Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Cytoskeletal Proteins in the Formation of a Functional In Vitro Blood-Brain Barrier Model

The brain capillary endothelium is highly regulatory, maintaining the chemical stability of the brain’s microenvironment. The role of cytoskeletal proteins in tethering nanotubules (TENTs) during barrier-genesis was investigated using the established immortalized mouse brain endothelial cell line (bEnd5) as an in vitro blood-brain barrier (BBB) model. The morphology of bEnd5 cells was evaluated using both high-resolution scanning electron microscopy and immunofluorescence to evaluate treatment with depolymerizing agents Cytochalasin D for F-actin filaments and Nocodazole for α-tubulin microtubules. The effects of the depolymerizing agents were investigated on bEnd5 monolayer permeability by measuring the transendothelial electrical resistance (TEER). The data endorsed that during barrier-genesis, F-actin and α-tubulin play a cytoarchitectural role in providing both cell shape dynamics and cytoskeletal structure to TENTs forming across the paracellular space to provide cell-cell engagement. Western blot analysis of the treatments suggested a reduced expression of both proteins, coinciding with a reduction in the rates of cellular proliferation and decreased TEER. The findings endorsed that TENTs provide alignment of the paracellular (PC) spaces and tight junction (TJ) zones to occlude bEnd5 PC spaces. The identification of specific cytoskeletal structures in TENTs endorsed the postulate of their indispensable role in barrier-genesis and the maintenance of regulatory permeability across the BBB.
A “Double-Locked” and Enzyme/pH-Activated Theranostic Agent for Accurate Tumor Imaging and Therapy

Theranostic agents for concurrent cancer therapy and diagnosis have begun attracting attention as a promising modality. However, accurate imaging and identification remains a great challenge for theranostic agents. Here, we designed and synthesized a novel theranostic agent H6M based on the “double-locked” strategy by introducing an electron-withdrawing nitro group into 1-position of a pH-responsive 3-amino-β-carboline and further covalently linking the hydroxamic acid group, a zinc-binding group (ZBG), to the 3-position of β-carboline to obtain histone deacetylase (HDAC) inhibitory effect for combined HDAC-targeted therapy. We found that H6M can be specifically reduced under overexpressed nitroreductase (NTR) to produce H6AQ, which emits bright fluorescence at low pH. Notably, H6M demonstrated a selective fluorescence imaging via successive reactions with NTR (first “key”) and pH (second “key”), and precisely identified tumor margins with a high S/N ratio to guide tumor resection. Finally, H6M exerted robust HDAC1/cancer cell inhibitory activities compared with a known HDAC inhibitor SAHA. Therefore, the NTR/pH-activated theranostic agent provided a novel tool for precise diagnosis and efficient tumor therapy.
Dietary Fat and Polyunsaturated Fatty Acid Intakes during Childhood Are Prospectively Associated with Puberty Timing Independent of Dietary Protein

Dietary fat and fat quality have been inconsistently associated with puberty timing. The aim of this study was to investigate the prospective associations of dietary fat, saturated fatty acid (SFA), polyunsaturated fatty acid (PUFA), and monounsaturated fatty acid (MUFA) with puberty timing. Using longitudinal data from China Health and Nutrition Survey (CHNS) and Southwest China Childhood Nutrition and Growth (SCCNG) Study, we analyzed dietary data, anthropometric measurements, and potential confounders. Dietary intakes were assessed by 3-day 24-h recalls. Age at Tanner stage 2 for breast/genital development (B2/G2) and age at menarche/voice break (M/VB) were used as puberty development markers. Cox proportional hazard regression models were used to estimate the relevance of dietary intake of total fat, SFA, PUFA, and MUFA on puberty timing. Among 3425 girls and 2495 boys, children with higher intakes of total fat and PUFA were more likely to reach their B2/G2 or M/VB at an earlier age. Associations were not attenuated on additional adjustment for childhood dietary protein intake. However, higher intakes of SFA or MUFA were not independently associated with puberty development. A higher intake of dietary fat and PUFA in prepuberty was associated with earlier puberty timing, which was independent of dietary protein intake.
Are growth effects of foreign capital significant for increasing access to electricity in Africa?

: Despite the advancements towards Sustainable Development Goal 7, access to electricity in Africa is still lagging far behind the goal. In this study, we employ a panel data covering 36 African countries from 2000 to 2017 to investigate the effects of FDI, remittances and foreign aid on access to electricity. We use a dynamic empirical model based on system GMM to control for unobserved heterogeneity and potential endogeneity of the explanatory variables. The results show that FDI and remittances matter for increasing access to electricity. Also, foreign aid reduces access to electricity. We also find that remittances reduce urban-rural disparities in access to electricity, while FDI and foreign aid increase disparities. Finally, these results remain globally robust when we perform sub-regional analyses.
Artificial Bee Colony for Affine and Perspective Template Matching

In this study, the artificial bee colony (ABC) algorithm was improved to achieve higher accuracy than the latest method in affine (6 DoF) and perspective (8 DoF) template matching. Inheritance of crossover probability and new mutation strategies that improve exploitation are introduced to employed and onlooker bees. In addition, a scout bee that requires no hyperparameters is proposed. Through experiments and quantitative evaluation, we confirmed that the improved ABC achieves more accurate matching and shorter processing time than the latest method based on differential evolution. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
A framework to evaluate multi-use flexibility concepts simultaneously in a co-simulation environment and a cyber-physical laboratory.

In this paper, we present an approach for a framework to test multi-use concepts for the coordination of flexibility resources in distribution grids. The framework allows testing in a large scale co-simulation environment, but also our cyber-physical smart grid laboratory. At the core of the proposed framework is the newly proposed design of a Virtual Edge Device (VED) to control either real or simulated flexibility resources. The VED is also provided for the interchangeable use of simulated and physical components with the same coordination logic. To tackle the questions of cyber resilience and cybersecurity, not only the energy system is taken into account but also the underlying Information and Communication Technology (ICT). Therefore, the ICT components are emulated in the co-simulation and mapped by corresponding components in the laboratory. We validate the environment by simulating and analysing three different use-cases, comprising local congestion management and battery dispatch optimisation. Our tests prove that our laboratory is suitable for a future application of the analysis and development of multi-use flexibility concepts.
Strain Induced by Bio-High-Performance Polymers and Cobalt-Chromium Digitally Constructed Telescopic Partial Dentures after 1 Year Simulation of Function

BACKGROUND: Numerous attempts were made to reduce the adverse effects of the distal extension removable partial dentures (RPDs) and enhance their prognosis. High-performance polymers (HPP) were utilized in the construction of RPDs to maintain the health of the supporting structures. AIM: Thus, this study was prompted to compare the strains induced by Bio HPP and Cobalt- Chromium (Co Cr) Computer Assisted Design and Computer Assisted Manufacturing telescopic RPDs after 1 year of function. MATERIALS AND METHODS: A maxillary Kennedy class I was used in this study. Twelve telescopic RPDs were fabricated from two different materials. In Group A, six telescopic RPDs were milled from Co-Cr and in Group B, six telescopic retained RPDs were milled from Bio-HPP. Each partial denture was seated on the cast and introduced into the chewing simulator. The strain values were recorded using four strain gauges connected to a four-channel strain indicator. Statistical analysis of the resultant data was done using one-way ANOVA, followed by Tukey’s HSD for comparison within the same group. Student t-test was used for comparison between the different groups. The significance level was set at p ≤ 0.05. RESULTS: During unilateral loading, the results showed higher strains in Group A at the abutments (473.33 μm/m ± 10.8, 193.39 μm/m ± 10.8) and at the distal aspect of the ridge (470.83 μm/m ± 13.93, 185 μm/m ± 20.83) than Group B. Independent t-test showed statistically significant difference between strains at the abutments of both groups (t = 70.4, p ≤ 0.0001), (t = 36.84, p ≤ 0.0001). Furthermore, there was a statistically significant difference between strains at the saddles of both groups (t = 51.62, p ≤ 0.0001), (t = 34.72, p ≤ 0.0001) respectively (DOF = 10). CONCLUSIONS: In telescopic RPDs, Co Cr induces higher strain values on the abutments and the distal aspect of the ridge than Bio-HPP during bilateral and unilateral loading. During unilateral loading, Bio-HPP telescopic RPDs direct high strain values on the distal aspect of the ridge of the loaded side. CLINICAL IMPLICATIONS: The materials that induce less stresses on the supporting structures of telescopic partial dentures on the long-term can be used to maintain the health of periodontally affected abutments.
Remote Psychological Interventions for Fear of Cancer Recurrence: Scoping Review

Background Patients with cancer and survivors may experience the fear of cancer recurrence (FCR), a preoccupation with the progression or recurrence of cancer. During the spread of COVID-19 in 2019, patients and survivors experienced increased levels of FCR. Hence, there is a greater need to identify effective evidence-based treatments to help people cope with FCR. Remotely delivered interventions might provide a valuable means to address FCR in patients with cancer. Objective The aim of this study is to first discuss the available psychological interventions for FCR based on traditional cognitive behavioral therapies (CBTs) or contemporary CBTs, in particular, mindfulness and acceptance and commitment therapy, and then propose a possible approach based on the retrieved literature. Methods We searched key electronic databases to identify studies that evaluated the effect of psychological interventions such as CBT on FCR among patients with cancer and survivors. Results Current evidence suggests that face-to-face psychological interventions for FCR are feasible, acceptable, and efficacious for managing FCR. However, there are no specific data on the interventions that are most effective when delivered remotely. Conclusions CBT interventions can be efficacious in managing FCR, especially at posttreatment, regardless of whether it is delivered face to face, on the web, or using a blended approach. To date, no study has simultaneously compared the effectiveness of face-to-face, web-based, and blended interventions. On the basis of the retrieved evidence, we propose the hypothetical program of an intervention for FCR based on both traditional CBT and contemporary CBT, named Change Of Recurrence, which aims to improve the management of FCR in patients with cancer and survivors.
Uncertainty–guided learning with scaled prediction errors in the basal ganglia

To accurately predict rewards associated with states or actions, the variability of observations has to be taken into account. In particular, when the observations are noisy, the individual rewards should have less influence on tracking of average reward, and the estimate of the mean reward should be updated to a smaller extent after each observation. However, it is not known how the magnitude of the observation noise might be tracked and used to control prediction updates in the brain reward system. Here, we introduce a new model that uses simple, tractable learning rules that track the mean and standard deviation of reward, and leverages prediction errors scaled by uncertainty as the central feedback signal. We provide a normative analysis, comparing the performance of the new model with that of conventional models in a value tracking task. We find that the new model has an advantage over conventional models when tested across various levels of observation noise. Further, we propose a possible biological implementation of the model in the basal ganglia circuit. The scaled prediction error feedback signal is consistent with experimental findings concerning dopamine prediction error scaling relative to reward magnitude, and the update rules are found to be consistent with many features of striatal plasticity. Our results span across the levels of implementation, algorithm, and computation, and might have important implications for understanding the dopaminergic prediction error signal and its relation to adaptive and effective learning. Author Summary The basal ganglia system is a collection of subcortical nuclei in the mammalian brain. This system and its dopaminergic inputs are associated with learning from rewards. Here, dopamine is thought to signal errors in reward prediction. The structure and function of the basal ganglia system are not fully understood yet—for example, the basal ganglia are split into two antagonistic pathways, but the reason for this split and the role of the two pathways are unknown. Further, it has been found that under some circumstances, rewards of different sizes lead to dopamine responses of similar size, which cannot be explained with the reward prediction error theory. Here, we propose a new model of learning in the basal ganglia—the scaled prediction error model. According to our model, both reward average and reward uncertainty are tracked and represented in the two basal ganglia pathways. The learned reward uncertainty is then used to scale dopaminergic reward prediction errors, which effectively renders learning adaptive to reward noise. We show that such learning is more robust than learning from unscaled prediction errors and that it explains several physiological features of the basal ganglia system.
Recent Achievements on Grating Fabrications in Polymer Optical Fibers with Photosensitive Dopants: A Review

This review discusses recent achievements on grating fabrications in polymer optical fibers doped with photosensitive materials. First, different photosensitive dopants in polymer optical fibers (POFs) are summarized, and their refractive index change mechanisms are discussed. Then, several different doping methods to fabricate the photosensitive POFs are presented. Following that, the principles of gratings, including standard fiber Bragg gratings (FBGs), tilted fiber Bragg gratings (TFBGs), chirped fiber Bragg gratings (CFBGs), phase-shifted fiber Bragg gratings (PSFBGs), and long period fiber gratings (LPFGs), are reported. Finally, fabrications of different gratings based on photosensitive POFs in the last 20 years are reported. We present our article clearly and logically, so that it will be helpful for researchers to explore a broad perspective on this proposed topic. Overall, the content provides a comprehensive overview of photosensitive POF fabrications and grating inscriptions in photosensitive POFs, including previous breakthroughs and recent advancements.
Deep Reinforcement Learning-based Network Slicing for Beyond 5G

With the advent of 5G era, network slicing has received a great deal of attention as a means to support a variety of wireless services in a flexible manner. Network slicing is a technique to divide a single physical resource network into multiple slices supporting independent services. In beyond 5G (B5G) systems, the main goal of network slicing is to assign the physical resource blocks (RBs) such that the quality of service (QoS) requirements of eMBB, URLLC, and mMTC services are satisfied. Since the goal of each service category is dearly distinct and the computational burden caused by the increased number of time slots is huge, it is in general very difficult to assign each RB to a certain service properly. In this paper, we propose a deep reinforcement learning (DRL)-based network slicing technique to find out the resource allocation policy maximizing the long-term throughput while satisfying the QoS requirements in the B5G systems. Key ingredient of the proposed technique is to use action elimination to eliminate undesirable actions that cannot satisfy the QoS requirements. Numerical results demonstrate that the proposed technique is effective in maximizing the long-term throughput and handling the coexistence of use cases in the B5G environments.
Studying Activated Fibroblast Phenotypes and Fibrosis-Linked Mechanosensing Using 3D Biomimetic Models.

Fibrosis and solid tumor progression are closely related, with both involving pathways associated with chronic wound dysregulation. Fibroblasts contribute to extracellular matrix (ECM) remodeling in these processes, a crucial step in scarring, organ failure, and tumor growth, but little is known about the biophysical evolution of remodeling regulation during the development and progression of matrix-related diseases including fibrosis and cancer. This study employed a 3D collagen-based scaffold model to mimic mechanical changes in normal (2 kPa, soft) versus advanced pathological (12 kPa, stiff) tissues. Activated fibroblasts grown on stiff scaffolds show lower migration and increased cell circularity compared to those on soft scaffolds. This is reflected in gene expression profiles, with cells cultured on stiff scaffolds showing upregulated DNA replication, DNA repair, and chromosome organization gene clusters, and a concomitant loss of ability to remodel and deposit ECM. Soft scaffolds can reproduce biophysically meaningful microenvironments to investigate early-stage processes in wound healing and tumor niche formation, while stiff scaffolds can mimic advanced fibrotic and cancer stages. These results establish the need for tunable, affordable 3D scaffolds as platforms for aberrant stroma research and reveal the contribution of physiological and pathological microenvironment biomechanics to gene expression changes in the stromal compartment. This article is protected by copyright. All rights reserved.
Network Inspection Using Heterogeneous Sensors for Detecting Strategic Attacks

We consider a two-player network inspection game, in which a defender allocates sensors with potentially heterogeneous detection capabilities in order to detect multiple attacks caused by a strategic attacker. The objective of the defender (resp. attacker) is to minimize (resp. maximize) the expected number of undetected attacks by selecting a potentially randomized inspection (resp. attack) strategy. We analytically characterize Nash equilibria of this large-scale zero-sum game when every vulnerable network component can be monitored from a unique sensor location. We then leverage our equilibrium analysis to design a heuristic solution approach based on minimum set covers for computing inspection strategies in general. Our computational results on a benchmark cyber-physical distribution network illustrate the performance and computational tractability of our solution approach.
Unrestricted Attention may not Be All You Need - Masked Attention Mechanism Focuses Better on Relevant Parts in Aspect-Based Sentiment Analysis

Aspect-Based Sentiment Analysis (ABSA) is one of the highly challenging tasks in natural language processing. It extracts fine-grained sentiment information in user-generated reviews, as it aims at predicting the polarities towards predefined aspect categories or relevant entities in free text. Previous deep learning approaches usually rely on large-scale pre-trained language models and the attention mechanism, which applies the complete computed attention weights and does not place any restriction on the attention assignment. We argue that the original attention mechanism is not the ideal configuration for ABSA, as for most of the time only a small portion of terms are strongly related to the sentiment polarity of an aspect or entity. In this paper, we propose a masked attention mechanism customized for ABSA, with two different approaches to generate the mask. The first method sets an attention weight threshold that is determined by the maximum of all weights, and keeps only attention scores above the threshold. The second selects the top words with the highest weights. Both remove the lower score parts that are assumed to be less relevant to the aspect of focus. By ignoring part of input that is claimed irrelevant, a large proportion of input noise is removed, keeping the downstream model more focused and reducing calculation cost. Experiments on the Multi-Aspect Multi-Sentiment (MAMS) and SemEval-2014 datasets show significant improvements over state-of-the-art pre-trained language models with full attention, which displays the value of the masked attention mechanism. Recent work shows that simple self-attention in Transformer quickly degenerates to a rank-1 matrix, and masked attention may be another cure for that trend.
Aerodynamic drag reduction of van based on underbody skirt

The principles and method of computational fluid dynamics were applied to numerical simulate the external flow field about the simplified geometrical model of a made-in-china van.The hybrid mesh of tetrahedral,triangular prismatic,pyramidal and hexahedral elements as well as the turbulence model of Realizable k-e was adopted to study the flow field of trucks with 4 styles,9 kinds of underbody skirt and no skirt.The aerodynamic characteristics of all the models were calculated and postprocessed including aerodynamic drag coefficients,surface pressure,streamlines and velocity vectors.The flow characteristics and aerodynamic drag coefficients were compared and analyzed among the different models with and without underbody skirt.The results show that the aerodynamic characteristics will be improved and the drag coefficients will be reduced when adding underbody skirts.