on an averaging scheme is also presented. Afterward, both these extracted features are concatenated and feed to the Support Vector Machine to perform the classification. Lastly, the extensive experimental analysis shows that our proposed method outperforms state-of-the-art approaches in terms of accuracy.
Ntrk1 Promotes Resistance to PD-1 Checkpoint Blockade in Mesenchymal Kras/p53 Mutant Lung Cancer

The implementation of cancer immunotherapeutics for solid tumors including lung cancers has improved clinical outcomes in a small percentage of patients. However, the majority of patients show little to no response or acquire resistance during treatment with checkpoint inhibitors delivered as a monotherapy. Therefore, identifying resistance mechanisms and novel combination therapy approaches is imperative to improve responses to immune checkpoint inhibitors. To address this, we performed an in vivo shRNA dropout screen that focused on genes encoding for FDA-approved drug targets (FDAome). We implanted epithelial and mesenchymal Kras/p53 (KP) mutant murine lung cancer cells expressing the FDAome shRNA library into syngeneic mice treated with an anti-PD-1 antibody. Sequencing for the barcoded shRNAs revealed Ntrk1 was significantly depleted from mesenchymal tumors challenged with PD-1 blockade, suggesting it provides a survival advantage to tumor cells when under immune system pressure. Our data confirmed Ntrk1 transcript levels are upregulated in tumors treated with PD-1 inhibitors. Additionally, analysis of tumor-infiltrating T cell populations revealed that Ntrk1 can promote CD8+ T cell exhaustion. Lastly, we found that Ntrk1 regulates Jak/Stat signaling to promote expression of PD-L1 on tumor cells. Together, these data suggest that Ntrk1 activates Jak/Stat signaling to regulate expression of immunosuppressive molecules including PD-L1, promoting exhaustion within the tumor microenvironment.
“A Face Like This Is Hard to Beat”: Negotiating Lilith in the Postfeminist Media Economy

Abstract From mythology, history, and religion to contemporary popular culture, Lilith has been represented in a variety of ways. As either an avenging vampire or a seductive temptress, or a fascinating combination of both, she has been understood as both an object of a patriarchal view of women and a liberated and liberating feminist icon. The meanings that are ascribed to Lilith are thoroughly interwoven with contemporary feminist discourse. We argue that it is precisely within the postfeminist media economy that the meanings and functions of various tropes of femininity are destabilised and renegotiated. In this article, we limit our focus to the appearance of Lilith in two recent television series, namely The Chilling Adventures of Sabrina (2018–) and Shadowhunters (2016–2019). Our aim is to highlight the ways in which the Liliths represented in each series negotiate one specific trope of femininity used in popular culture, namely the femme fatale. We show that whilst these manifestations of Lilith as postfeminist femme fatale may open up potentialities for feminist resistance, they are simultaneously trapped in an oppressive system of representation that constructs women as passive objects of heteronormative male fantasies.
Dietary Ingredients Requiring Further Research Before Evidence-Based Recommendations Can Be Made for Their Use as an Approach to Mitigating Pain

Abstract Objective Approximately 55–76% of Service members use dietary supplements for various reasons; although such use has become popular, decisions are often driven by information that is not evidence-based. This work evaluates whether current research on dietary ingredients for chronic musculoskeletal pain provides sufficient evidence to inform decisions for practice and self-care, specifically for Special Operations Forces personnel. Methods A steering committee convened to develop research questions and factors required for decision-making. Key databases were searched through August 2016. Eligible systematic reviews and randomized controlled trials were assessed for methodological quality. Meta-analysis was applied where feasible. Grading of Recommendations, Assessment, Development and Evaluation was used to determine confidence in the effect estimates. The committee used a decision table to make evidence-informed judgments across decision-making factors and recommendations for practice and self-care use. Results Nineteen dietary ingredients were assessed. No recommendations were given for boswellia, ginger, rose hip, or s-adenosyl-L-methionine (SAMe); specifically, although ginger can be obtained via food, no recommendation is provided for use as a supplement due to unclear research. Further, there were insufficient strong research on boswellia and SAMe and possible compliance issues (i.e., high number of capsules required daily) associated with rose hip. Conclusions No recommendations were made when the evidence was low quality or trade-offs were so closely balanced that any recommendation would be too speculative. Research recommendations are provided to enhance the quality and body of evidence for the most promising ingredients. Clinicians and those with chronic pain can rely on evidence-based recommendations to inform their decisions.
Feasibility of Family Group Conference to promote return-to-work of persons receiving work disability benefit

Abstract Purpose: To investigate the feasibility of Family Group Conference for promoting return to work by clients receiving work disability benefits from the Social Security Institute in the Netherlands. Methods: We conducted a mixed-method pre- post-intervention feasibility study, using questionnaires, semi-structured interviews and return to work plans drafted in Family Group Conferences. A convenient sample of Labour experts, Clients, and Facilitators was followed for a period of six months. Feasibility outcomes were demand, acceptability, implementation and limited efficacy of perceived mental health and level of participation. Results: Fourteen labour experts and sixteen facilitators enrolled in the study. Of 28 eligible clients, nine (32%) participated in a Family Group Conference. About 78% of the Family Group Conferences were implemented as planned. Participant satisfaction about Family Group Conference was good (mean score 7). Perceived mental health and level of participation improved slightly during follow-up. Most actions in the return to work plans were work related. Most frequently chosen to take action was the participating client himself, supported by significant others in his or her social network. Six months after the Family Group Conference five participating clients returned to paid or voluntary work. Conclusions: Family Group Conference seems a feasible intervention to promote return to work by clients on work disability benefit. Involvement of the social network may have added value to support the clients in this process. An effectiveness study to further develop and test Family Group Conferences is recommended. Implications for rehabilitation Family Group Conference may represent a promising approach to be used in activation strategies to enhance social inclusion and return to work of persons receiving disability benefits. Conventional supply-oriented activation services could be improved by providing the Family Group Conference to unemployed persons on disability benefit. Involvement of the social network may have added value for return to work of clients receiving work disability benefits.
Photocatalytic Activity of TiO2 Nanofibers: The Surface Crystalline Phase Matters

The crystal phases and surface states of TiO2 can intrinsically determine its performance in the applications of photocatalysis. Here, we prepared TiO2 nanofibers with different crystal phase contents by electrospinning followed via calcination at different temperatures. The TiO2 nanofibers were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectrometry, transmission electron microscopy (TEM), and photocatalytic performance testing. The results showed that the phases of TiO2 nanofibers were layered, that surface crystal phase transition rate was faster than that of internal layers contributed the difference in the ratio of anatase and rutile in the outer and inner layer of TiO2 nanofibers. The TiO2 nanofibers obtained at 575 °C had the best photocatalytic activity, taking only 25 min to degrade Rhodamine B. At 575 °C, the rutile content of the sample surface was about 80 wt. %, while the internal rutile content was only about 40 wt. %. Subsequently, we prepared two different structures of anatase–rutile core-shell TiO2 nanofibers. The core-shell structure can be clearly seen by TEM characterization. The photocatalytic activity of two kinds of core-shell TiO2 nanofibers was tested. The results showed that the photocatalytic activity was close to that of the pure phase TiO2 nanofibers, which corresponded with the surface phase. This further proves that the photocatalytic activity of the material is mainly affected by its surface structure.
Assessing Singular Causation: The Role of Causal Latencies

Singular causation queries require an assessment of whether a singular co-occurrence of two events c and e was causal or simply coincidental. The current study builds on our previous research (Stephan & Waldmann, 2018) in which we proposed a computational model of singular causation judgments. The model highlights that singular causation judgments need to take into account the power of the target cause C and of alternative causes A, as well as the possibility of preemption. What was missing was a detailed model allowing us to estimate the probability of preemption of a target cause by the alternative causes. The present research fills this gap by elaborating the temporal assumptions that might enter assessments of singular causation. We focus on assumptions about temporal precedence between target and alternative causes, with a specific focus on assumptions about causal latency. We report the results of two new experiments supporting the model.
Simulation, Fabrication, and Characterization of a Sensitive SU-8-Based Fabry-Pérot MOEMS Accelerometer

This paper presents the design, fabrication, and characterization of a SU-8 four L-shaped beams optical micro-electro-mechanical-system accelerometer based on a Fabry–Pérot (FP) interferometer. An applied acceleration causes a displacement of the proof mass and changes the cavity of FP resonator. Fabrication process has been simplified such that only two photolithography steps are required and SU-8 is used for both the structural body and the sacrificial layer. To prevent the sacrificial layer from being exposed to UV light, a thin copper layer is coated by physical vapor deposition technique between the two SU-8 layers. The sensor chip consists of a proof mass which is suspended by four L-shaped springs. The movement of the proof mass in response to acceleration is detected by a FP cavity formed between the proof mass and the cleaved end of a single mode optical fiber. The fabricated sensor has a sensitivity of 12.5 μW/g and resonant frequency of 1872 Hz in the range of ±1 g.
Application of Power Grid Communication Operation and Maintenance Knowledge Base Based on Self-learning Technology

With the continuous development of information technology, applying automatic learning and self-learning methods such as machine learning and neural networks to the knowledge acquisition process of the knowledge base, becomes the trend and direction of the current knowledge base development. This paper describes the development of the self-learning knowledge base and technical methods, and practices the whole process of the database construction, neural network construction, neural network training process, experimental application of self-learning knowledge base, achieves the desired goal. It lays the foundation for the construction and practice of the self learning knowledge base in the broader knowledge field.
Projected Stochastic Primal-Dual Method for Constrained Online Learning With Kernels

We consider the problem of stochastic optimization with nonlinear constraints, where the decision variable is not vector-valued but instead a function belonging to a reproducing Kernel Hilbert Space (RKHS). Currently, there exist solutions to only special cases of this problem. To solve this constrained problem with kernels, we first generalize the Representer Theorem to a class of saddle-point problems defined over RKHS. Then, we develop a primal-dual method which that executes alternating projected primal/dual stochastic gradient descent/ascent on the dual-augmented Lagrangian of the problem. The primal projection sets are low-dimensional subspaces of the ambient function space, which are greedily constructed using matching pursuit. By tuning the projection-induced error to the algorithm step-size, we are able to establish mean convergence in both primal objective sub-optimality and constraint violation, to respective <inline-formula><tex-math notation="LaTeX">${\mathcal O}(\sqrt{T})$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">${\mathcal O}(T^{3/4})$</tex-math></inline-formula> neighborhoods. Here, <inline-formula><tex-math notation="LaTeX">$T$</tex-math></inline-formula> is the final iteration index and the constant step-size is chosen as <inline-formula><tex-math notation="LaTeX">$1/\sqrt{T}$</tex-math></inline-formula> with <inline-formula><tex-math notation="LaTeX">$1/T$</tex-math></inline-formula> approximation budget. Finally, we demonstrate experimentally the effectiveness of the proposed method for risk-aware supervised learning.
Carrier Aggregation for Underlay Cognitive Radio Wireless Mesh Networks

Cognitive radio (CR) has emerged as a promising technology to solve the tremendous spectrum scarcity problem. Although CR has shown very interesting results, it is still dealing with some drawbacks such as blocking or forced termination events in opportunistic mode and capacity limitation in underlay mode. In this paper carrier aggregation is proposed for wireless mesh networks to enhance the network throughput in underlay CR condition. In the proposed scenario, the primary user uses traditional channels whereas the secondary user aggregates carriers in PU's channels for its transmission. An analytical performance study is carried out which shows the effectiveness of our proposal. With relatively few aggregated carriers per channel, carrier aggregation outperforms single channel and channel aggregation due to its higher detection probability. These results can be used to extend the already well known properties of wireless mesh networks and their applications.
SC-FDE Based MIMO Uplink Transmission Over Infrared Communication Channels

In this paper, we propose a multiple-input multiple-output (MIMO) uplink transmission scheme for optical wireless communication applications. The transmission is based on optical single-carrier frequency domain equalization (SC-FDE) due to its low complexity where the signal is transmitted over infrared communication channels. Based on non-sequential ray tracing, we first obtained realistic infrared MIMO channel impulse responses including low-pass filter effect of infrared light-emitting-diodes. We then investigate the performance of bit-error-rate (BER) and peak to average power ratio (PAPR) with respect to different modulation orders using spatial multiplexing.
Humans and Algorithms Detecting Fake News: Effects of Individual and Contextual Confidence on Trust in Algorithmic Advice

Abstract Algorithms have become part of our daily lives and have taken over many decision-making processes. It has often been argued and shown that algorithmic judgment can be as accurate or even more accurate than human judgement. However, humans are reluctant to follow algorithmic advice, especially when they do not trust the algorithm to be better than they are themselves: self-confidence has been found as one factor that influences the willingness to follow algorithmic advice. However, it is unknown whether this is an individual or a contextual characteristic. The current study analyses whether individual or contextual factors determine whether humans are willing to request algorithmic advice, to follow algorithmic advice, and whether their performance improves given algorithmic advice. We consider the use of algorithmic advice in fake news detection. Using data from 110 participants and 1610 news stories of which almost half were fake, we find that humans without algorithmic advice correctly assess the news stories 64% of the time. This only marginally increases to 66% after they have received feedback from an algorithm that itself is 67% correct. The willingness to accept advice indeed decreases with participants’ self-confidence in the initial assessment, but this effect is contextual rather than individual. That is, participants who are on average more confident accept advice just as often as those who are on average less confident. What does hold, however, is that a participant is less likely to accept algorithmic advice for the news stories about which that participant is more confident We outline the implications of these findings for the design of experimental tests of algorithmic advice and give general guidelines for human-algorithm interaction that follow from our results.
Adesão à terapêutica anti-retroviral por indivíduos com HIV/AIDS assistidos em uma instituição do interior paulista

Inadequate adherence to highly active anti-retroviral therapy (HAART) provokes important secondary effects in people living with aids. The objective was to identify the factors that make HAART adherence easy or difficult, according to aids patients attended at a university hospital in the state of Sao Paulo, Brazil. We interviewed 200 diagnosed aids patients using HAART for at least 6 months. Patients were interviewed individually, using a semi-structured design. Qualitative and quantitative analysis was used. 59% of the participants were men; average age was 38.2 years; 51% did not finish basic education; 50.5% did not perform any remunerated work. Patients had been using anti-retroviral agents for an average time of 5 years. The number of anti-retroviral pills ranged from 3 to 24. The main difficulties mentioned for adherence were: taste, size, number, smell of pills (40.0%); intense collateral effects (14.4%); psychological factors (13.7%); different times to take the pills (10.8%). Patients mentioned the following facilitators: coincidence of times to take the drugs (26.2%), no facility (16.4%), and administration associated to some habit (16.0%). The nursing group needs to reinforce supervised surveillance, educational and intervention actions.
Dyslipidaemia Is Associated with Severe Disease Activity and Poor Prognosis in Ulcerative Colitis: A Retrospective Cohort Study in China

Background: Clinical data on the correlation of dyslipidaemia with the long-term outcomes of ulcerative colitis (UC) are limited. This study aimed to evaluate the impact of lipid levels on disease activity and prognosis in UC. Methods: The retrospective data of UC patients who had detailed lipid profiles were collected from January 2003 to September 2020. All patients were followed-up to 30 September 2021. The long-term outcomes were UC-related surgery and tumorigenesis. Results: In total, 497 patients were included in the analysis. Compared to patients with normal lipid levels, those with dyslipidaemia commonly presented with more serious disease activity. Low high-density lipoprotein cholesterol (p < 0.05) levels were associated with higher risks of severe disease activity in UC. Regarding the long-term outcomes, patients with persistent dyslipidaemia were at higher risks of UC-related surgery (HR: 3.27, 95% CI: 1.86–5.75, p < 0.001) and tumorigenesis (HR: 7.92, 95% CI: 3.97–15.78, p < 0.001) and had shorter surgery- and tumour-free survival (p < 0.001) than patients with transient dyslipidaemia and normal lipid levels. Low levels of high-density lipoprotein cholesterol (p < 0.001) and apolipoprotein A1 (p < 0.05) were associated with higher risks of surgery and tumorigenesis. Conclusion: Persistent dyslipidaemia was associated with a higher risk of serious disease activity and worse long-term outcomes among patients with UC. Lipid patterns should be assessed to improve the management of high-risk patients with UC in the early phase.