Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of paclitaxel loaded pegylated gelatin targeted nanoparticles for improved treatment efficacy in non-small cell lung cancer (NSCLC): an in vitro and in vivo evaluation study.

PURPOSE To develop and evaluate paclitaxel (PTX) loaded pegylated gelatin targeted nanoparticles for improved efficacy in non-small cell lung cancer (NSCLC) treatment. METHOD PTX loaded gelatin nanoparticles (PTX-GNP) were prepared by crosslinking with glutaraldehyde aqueous solution. These nanoparticles (NPs) were further incubated with PEG 400 to form PEGylated NPs (PEG-PTX-GNP). The NPs were evaluated for surface morphology, size, zeta potential, encapsulation efficiency, drug loading, in vitro drug release, cytotoxicity in an assay on cancer cell lines L132, in vitro cellular uptake in an assay in L132 and 293T cell lines, in vivo antitumor activity on female Balb/c mice, pulmonary deposition, histopathology, and immunohistochemical properties. RESULTS The nanoparticles were of spherical shape with smooth surface characteristics. The observed DL was of 20.18 to 32.11%, as particle size was of 90 to 115 nm. Zeta potential and polydispersity index (PDI) were within acceptable ranges. Encapsulation was effective when the NPs had a size of 80.50 nm to 98.12 nm. The PEGylated PTX loaded nanoparticles (PEG-PTX-GNP, GNP4) showed similar PTX release profile to that of the NP4 formulation. PEGylated NPs showed the desired PTX release pattern that is required for cancer treatment. In an in vitro cytotoxicity study, PEG-PTX-GNP showed the maximum antiproliferative activity over the period of 24 hours, followed by PTX-GNP, pure PTX and BPEG-GNP. PEG-PTX-GNP showed the highest internalization within both cell lines, followed by PTX-GNP and pure PTX. The survival rate of animals in PEG-PTX-GNP group was 100%, proving the safety and efficacy of the treatment. PEG-PTX-GNP showed the highest antitumor activity as compared to other formulations. The pulmonary deposition rate was the highest (6.5 to 12.55 μg/g) in PEG-PTX-GNP formulations. Histopathology and immunohistochemical study proved that PEG-PTX-GNP had greater anticancer potential than other tested formulations. CONCLUSION This study confirms the potential use of paclitaxel loaded PEGylated gelatin targeted nanoparticles for improved efficacy in non-small cell lung cancer (NSCLC) treatment.
Comprehensive Workplace Policies and Practices Regarding Employee Opioid Use

The workplace is a key environment to impact employees, families, and communities to prevent further opioid and substance misuse, addiction, and overdose. However, it is often overlooked as an ideal location to launch a prevention intervention or support strategy. Employees in recovery, seeking treatment, and dealing with mental distress require employer support. Supports should consider the diversity of the work force and be culturally appropriate. Several data sources, tools, and other resources exist to aid employers in supporting their employees and addressing the opioid epidemic; a few from the National Safety Council are discussed. As well as suitable strategies to strengthen workplace prevention interventions and treatment access, in light of the opioid epidemic, coronavirus pandemic, and workplace disparities.
EBNA2 driven enhancer switching at the CIITA-DEXI locus suppresses HLA class II gene expression during EBV infection of B-lymphocytes

Viruses suppress immune recognition through diverse mechanisms. Epstein-Barr Virus (EBV) establishes latent infection in memory B-lymphocytes and B-cell malignancies where it impacts B-cell immune function. We show here that EBV primary infection of naïve B-cells results in a robust down-regulation of HLA genes. We found that the viral encoded transcriptional regulatory factor EBNA2 bound to multiple regulatory regions in the HLA locus. Conditional expression of EBNA2 correlated with the down regulation of HLA class II transcription. EBNA2 down-regulation of HLA transcription was found to be dependent on CIITA, the major transcriptional activator of HLA class II gene transcription. We identified a major EBNA2 binding site downstream of the CIITA gene and upstream of DEXI, a dexamethasone inducible gene that is oriented head-to-head with CIITA gene transcripts. CRISPR/Cas9 deletion of the EBNA2 site upstream of DEXI attenuated CIITA transcriptional repression. EBNA2 caused an increase in DEXI transcription and a graded change in histone modifications with activation mark H3K27ac near the DEXI locus, and a loss of activation marks at the CIITA locus. A prominent CTCF binding site between CIITA and DEXI enhancers was mutated and further diminished the effects of EBNA2 on CIITA. Analysis of HiC data indicate that DEXI and CIITA enhancers are situated in different chromosome topological associated domains (TADs). These findings suggest that EBNA2 down regulates HLA-II genes through the down regulation of CIITA, and that this down regulation is an indirect consequence of EBNA2 enhancer formation at a neighboring TAD. We propose that enhancer competition between these neighboring chromosome domains represents a novel mechanism for gene regulation demonstrated by EBNA2.
Effects on Life‐History Traits of Hypogastrura viatica (Collembola) Exposed to Imidacloprid Through Soil or Diet

Collembola (springtails) are important members of soil communities worldwide by contributing to degradation of organic matter. In nature, Collembola might be exposed to the neonicotinoid insecticide imidacloprid, which is fairly persistent in soil. We exposed the widespread Hypogastrura viatica to imidacloprid through soil or food and monitored the animals during exposure and a post exposure period. We recorded effects on life‐history traits affecting individual fitness, that is, mortality, behavioral activity, several reproduction traits, and molting frequency. Exposure through soil led to a concentration‐dependent mortality, while the mortality from dietary exposure possibly reflected reduced feeding activity. The body burden of imidacloprid in the Collembola did not differ between treatments. We found no sign of recovery in behavioral activity following exposure in either experiment. The egg production of H. viatica was not significantly affected by imidacloprid at 0.01 mg/kg dry soil but showed a tendency to reduce number of eggs per batch and reduced hatching success. At higher concentrations, reproduction was close to, or completely, stopped. The molting frequency decreased during exposure, while in the post exposure period, we saw milder effects at the highest concentrations, suggesting elimination through molting or reduced toxic response as a result of reduced feeding activity. Overall, H. viatica was more sensitive to imidacloprid than previously studied Collembola, which highlights the importance of considering species sensitivities when risk‐assessing soil environments. Environ Toxicol Chem 2021;40:3111–3122. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Effects of shear stress on the secretion of extracellular polymeric substances in biofilms

Movement of biofilm into the suspended state as a result of erosion and sloughing is inevitable. The causes for this have been widely attributed to the presence of high shear stress, excess nutrients or a combination of both parameters. It is believed that the extracellular polymeric substances (EPS) of biofilm contribute to the mechanical stability of the biofilm; however, the effect of changing shear stress on the secretion of biofilm EPS is not well understood. This research examined the EPS of a biofilm quantitatively during the change in shear stress. Biofilm was grown in a rotating drum biofilm reactor and subjected to three different shear stresses: 0.1022 N/m 2 at 100 rpm, 0.1533 N/m 2 at 150 rpm and 0.2044 N/m 2 at 200 rpm. Results indicate that a sudden increase of shear stress caused a drastic increase of the EPS-polysaccharides in the biofilm. However, 20 days after each shear increase, the EPS-polysaccharides secretion dropped back to the previous values before the shear change. Physical properties of the biofilm such as porosity were also monitored and the result showed that higher shear stress produced less porous but denser biofilm. Another notable effect when the shear stress was increased was that more erosion of biofilm occurred.
Acoustic component programming in children with cochlear implants using electrocochleography

Abstract Objective Objective measurements improve reliability and effectiveness of hearing assessment and cochlear implant (CI) programming in young children. In CI recipients with acoustic hearing in the implanted ear, electrocochleography (ECochG) can be conducted using intracochlear electrodes. The cochlear microphonic (CM) portion of ECochG has been shown to correlate with pure-tone audiometric thresholds in adult and paediatric CI recipients. Our goal was to determine if ECochG thresholds can be used to appropriately fit the acoustic component to the implanted ear in children. Design Prospective. Study sample Eight children (aged 3.5–15.5 years, 10 ears) implanted with Advanced Bionics HiFocus Mid-Scala electrode array were recruited. CI ear acoustic thresholds were measured behaviourally and via ECochG. Two acoustic component enabled CI programs were created using the two sets of thresholds. Age and language appropriate speech outcomes and subjective feedback were obtained. Results Speech scores were equivalent with the behavioural and ECochG thresholds programs. Subjectively, the ECochG thresholds program was preferred by 7/8 subjects. One subject preferred to use an electric only program. Conclusion Our data suggest that ECochG thresholds can be used to supplement the behavioural clinical methods and aid the reliable fitting of the acoustic component in paediatric CI recipients.
Identification of BiP as a CB1 Receptor-Interacting Protein That Fine-Tunes Cannabinoid Signaling in the Mouse Brain

Cannabinoids, the bioactive constituents of cannabis, exert a wide array of effects on the brain by engaging Type 1 cannabinoid receptor (CB1R). Accruing evidence supports that cannabinoid action relies on context-dependent factors, such as the biological characteristics of the target cell, suggesting that cell population-intrinsic molecular cues modulate CB1R-dependent signaling. Here, by using a yeast two-hybrid-based high-throughput screening, we identified BiP as a potential CB1R-interacting protein. We next found that CB1R and BiP interact specifically in vitro, and mapped the interaction site within the CB1R C-terminal (intracellular) domain and the BiP C-terminal (substrate-binding) domain-α. BiP selectively shaped agonist-evoked CB1R signaling by blocking an “alternative” Gq/11 protein-dependent signaling module while leaving the “classical” Gi/o protein-dependent inhibition of the cAMP pathway unaffected. In situ proximity ligation assays conducted on brain samples from various genetic mouse models of conditional loss or gain of CB1R expression allowed to map CB1R-BiP complexes selectively on terminals of GABAergic neurons. Behavioral studies using cannabinoid-treated male BiP+/− mice supported that CB1R-BiP complexes modulate cannabinoid-evoked anxiety, one of the most frequent undesired effects of cannabis. Together, by identifying BiP as a CB1R-interacting protein that controls receptor function in a signaling pathway- and neuron population-selective manner, our findings may help to understand the striking context-dependent actions of cannabis in the brain. SIGNIFICANCE STATEMENT Cannabis use is increasing worldwide, so innovative studies aimed to understand its complex mechanism of neurobiological action are warranted. Here, we found that cannabinoid CB1 receptor (CB1R), the primary molecular target of the bioactive constituents of cannabis, interacts specifically with an intracellular protein called BiP. The interaction between CB1R and BiP occurs selectively on terminals of GABAergic (inhibitory) neurons, and induces a remarkable shift in the CB1R-associated signaling profile. Behavioral studies conducted in mice support that CB1R-BiP complexes act as fine-tuners of anxiety, one of the most frequent undesired effects of cannabis use. Our findings open a new conceptual framework to understand the striking context-dependent pharmacological actions of cannabis in the brain.
Evolution-inspired redesign of the LPS receptor caspase-4 into an interleukin-1β–converting enzyme

Caspase-4 homologs can naturally evolve or be synthetically engineered to directly link cytosolic LPS detection to IL-1β secretion. Multitasking by caspases Caspases are innate immune enzymes that regulate activation of inflammasomes and cell death occurring via pyroptosis. Devant et al. investigated the biological activity of naturally occurring hybrid caspase molecules in dogs containing separate domains related to human caspase-1 and -4. The canine caspase-1/4 hybrid lacked the LPS-sensing ability of human caspase-4 but retained the interleukin-1β (IL-1β)–cleaving activity of caspase-1. These observations enabled engineering of modified versions of human caspase-4 that acquired caspase-1 functions. A survey of carnivoran species revealed that the naturally occurring feline caspase-1/4 hybrid could mediate both caspase-1 and -4 functions without requiring inflammasome activation as an intermediate step. These findings demonstrate the plasticity of caspase domains and the ability of a single caspase protein to directly connect LPS detection to IL-1β cleavage. Innate immune signaling pathways comprise multiple proteins that promote inflammation. This multistep means of information transfer suggests that complexity is a prerequisite for pathway design. Here, we test this hypothesis by studying caspases that regulate inflammasome-dependent inflammation. Several caspases differ in their ability to recognize bacterial lipopolysaccharide (LPS) and cleave interleukin-1β (IL-1β). No caspase is known to contain both activities, yet distinct caspases with complementary activities bookend an LPS-induced pathway to IL-1β cleavage. Using caspase-1/4 hybrid proteins present in canines as a guide, we identified molecular determinants of IL-1β cleavage specificity within human and murine caspase-1. This knowledge enabled the redesign of human caspase-4 to operate as a one-protein signaling pathway, which intrinsically links LPS detection to IL-1β cleavage and release, independent of inflammasomes. We identified caspase-4 homologs in multiple carnivorans that display the activities of redesigned human caspase-4. These findings illustrate natural signaling pathway diversity and highlight how multistep innate immune pathways can be condensed into a single protein.
Vision-based classification of mosquito species: data augmentation by background replacement for convolutional neural network-based species classification of smashed mosquitoes

This study proposes a method of data augmentation by background replacement for the species classification of smashed mosquitoes using convolutional neural networks (CNNs). To augment data from a limited number of images of smashed mosquitoes, varieties of foreground mosquito and background are ensured by clipping a foreground mosquito image and pasting it into different backgrounds. For the background images, a white image is prepared as the ideal background, and a hand palm image is assumed as the background for practical use. Images extracted from three publicly available datasets are also prepared, which are considered as the variable backgrounds. A CNN-based deep classification is used with three types of architecture, and the classification accuracy is compared using training images corresponding to different background conditions. The classification accuracy using training images with a variety of backgrounds is better than that with a white or palm background. Moreover, deep classification with a residual network achieves the highest classification accuracy. The results of this work show that the species classification of the smashed mosquitoes can be achieved by using datasets with the proposed data augmentation method.
Training PointNet for human point cloud segmentation with 3D meshes

PointNet, which enables end-to-end learning for scattered/unordered point data, is a popular neural network architecture. However, in many applications, large amounts of complete point clouds are hardly available for non-rigid objects such as the human body. To generate the training data of PointNet, in this study, we propose to generate human body point clouds of various postures by uniformly sampling point clouds from meshes with respect to multiple human mesh model datasets. Experiments show that the model trained with the point clouds generated from mesh data is effective in the task of human body segmentation.
Human detection from low-resolution video images using 3D convolutional neural network

In this paper, we propose a method for human detection from low-resolution camera images. The proposed method uses video images as input and uses 3D-CNN for classification, which is an extension of 2D-CNN and that can take into account temporal features such as gait motion. In our experiments, we used Caltech Pedestrian Detection Benchmark to make datasets of low-resolution still and video images and compared the performance between 2D-CNN and 3D-CNN. As a result, 3D-CNN with low-resolution video images achieved 91.8 % accuracy rate, 99.0 % precision rate, and 82.8 % recall rate, and showed higher performance than 2D-CNN with low-resolution images, and comparable performance than 2D-CNN with high-resolution images.
NanoVDB: A GPU-Friendly and Portable VDB Data Structure For Real-Time Rendering And Simulation

We introduce a sparse volumetric data structure, dubbed NanoVDB, which is portable to both C++11 and C99 as well as most graphics APIs, e.g. CUDA, OpenCL, OpenGL, WebGL, DirectX 12, OptiX, HLSL, and GLSL. As indicated by its name, NanoVDB is a mini-version of the much bigger OpenVDB library, both in terms of functionality and scope. However, NanoVDB offers one major advantage over OpenVDB, namely support for GPUs. As such it is applicable to both CPU and GPU accelerated simulation and rendering of high-resolution sparse volumes. In fact, it has already been adopted for real-time applications by several commercial renders and digital content creation tools, e.g. Autodesk’s Arnold, Blender, SideFX’s Houdini, and NVIDIA’s Omniverse just to mention a few.
The Atmosphere of Raya and the Last Dragon

The cultures of South-east Asia provided plentiful inspiration for the setting and art direction in Walt Disney Animation Studios’ ”Raya and the Last Dragon”. This fantasy adventure required many unique environments ranging from desert landscapes to tropical forests, each describing rich lighting scenarios paired with the appropriate atmospherics. Many departments collaborated to create the extensive amount of atmospherics required by such varied and lush locations. Simultaneously, emphasis was placed on making the atmospheric Lighting workflow more efficient. We focused on improvements to allow Lighting artists more flexibility and control over making complicated atmospheric setups without having to request new assets or assistance from the Effects department on every shot. This in turn would save time and relieve significant production strain.
Developable Surface Segmentation For CAD Models

We present a novel method to segment CAD models into developable patches by detecting curve-like features on Gauss images of the corresponding patches. A region-growing approach is employed to detect planar and curved developable patches. The Gauss image of each segmented patch is constrained to be curve-like via principal component analysis and Pearson correlation analysis. Experimental results demonstrate that our approach generates nice results on CAD models with all kinds of developable surfaces.
Server-Language Processing: A Semi-Supervised approach to Server Failure Detection

As industrial systems continue to grow in terms of scale and complexity, having an effective as well as proactive failure management approach helps mitigate the impact of server failure. While supervised methods fail to perform well in real-world servers due to label noise in log data as well as their failure to detect unseen failures, unsupervised techniques are often too naive to differentiate between complex log structures. We propose a NLP based semi-supervised solution that learns the complex understanding of healthy and failure log patterns using an ensemble of deep learning based density and sequential solutions. Our hypothesis is that server logs follow a language of their own, which we attempt to decipher through Server-Language Processing. Experimental evaluations on real world log data show that our proposed solution outperforms other existing log-based anomaly detection methods for real world application. The solution was implemented for 3000 servers for 6 months of log data, and was able to pick up server failures upto 2 weeks in advance without raising an excess of false alarms.
Swish: Neural Network Cloth Simulation on Madden NFL 21

This work presents Swish, a real-time machine-learning based cloth simulation technique for games. Swish was used to generate realistic cloth deformation and wrinkles for NFL player jerseys in Madden NFL 21. To our knowledge, this is the first neural cloth simulation featured in a shipped game. This technique allows accurate high-resolution simulation for tight clothing, which is a case where traditional real-time cloth simulations often achieve poor results. We represent cloth detail using both mesh deformations and a database of normal maps, and train a simple neural network to predict cloth shape from the pose of a character’s skeleton. We share implementation and performance details that will be useful to other practitioners seeking to introduce machine learning into their real-time character pipelines.
Research on Data Collection Mechanism of Wireless Sensor Network Based on UAV

In recent years, Wireless Sensor networks (WSNs) have developed rapidly and have been widely used in various fields such as commerce, agriculture, military affairs and the environment. However, with the development of technology and the increasing demand of application scenarios, the limitations of WSNs are becoming more and more obvious. On the other hand, through continuous improvement, Unmanned Aerial Vehicle (UAV) technology has become more and more powerful, which can provide reliable, cost-effective services for people. The connectivity and energy efficiency of WSN can be significantly improved by taking advantage of UAV's high altitude hovering capability, communication capability and flexible mobility. Many researchers believe that UAV assisted communication in WSN is a promising solution. In this paper, we first discuss the limitations of WSN in certain scenarios and the advantages of UAV-assisted WSN. Secondly, the development and research status of UAV-assisted wireless sensor network communication are introduced. In this process, this paper introduces the research status of three data collection methods: data storage and forwarding UAV, mobile relay UAV and aerial base station UAV, and discusses the research progress in the field of wireless communication of UAV. Finally, this paper compares and analyzes the above three types of UAV-assisted sensor network data collection methods, and prospects the future research of UAV-assisted WSN.
Unbiased VNDF Sampling for Backfacing Shading Normals

Figure 1: Path tracing using Smith–GGX VNDF sampling [Heitz 2018] with previous normalization (upper row) and our normalization (lower row) for a normal-mapped scene (2048 spp, CPU: AMD RyzenTM 7 3800X). Right images are visualizations of the error and the VNDF integral. For backfacing shading normals, previous normalization produces a brightening bias. This is because the VNDF integral is less than one in these cases. We avoid this bias by correcting the normalization factor.