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Background: The rumen microbiome plays an essential role in maintaining ruminants’ growth and performance even under extreme environmental conditions, however, which factors influence rumen microbiome stability when ruminants are reared in such habitats throughout the year is unclear. Hence, the rumen microbiome of yak (less domesticated) and cattle (domesticated) reared on the Qinghai-Tibetan Plateau through the year were assessed to evaluate temporal changes in their composition, function, and stability. Results: Rumen fermentation characteristics and pH significantly shifted across seasons in both cattle and yak, but the patterns differed between the two ruminant species. Ruminal enzyme activity varied with season, and production of xylanase and cellulase was greater in yak compared to cattle in both fall and winter. The rumen bacterial community varied with season in both yak and cattle, with higher alpha diversity and similarity (beta diversity) in yak than cattle. The diversity indices of eukaryotic community did not change with season in both ruminant species, but higher similarity was observed in yak. In addition, the similarity of rumen microbiome functional community was higher in yak than cattle across seasons. Moreover, yak rumen microbiome encoded more genes (GH2 and GH3) related to cellulose and hemicellulose degradation compared to cattle, and a new enzyme family (GH160) gene involved in oligosaccharides was uniquely detected in yak rumen. The season affected microbiome attenuation and buffering values (stability), with higher buffering value in yak rumen microbiome than cattle. Positive correlations between antimicrobial resistance gene (dfrF) and CAZyme family (GH113) and microbiome stability were identified in yak, but such relationship was negatively correlated in cattle. Conclusions: The findings of the potential of cellulose degradation, the relationship between rumen microbial stability and the abundance of functional genes varied differentl

INTRODUCTION: Gut microbiota are associated with the health and performance of ruminant species, and they are affected by altitude, host genetics, and sex. However, there has been little research on comparing the fecal microbiota of indigenous small ruminants such as sheep and goats in Guizhou province, China. In the present study, we revealed the effect of altitude, genetics, and sex on fecal microbiota profiles and enterotypes in indigenous small ruminants of Guizhou province, China.METHODS: Fecal samples were collected from Hei and Qianbei Ma goats and Weining sheep in the Chinese province of Guizhou. 16S rRNA gene sequencing targeting the V3-V4 region was performed using the Illumina MiSeq platform. Sequences were processed using QIIME2, and the qualified sequences were processed using the plugin DADA2 to generate amplicon sequence variants (ASVs). The statistical analysis was performed using R studio.RESULTS: The fecal microbial profile was found to vary by herd (influenced by genetics/altitude) and sex. All samples were categorized into two enterotypes. The first enterotype is dominated by UCG-005, and the second enterotype is dominated by the Christensenellaceae_R-7_group, which may be highly driven by the host's genetics (breed). The predicted functional profiles of the fecal microbiota were also assigned to two clusters that corresponded exactly to the enterotypes. Cluster 1 of the functional profiling was characterized by biosynthesis pathways, and cluster 2 was characterized by energy metabolism pathways. DISCUSSION: Our findings may provide new insights into the fecal microbial community and enterotypes in small ruminants by herds, offering clues for understanding the mechanisms by which the fecal microbiota contribute to divergent host phenotypes in indigenous small ruminants in Guizhou.

Visual geo-localization using prior map of known environments has extensive applications in the fields such as self-driving, augmented reality and navigation. Currently, such prior maps are usually constructed by visual SLAM or SFM. However, the recent advances in LiDAR SLAM technology with RGB camera demonstrate great potential in efficient and accurate prior map construction and visual geo-localization. In this research, we developed a novel prior map construction approach which seamlessly integrates a handheld LiDAR SLAM system, a global LiDAR localization algorithm and a sparse set of terrestrial LiDAR scans as accurate control within a factor graph optimization framework. The developed LiDAR SLAM system augmented by terrestrial LiDAR scans achieves an improved mapping accuracy of 8 cm under GNSS-denied conditions in the areas over 50,000 m2 while the state-of-art FAST-LIO2 alone fails and produces a mapping error over 30 m. The results show that a competitive accuracy of visual geo-localization on a mobile phone using the constructed prior map is achieved (i.e. 60 and 76 cm in two tests respectively). Finally, this work also demonstrates a novel LiDAR point cloud fusion method that produces optimized and consistent coarse-to-fine 3D reconstruction in large and complex scenes.

Lingling Shan,1 Yudie Li,1 Yifan Ma,2 Yang Yang,1 Jing Wang,1 Lei Peng,1 Weiwei Wang,1 Fang Zhao,1 Wanrong Li,1 Xiaoyuan Chen3– 6 1Institute of Pharmaceutical Biotechnology, School of Biology and Food Engineering, Suzhou University, Suzhou, People’s Republic of China; 2Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, People’s Republic of China; 3Departments of Diagnostic Radiology, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and College of Design and Engineering, National University of Singapore, Singapore, Singapore; 4Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; 5Nanomedicine Translational Research Program, NUS Center for Nanomedicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; 6Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research (A*STAR), Singapore, SingaporeCorrespondence: Xiaoyuan Chen; Lingling Shan, Email chen.shawn@nus.edu.sg; ntlinger-300@163.comBackground: While nanoplatform-based cancer theranostics have been researched and investigated for many years, enhancing antitumor efficacy and reducing toxic side effects is still an essential problem.Methods: We exploited nanoparticle coordination between ferric (Fe2+) ions and telomerase-targeting hairpin DNA structures to encapsulate doxorubicin (DOX) and fabricated Fe2+-DNA@DOX nanoparticles (BDDF NPs). This work studied the NIR fluorescence imaging and pharmacokinetic studies targeting the ability and biodistribution of BDDF NPs. In vitro and vivo studies investigated the nano formula’s toxicity, imaging, and synergistic therapeutic effects.Results: The enhanced permeability and retention (EPR) effect and tumor targeting resulted in prolonged blood circulation times and high tumor accumulation. Significantly, BDDF NPs could red

This thesis investigates related organizations perceptions and coordination in response to legal changes governing packaging waste collection (PWC) in Gotland, Sweden, utilizing Sensemaking theory, Interorganizational Coordination (IOC) theory, and Corporate Social Responsibility (CSR) theory. Through qualitative research methods, including interviews with key participants from public and private sectors involved in waste management, this study explores how individuals from different organizations make sense of and adapt to the new regulatory framework. The research identifies diverse organization views towards the legal changes, highlighting challenges related to ambiguity and clarity in regulatory details. Sensemaking processes influence organizational interpretations of the regulations, shaping their actions and collaborative efforts. IOC dynamics play a crucial role in waste management coordination, with task breakdown and coordination among multiple organizations proving more effective than centralized approaches. CSR illustrates the dilemma of private sectors’ contribution to broader sustainability goals due to competition concern in a market-driven business context. The study underscores the significance of public sector entities in waste management governance compared to private organizations. This research contributes to advancing understanding of waste management policy implementation and coordination dynamics within a regional context, leveraging sensemaking, IOC and CSR theories.

Micro-expression recognition (MER) aims to recognize the short and subtle facial movements from the Micro-expression (ME) video clips, which reveal real emotions. Recent MER methods mostly only utilize special frames from ME video clips or extract optical flow from these special frames. However, they neglect the relationship between movements and space-time, while facial cues are hidden within these relationships. To solve this issue, we propose the Hierarchical Space-Time Attention (HSTA). Specifically, we first process ME video frames and special frames or data parallelly by our cascaded Unimodal Space-Time Attention (USTA) to establish connections between subtle facial movements and specific facial areas. Then, we design Crossmodal Space-Time Attention (CSTA) to achieve a higher-quality fusion for crossmodal data. Finally, we hierarchically integrate USTA and CSTA to grasp the deeper facial cues. Our model emphasizes temporal modeling without neglecting the processing of special data, and it fuses the contents in different modalities while maintaining their respective uniqueness. Extensive experiments on the four benchmarks show the effectiveness of our proposed HSTA. Specifically, compared with the latest method on the CASME3 dataset, it achieves about 3% score improvement in seven-category classification., Comment: 9 pages, 4 figures

Early-life gut microbial colonization and development exert a profound impact on the health and metabolism of the host throughout the life span. The transmission of microbes from the mother to the offspring affects the succession and establishment of the early-life rumen microbiome in newborns, but the contributions of different maternal sites to the rumen microbial establishment remain unclear. In the present study, samples from different dam sites (namely, oral, rumen fluid, milk, and teat skin) and rumen fluid of yak calves were collected at 6 time points between d 7 and 180 postpartum to determine the contributions of the different maternal sites to the establishment of the bacterial and archaeal communities in the rumen during early life. Our analysis demonstrated that the dam's microbial communities clustered according to the sites, and the calves' rumen microbiota resembled that of the dam consistently regardless of fluctuations at d 7 and 14. The dam's rumen microbiota was the major source of the calves' rumen bacteria (7.9%) and archaea (49.7%) compared with the other sites, whereas the potential sources of the calf rumen microbiota from other sites varied according to the age. The contribution of dam's rumen bacteria increased with age from 0.36% at d 7 to 14.8% at d 180, whereas the contribution of the milk microbiota showed the opposite trend, with its contribution reduced from 2.7% at d 7 to 0.2% at d 180. Maternal oral archaea were the main sources of the calves' rumen archaea at d 14 (50.4%), but maternal rumen archaea became the main source gradually and reached 66.2% at d 180. These findings demonstrated the potential microbial transfer from the dam to the offspring that could influence the rumen microbiota colonization and establishment in yak calves raised under grazing regimens, providing the basis for future microbiota manipulation strategies during their early life.

Firstly, a method for measuring the risk aversion of investors was proposed based on the prospect theory. Secondly, under a sole hypothetical condition in which the risk aversion degree for different assets is the same in a market, the pricing of discrete European options was given based on the objective probability. Thirdly, it was proven that the European option price obtained was a non-arbitrate price. And then, both for the binomial tree, which is a complete market, and for the trinomial tree, which is an incomplete market, pricing European options were discussed by implementing the method provided in this paper. Lastly, an illustration is used to demonstrate how to estimate preference parameters from market data and how to calculate options prices. The result states that the method in this paper is the same as the traditional risk-neutral methods in a complete market, but it is different from the traditional risk-neutral methods in an incomplete market, and more, the price obtained in this paper is affected by the objective probability and also contains the risk attitude of the investors.

Clustering is a fundamental unsupervised representation learning task with wide application in computer vision and pattern recognition. Deep clustering utilizes deep neural networks to learn latent representation, which is suitable for clustering. However, previous deep clustering methods, especially image clustering, focus on the features of the data itself and ignore the relationship between the data, which is crucial for clustering. In this paper, we propose a novel Deep Structure and Attention aware Subspace Clustering (DSASC), which simultaneously considers data content and structure information. We use a vision transformer to extract features, and the extracted features are divided into two parts, structure features, and content features. The two features are used to learn a more efficient subspace structure for spectral clustering. Extensive experimental results demonstrate that our method significantly outperforms state-of-the-art methods. Our code will be available at https://github.com/cs-whh/DSASC, Comment: 13 pages, 4 figures, accepted by PRCV2023

The latest advances in artificial intelligence (AI) present many unprecedented opportunities to achieve much improved bandwidth saving in communications. Unlike conventional communication systems focusing on packet transport, rich datasets and AI makes it possible to efficiently transfer only the information most critical to the goals of message recipients. One of the most exciting advances in generative AI known as diffusion model presents a unique opportunity for designing ultra-fast communication systems well beyond language-based messages. This work presents an ultra-efficient communication design by utilizing generative AI-based on diffusion models as a specific example of the general goal-oriented communication framework. To better control the regenerated message at the receiver output, our diffusion system design includes a local regeneration module with finite dimensional noise latent. The critical significance of noise latent control and sharing residing on our Diff-GO is the ability to introduce the concept of "local generative feedback" (Local-GF), which enables the transmitter to monitor the quality and gauge the quality or accuracy of the message recovery at the semantic system receiver. To this end, we propose a new low-dimensional noise space for the training of diffusion models, which significantly reduces the communication overhead and achieves satisfactory message recovery performance. Our experimental results demonstrate that the proposed noise space and the diffusion-based generative model achieve ultra-high spectrum efficiency and accurate recovery of transmitted image signals. By trading off computation for bandwidth efficiency (C4BE), this new framework provides an important avenue to achieve exceptional computation-bandwidth tradeoff., Comment: Submitted to IEEE International Conference on Communications (ICC) 2024

Adverse drug reaction (ADR) detection is an essential task in the medical field, as ADRs have a gravely detrimental impact on patients' health and the healthcare system. Due to a large number of people sharing information on social media platforms, an increasing number of efforts focus on social media data to carry out effective ADR detection. Despite having achieved impressive performance, the existing methods of ADR detection still suffer from three main challenges. Firstly, researchers have consistently ignored the interaction between domain keywords and other words in the sentence. Secondly, social media datasets suffer from the challenges of low annotated data. Thirdly, the issue of sample imbalance is commonly observed in social media datasets. To solve these challenges, we propose the Knowledge Enhanced Shallow and Deep Transformer(KESDT) model for ADR detection. Specifically, to cope with the first issue, we incorporate the domain keywords into the Transformer model through a shallow fusion manner, which enables the model to fully exploit the interactive relationships between domain keywords and other words in the sentence. To overcome the low annotated data, we integrate the synonym sets into the Transformer model through a deep fusion manner, which expands the size of the samples. To mitigate the impact of sample imbalance, we replace the standard cross entropy loss function with the focal loss function for effective model training. We conduct extensive experiments on three public datasets including TwiMed, Twitter, and CADEC. The proposed KESDT outperforms state-of-the-art baselines on F1 values, with relative improvements of 4.87%, 47.83%, and 5.73% respectively, which demonstrates the effectiveness of our proposed KESDT.

Cortical surface registration plays a crucial role in aligning cortical functional and anatomical features across individuals. However, conventional registration algorithms are computationally inefficient. Recently, learning-based registration algorithms have emerged as a promising solution, significantly improving processing efficiency. Nonetheless, there remains a gap in the development of a learning-based method that exceeds the state-of-the-art conventional methods simultaneously in computational efficiency, registration accuracy, and distortion control, despite the theoretically greater representational capabilities of deep learning approaches. To address the challenge, we present SUGAR, a unified unsupervised deep-learning framework for both rigid and non-rigid registration. SUGAR incorporates a U-Net-based spherical graph attention network and leverages the Euler angle representation for deformation. In addition to the similarity loss, we introduce fold and multiple distortion losses, to preserve topology and minimize various types of distortions. Furthermore, we propose a data augmentation strategy specifically tailored for spherical surface registration, enhancing the registration performance. Through extensive evaluation involving over 10,000 scans from 7 diverse datasets, we showed that our framework exhibits comparable or superior registration performance in accuracy, distortion, and test-retest reliability compared to conventional and learning-based methods. Additionally, SUGAR achieves remarkable sub-second processing times, offering a notable speed-up of approximately 12,000 times in registering 9,000 subjects from the UK Biobank dataset in just 32 minutes. This combination of high registration performance and accelerated processing time may greatly benefit large-scale neuroimaging studies.

Endothelial cells differ from other cell types responsible for the formation of the vascular wall in their unusual reliance on glycolysis for most energy needs, which results in extensive production of lactate. We find that endothelium-derived lactate is taken up by pericytes, and contributes substantially to pericyte metabolism including energy generation and amino acid biosynthesis. Endothelial-pericyte proximity is required to facilitate the transport of endothelium-derived lactate into pericytes. Inhibition of lactate production in the endothelium by deletion of the glucose transporter-1 (GLUT1) in mice results in loss of pericyte coverage in the retina and brain vasculatures, leading to the blood-brain barrier breakdown and increased permeability. These abnormalities can be largely restored by oral lactate administration. Our studies demonstrate an unexpected link between endothelial and pericyte metabolisms and the role of endothelial lactate production in the maintenance of the blood-brain barrier integrity. In addition, our observations indicate that lactate supplementation could be a useful therapeutic approach for GLUT1 deficiency metabolic syndrome patients.

Changes in land use land cover (LULC) and landscape pattern in arid areas can considerably impact water quality in small watersheds. Exploring the associations between land use, landscape pattern, and riverine water quality can inform land-use planning for water-quality security. In northwest China's Jing River Watershed (JRW), water samples were collected at 67 points in 2016–2017 and analyzed. Coupled with Sentinel-2 remote-sensing images, this study calculated the Canadian Water Quality Index (CWQI) to assign the water-quality category. The Random Forest classification characterized current LULC patterns and computed landscape metrics in a riparian buffer zone. The stepwise multiple linear regression and redundancy analysis methods investigated the relationships amongst LULC, eight landscape metrics, and eight water-quality parameters. The results indicated high concentrations of total phosphorus (TP) and total nitrogen (TN) in the JRW's middle and lower reaches. For CWQI, lacking evident temporal fluctuations was contrasted by noticeable spatial variations. Intense Human activities have aggravated the deterioration of the water quality of the JRW. LULC-type changes, including Waterbody, Forest-grassland, and Farmland, imposed notable impacts on seasonal water quality. For landscape metrics, patch cohesion index (COHESION) strongly correlated with chemical oxygen demand (COD), mineralization degree (MD), and TN. By contrast, patch density (PD) correlated negatively with TN. Interspersion juxtaposition index (IJI) strongly correlated with biochemical oxygen demand after five days (BOD5). COHESION, PD, and IJI can be critical factors in predicting water-quality changes at the small-watershed scale. Our findings offered a robust scientific basis to refine regional sustainable water development strategy and rational water-resource management.

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.

There has been much interest in using skyrmions for new approaches to compution, however, creating, deleting and driving skyrmions remains a challenge. Here, Wang et al demonstrate all three operations for skyrmions in tailored Co8Zn10Mn2 nanodevices using tailored current pulses. Writing, erasing and computing are three fundamental operations required by any working electronic device. Magnetic skyrmions could be essential bits in promising in emerging topological spintronic devices. In particular, skyrmions in chiral magnets have outstanding properties like compact texture, uniform size, and high mobility. However, creating, deleting, and driving isolated skyrmions, as prototypes of aforementioned basic operations, have been a grand challenge in chiral magnets ever since the discovery of skyrmions, and achieving all these three operations in a single device is even more challenging. Here, by engineering chiral magnet Co8Zn10Mn2 into the customized micro-devices for in-situ Lorentz transmission electron microscopy observations, we implement these three operations of skyrmions using nanosecond current pulses with a low current density of about 10(10) A center dot m(-)(2) at room temperature. A notched structure can create or delete magnetic skyrmions depending on the direction and magnitude of current pulses. We further show that the magnetic skyrmions can be deterministically shifted step-by-step by current pulses, allowing the establishment of the universal current-velocity relationship. These experimental results have immediate significance towards the skyrmion-based memory or logic devices.

The United Nations (UN) Sustainable Development Goals (SDGs) challenge the global community to build a world where no one is left behind. Recognizing that research plays a fundamental part in supporting these goals, attempts have been made to classify research publications according to their relevance in supporting each of the UN's SDGs. In this paper, we outline the methodology that we followed when mapping research articles to SDGs and which is adopted by Times Higher Education in their Social Impact rankings. We compare our solution with other existing queries and models mapping research papers to SDGs. We also discuss various aspects in which the methodology can be improved and generalized to other types of content apart from research articles. The results presented in this paper are the outcome of the SDG Research Mapping Initiative that was established as a partnership between the University of Southern Denmark, the Aurora European Universities Alliance (represented by Vrije Universiteit Amsterdam), the University of Auckland, and Elsevier to bring together broad expertise and share best practices on identifying research contributions to UN's Sustainable Development Goals., Comment: 16 pages, 2 figures, 12 tables, 24 references

The Tallo database (v1.0.0) is a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. Data were compiled from 61,856 globally distributed sites and include measurements for 5,163 tree species., The Tallo database (v1.0.0) is a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. Data were compiled from 61,856 globally distributed sites and include measurements for 5,163 tree species. For a full description of the database, see: Jucker et al. (2022) Tallo – a global tree allometry and crown architecture database. Global Change Biology, https://doi.org/10.1111/gcb.16302. If using the Tallo database in your work please cite the original publication listed above, as well as this repository using the corresponding DOI (10.5281/zenodo.6637599).

Fang Ding,1 Wenjing Liu,2 Huiqing Wang,3 Weiwei Wang,1 Caixia Yang1 1Department of Geriatrics, Hengshui People’s Hospital, Hengshui City, Hebei Province, People’s Republic of China; 2Department of Respiratory Medicine, Hengshui People’s Hospital, Hengshui City, Hebei Province, People’s Republic of China; 3Department of Intensive Care Medicine, Hengshui People’s Hospital, Hengshui City, Hebei Province, People’s Republic of ChinaCorrespondence: Fang Ding, Department of Geriatrics, Hengshui People’s Hospital, No. 180, Renmin East Road, TaoCheng District, Hengshui City, Hebei Province, 053000, People’s Republic of China, Tel +86 0318-2187239, Email dingfan99g@126.comObjective: To analyse the guiding value of procalcitonin (PCT) for the selection of ventilation switching points in sequential mechanical ventilation for patients with acute exacerbation of chronic obstructive pulmonary disease (COPD) and respiratory failure, and to provide a reference for the optimisation of mechanical ventilation for patients with COPD and respiratory failure.Methods: The study included 160 patients with an acute exacerbation of COPD complicated by respiratory failure who received sequential mechanical ventilation treatment. They were divided into two groups of 80 participants. The critical point of the pulmonary infection observation window (PIC) was used as the switching point for sequential mechanical ventilation treatment in the control group, and PCT clinical node was used as the switching point for sequential mechanical ventilation treatment in the observation group. The invasive ventilation time, non-invasive mechanical ventilation time, total mechanical ventilation time, intensive care unit (ICU) treatment time, complication rate and prognosis were compared for the two groups.Results: (1) There was no significant difference in the respiratory rate, heart rate, arterial systolic pressure, arterial oxygen partial pressure, arterial carbon dioxide partial pressure or p

Weiwei Wang, Ting Wei, Suihuai Yu, Jian Chen, Xiaoyan Yang College of Art and Design, Shaanxi University of Science and Technology, Xi’an City, People’s Republic of ChinaCorrespondence: Ting Wei, College of Art and Design, Shaanxi University of Science and Technology, Xi’an City, People’s Republic of China, Email wt@joya.cnIntroduction: The telecommuting experience and job performance have been significantly impacted by the COVID-19 pandemic, and job performance stability of telecommuting employees has become a critical concern.Objective: A decision model for telecommuting experience service design was constructed based on a backpropagation (BP) neural network to provide a theoretical basis for enterprises to evaluate telework performance and the psychological health of employees.Methods: The analytic hierarchy process (AHP) was used to determine the core stakeholders. The grey relational analysis (GRA) method and the NASA Task Load Index (NASA-TLX) scale were used to measure the factors affecting employees’ telecommuting experience and job performance. A BP neural network relationship model of employees’ telecommuting experience was established to predict its impact on employees’ job performance.Results: Based on the model prediction results, a service system map was created, and the potential to enhance the telework performance of employees was evaluated.Discussion: It was concluded that the factors affecting the telecommuting experience were diverse, but emotions had the dominant influence. Significant positive correlations were found between emotional impact and temporal perception, execution difficulty, and communication barriers.Conclusion: The proposed decision model for telecommuting experience service design accurately predicted the impact of telecommuting efficiency, providing an effective approach for innovative remote management.Keywords: design decision, job performance, telecommuting experience, BP neural networks, NASA-TLX scale

Forest ecosystems sequester approximately half of the world’s organic carbon (C), most of it in the soil. The amount of soil C stored depends on the input and decomposition rate of soil organic matter (OM), which is controlled by the abundance and composition of the microbial and invertebrate communities, soil physico-chemical properties, and (micro)-climatic conditions. Although many studies have assessed how these site-specific climatic and soil properties affect the decomposition of fresh OM, differences in the type and quality of the OM substrate used, make it difficult to compare and extrapolate results across larger scales. Here, we used standard wood stakes made from aspen (Populus tremuloides Michx.) and loblolly pine (Pinus taeda L.) to explore how climate and abiotic soil properties affect wood decomposition across 44 unharvested forest stands located across the northern hemisphere. Stakes were placed in three locations: (i) on top of the surface organic horizons (surface), (ii) at the interface between the surface organic horizons and mineral soil (interface), and (iii) into the mineral soil (mineral). Decomposition rates of both wood species was greatest for mineral stakes and lowest for stakes placed on the surface organic horizons, but aspen stakes decomposed faster than pine stakes. Our models explained 44 and 36% of the total variation in decomposition for aspen surface and interface stakes, but only 0.1% (surface), 12% (interface), 7% (mineral) for pine, and 7% for mineral aspen stakes. Generally, air temperature was positively, precipitation negatively related to wood stake decomposition. Climatic variables were stronger predictors of decomposition than soil properties (surface C:nitrogen ratio, mineral C concentration, and pH), regardless of stake location or wood species. However, climate-only models failed in explaining wood decomposition, pointing toward the importance of including local-site properties when predicting wood decomposition. The d

The wide application of chromium will definitely increase the probability of impact of chromium-containing effluents on the surrounding environment and human health. Prior to reviewing the research progress on the liquid–liquid extraction of chromium, the common methods for treating chromium-containing wastewater and chromium species in solution are first introduced. Liquid–liquid extraction processes of Cr(VI) and Cr(III) are respectively investigated in detail in subsequent sections. The typical oxidisation effect of Cr(VI) and ageing effect of Cr(III) are analysed. Most of the mechanisms involved in chromium extraction processes are also reviewed. This literature review provides not only a theoretical basis for choosing an appropriate ion host, but also an important reference for optimisation of chromium removal processes by solvent extraction. In the industrial production of nickel, cobalt, and scandium, it can also be used to predict the effects of Cr(III) ageing and Cr(VI) oxidation on chromium-containing solvent extraction systems and further avoid these negative effects in advance. (Authors.), The wide application of chromium will definitely increase the probability of impact of chromium-containing effluents on the surrounding environment and human health. Prior to reviewing the research progress on the liquid–liquid extraction of chromium, the common methods for treating chromium-containing wastewater and chromium species in solution are first introduced. Liquid–liquid extraction processes of Cr(VI) and Cr(III) are respectively investigated in detail in subsequent sections. The typical oxidisation effect of Cr(VI) and ageing effect of Cr(III) are analysed. Most of the mechanisms involved in chromium extraction processes are also reviewed. This literature review provides not only a theoretical basis for choosing an appropriate ion host, but also an important reference for optimisation of chromium removal processes by solvent extraction. In the industrial production of nickel, cobalt, and scandium, it can also be used to predict the effects of Cr(III) ageing and Cr(VI) oxidation on chromium-containing solvent extraction systems and further avoid these negative effects in advance. (Authors.)

Zhang Y, Zhou J, Yang C, et al. Int J Nanomedicine. 2016;11:1119–1130. The authors have advised due to an error at the time of figure assembly, Figure 4 on page 1124 is incorrect. The correct Figure 4 is shown in Download Article. Page 1126, Table 1, the authors have advised a mistake was made in calculating the Drug loading content (DLC) in the manuscript. The correct Table 1 is shown in Download Article. The authors apologize for these errors and advise it does not affect the results of the paper. Read the original article

Jianhua Chen,1,* Quanhe Chen,2,* Feilong Zhang,1 Xuehai Chen,1 Zhe Xu,1 Qiong Jiang,1 Xudong Sun,1 Jinguo Li,1 Lianglong Chen,1 Weiwei Wang1 1Department of Cardiology, Fujian Medical University Union Hospital & Fujian Provincial Institute of Coronary Disease, Fuzhou, People’s Republic of China; 2Union Clinic Medical College, Fujian Medical University, Fuzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Weiwei WangDepartment of Cardiology, Fujian Medical University Union Hospital & Fujian Provincial Institute of Coronary Disease, No. 29 of Xinquan Road, Gulou District, Fuzhou, 350001, People’s Republic of ChinaTel +86 591 86218022Fax +86 591 83322156Email wang_wwedh@163.comObjective: This study aimed to investigate whether the enhanced endpoint of pulmonary vein isolation (PVI; intravenous injection of adenosine-triphosphate [ATP] + pacing capture + supplemental ablation) after initial PVI can reduce the long-term recurrence rate of atrial fibrillation (AF) after PVI.Methods: Patients with paroxysmal or persistent AF undergoing catheter ablation treatment were enrolled in this study and divided into three groups according to the surgical endpoint: (1) group 1 (n = 92), in which patients were observed for 30 minutes after the initial PVI and pulmonary vein–left atrium (PV–LA) electrical conduction had not recovered; (2) group 2 (n = 99), in which patients were observed for 30 minutes after the initial PVI, then intravenously injected with ATP, and PV–LA electrical conduction had not recovered; and (3) group 3 (n = 102), in which patients were observed for 30 minutes after the initial PVI, then intravenously injected with ATP + treated with ablation line pacing, and the atrium could not be captured.Results: Patients were followed up for 12 months after the operation. Twenty-eight patients in group 1 (30.4%), 19 patients in group 2 (19.2%), and 10 pat

Species are becoming extinct at unprecedented rates as a consequence of human activity. Hence it is important to understand the evolutionary dynamics of species with already small population sizes. Populus ilicifolia is a vulnerable poplar species that is isolated from other poplar species and is uniquely adapted to the Tropics. It has a very limited size, reproduces partly clonally and is therefore an excellent case study for conservation genomics. We present here the first annotated draft genome of P. ilicifolia, characterize genome-wide patterns of polymorphisms and compare those to other poplar species with larger natural ranges. P. ilicifolia experienced a more prolonged and severe decline of effective population size (Ne) and signs of genetic erosion than any other poplar species with which it was compared. At present, the species has the lowest genome-wide genetic diversity, the highest abundance of long runs of homozygosity, high inbreeding levels as well as a high overall accumulation of deleterious variants. However, more effective purging of severely deleterious variants and adaptation to the Tropics may have contributed to its survival. Hence, in spite of its limited genetic variation, it is certainly worth pursuing the conservation efforts of this unique species.

The Empirical Revenue Maximization (ERM) is one of the most important price learning algorithms in auction design: as the literature shows it can learn approximately optimal reserve prices for revenue-maximizing auctioneers in both repeated auctions and uniform-price auctions. However, in these applications the agents who provide inputs to ERM have incentives to manipulate the inputs to lower the outputted price. We generalize the definition of an incentive-awareness measure proposed by Lavi et al (2019), to quantify the reduction of ERM’s outputted price due to a change of m = 1 out of N input samples, and provide specific convergence rates of this measure to zero as N goes to infinity for different types of input distributions. By adopting this measure, we construct an efficient, approximately incentive-compatible, and revenue-optimal learning algorithm using ERM in repeated auctions against non-myopic bidders, and show approximate group incentive-compatibility in uniform-price auctions. © 2020 Neural information processing systems foundation. All rights reserved.

Weiwei Wang,1 Junting Fan,2 Guang Zhu,1 Jing Wang,1 Yumei Qian,1 Hongxia Li,1 Jianming Ju,3 Lingling Shan1 1Institute of Pharmaceutical Biotechnology, School of Biology and Food Engineering, Key Laboratory of Spin Electron and Nanomaterials of Anhui Higher Education Institutes, Suzhou University, Suzhou 234000, People’s Republic of China; 2Department of Pharmaceutical Analysis, School of Pharmacy, Nanjing Medical University, Nanjing 211166, People’s Republic of China; 3Jiangsu Province Academy of Traditional Chinese Medicine, Nanjing, People’s Republic of ChinaCorrespondence: Lingling Shan; Junting Fan Email ntlinger-300@163.com; Juntingfan@njmu.edu.cnBackground: Targeted prodrug has various applications as drug formulation for tumor therapy. Therefore, amphoteric small-molecule prodrug combined with nanoscale characteristics for the self-assembly of the nano-drug delivery system (DDS) is a highly interesting research topic.Methods and Results: In this study, we developed a prodrug self-assembled nanoplatform, 2-glucosamine-fluorescein-5(6)-isothiocyanate-glutamic acid-paclitaxel (2DA-FITC-PTX NPs) by integration of targeted small molecule and nano-DDS with regular structure and perfect targeting ability. 2-glucosamine (DA) and paclitaxel were conjugated as the targeted ligand and anti-tumor chemotherapy drug by amino acid group. 2-DA molecular structure can enhance the targeting ability of prodrug-based 2DA-FITC-PTX NPs and prolong retention time, thereby reducing the toxicity of normal cell/tissue. The fluorescent dye FITC or near-infrared fluorescent dye ICG in prodrug-based DDS was attractive for in vivo optical imaging to study the behavior of 2DA-FITC-PTX NPs. In vitro and in vivo results proved that 2DA-FITC-PTX NPs exhibited excellent targeting ability, anticancer activity, and weak side effects.Conclusion: This work demonstrates a new combination of nanomaterials for chemotherapy and may promote prodrug-based DDS clinical appli

Highlights • Microplastics act as anthropogenic vectors of trace metals in freshwaters. • Adsorption capacity of microplastics is enhanced by biofilms but is not strong as natural substrates. • Biofilms alter the adsorption kinetics and mechanisms of trace metals onto microplastics. • Microplastics enhance exchange rates of trace metals between water and solid materials. • Anthropogenic substrate is necessary in evaluation of migration and fate of trace metals. Microplastics (MPs) are ubiquitous in freshwater environments, and represent an emerging anthropogenic vector for contaminants, such as trace metals. In this study, virgin expanded polystyrene (PS) particles were placed in a eutrophic urban lake and a reservoir serving as the resource of domestic water for 4 weeks, to develop biofilms on the surface. For comparison, natural adsorbents in the form of suspended particles and surficial sediment were also sampled from these waterbodies. The trace metal adsorption properties of anthropogenic (virgin and biofilm covered microplastics) and natural substrates were investigated and compared via batch adsorption experiments. The adsorption isotherms fitted the Langmuir model, revealed that biofilms could enhance the trace metal adsorption capacity of MPs. However, natural substrates still had a greater adsorption capacity. Biofilms also alter the adsorption kinetics of trace metals onto MPs. The process of adsorption onto virgin MPs was dominated by intraparticle diffusion, whereas film diffusion governed adsorption onto biofilm covered microplastics and natural substrates. The trace metal adsorption of all the substrates was significantly dependent on pH and ionic strength. The adsorption mechanisms were further analyzed by SEM-EDS and FT-IR. The enhancement of adsorption was mainly attributed to complexation with functional groups contained in the biofilms, including carboxyl, amino, and phenyl-OH. Collectively, biofilm development intensifies the role of MPs in the

Good acoustical behavior is one of the most important factor in the light-weight design. The acoustic metametamaterials are promising solutions to achieve the improvements in this field. With their repeat- ing structure in periodicity, an excellent sound reduction effect can be achieved. According to the litera- ture research, there are various of acoustic metamaterial designs with different materials and structures. However, there are still challenges to find a model, which can be both manufactured and simulated and meanwhile the results agree with each other. On the one hand, the manufacturing method (3D-printing technology) has error potentials when building small-size models. This will lead to a wrong value in experiments. On the other hand, the simulation environment is idealized, which cause a deviation between simulation results and experimental results. Obviously, the acoutic physical domain has some unavoidable uncertenties. It is difficult to explore the propagation of acoustic waves in different media materials. This thesis aims to propose possible acoustic metamaterial designs based on the literature research. These models can be both manufactured by 3D-printing technology and simulated in software. The focus of thesis is to find a simulation process, in which the experiments machted results can be calculated. The properties of acoustic metamaterials, which can be evaluataed and compared by experiments and simulations, are also explained and analyzed. The first few chapters give an overview about state of the art. The history and development as well as categories of metamaterials are introduced. After that, the important physical parameters and academica models as well as possible analytical methods of acoustical metamaterials are explained. Possible math- ematical calculation methods are compared with Finite-element method specially for software. Based on the literature research different prototype designs are proposed. Before explain the simulation pro

In this paper, we mainly use classical Hermitian self-orthogonal generalized Reed-Solomon codes to construct two new classes of quantum MDS codes. Most of our quantum MDS codes have minimum distance larger than q/2+1. Compared with previously known constructions, these quantum MDS codes in our constructions have large minimum distance and their parameters are not covered by the previous codes., Comment: Unfortunately, we have recognized that the quantum MDS codes in our manuscript is covered by the codes in the reference [17]. We are going to rearrange this manuscript and try to give more new results

Mycosis fungoides (MF) is a slowly progressive cutaneous T-cell lymphoma (CTCL) for which there is no cure. In the early plaque stage, the disease is indolent, but development of tumors heralds an increased risk of metastasis and death. Previous research into the genomic landscape of CTCL revealed a complex pattern of >50 driver mutations implicated in more than a dozen signaling pathways. However, the genomic mechanisms governing disease progression and treatment resistance remain unknown. Building on our previous discovery of the clonotypic heterogeneity of MF, we hypothesized that this lymphoma does not progress in a linear fashion as currently thought but comprises heterogeneous mutational subclones. We sequenced exomes of 49 cases of MF and identified 28 previously unreported putative driver genes. MF exhibited extensive intratumoral heterogeneity (ITH) of a median of 6 subclones showing a branched phylogenetic relationship pattern. Stage progression was correlated with an increase in ITH and redistribution of mutations from stem to clades. The pattern of clonal driver mutations was highly variable, with no consistent mutations among patients. Similar intratumoral heterogeneity was detected in leukemic CTCL (Sézary syndrome). Based on these findings, we propose a model of MF pathogenesis comprising divergent evolution of cancer subclones and discuss how ITH affects the efficacy of targeted drug therapies and immunotherapies for CTCL.

Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma. Lesions of MF are formed by hematogenous seeding the skin with polyclonal (clonotypically diverse) neoplastic T-cells which accumulate numerous mutations and display a high degree of mutational, intratumoral heterogeneity (ITH). A characteristic but poorly studied feature of MF is epidermotropism, the tendency to infiltrate skin epithelial layer (epidermis) in addition to the vascularized dermis. By sequencing the exomes of the microdissected clusters of lymphoma cells from the epidermis and the dermis, we found that those microenvironments comprised different malignant clonotypes. Subclonal structure witnessed the independent mutational evolution in the epidermis and dermis. Thus, the epidermal involvement in MF could not be explained by gradual infiltration from the dermis but was caused by a separate seeding process followed by a quasi-neutral, branched evolution. In conclusion, tissue microenvironments shape the subclonal architecture in MF leading to “ecological heterogeneity” which contributes to the total ITH. Since ITH adversely affects cancer prognosis, targeting the microenvironment may present therapeutic opportunities in MF and other cancers.

This paper describes DiDi AI Labs' submission to the WMT2020 news translation shared task. We participate in the translation direction of Chinese->English. In this direction, we use the Transformer as our baseline model, and integrate several techniques for model enhancement, including data filtering, data selection, back-translation, fine-tuning, model ensembling, and re-ranking. As a result, our submission achieves a BLEU score of $36.6$ in Chinese->English., Comment: Accepted at WMT 2020

Communicating effectively with customers is a challenge for many marketers, but especially in a context that is both pivotal to individual long-term financial well-being and difficult to understand: pensions. Around the world, participants are reluctant to consider their pension in advance, it leads to a lack of preparation of their pension retirement [1], [2]. In order to engage participants to obtain information on their expected pension benefits, personalizing the pension providers' email communication is a first and crucial step. We describe a machine learning approach to model email newsletters to fit participants' interests. The data for the modeling and analysis is collected from newsletters sent by a large Dutch pension provider of the Netherlands and is divided into two parts. The first part comprises 2,228,000 customers whereas the second part comprises the data of a pilot study, which took place in July 2018 with 465,711 participants. In both cases, our algorithm extracts features from continuous and categorical data using random forests, and then calculates node embeddings of the decision boundaries of the random forest. We illustrate the algorithm's effectiveness for the classification task, and how it can be used to perform data mining tasks. In order to confirm that the result is valid for more than one data set, we also illustrate the properties of our algorithm in benchmark data sets concerning churning. In the data sets considered, the proposed modeling demonstrates competitive performance with respect to other state of the art approaches based on random forests, achieving the best Area Under the Curve (AUC) in the pension data set (0.948). For the descriptive part, the algorithm can identify customer segmentations that can be used by marketing departments to better target their communication towards their customers., Comment: 32 pages, 8 tables, 7 figures

TRAAK is a membrane tension-activated K+ channel that has been associated through behavioral studies to mechanical nociception. We used specific monoclonal antibodies in mice to show that TRAAK is localized exclusively to nodes of Ranvier, the action potential propagating elements of myelinated nerve fibers. Approximately 80 percent of myelinated nerve fibers throughout the central and peripheral nervous system contain TRAAK in what is likely an all-nodes or no-nodes per axon fashion. TRAAK is not observed at the axon initial segment where action potentials are first generated. We used polyclonal antibodies, the TRAAK inhibitor RU2 and node clamp amplifiers to demonstrate the presence and functional properties of TRAAK in rat nerve fibers. TRAAK contributes to the leak K+ current in mammalian nerve fiber conduction by hyperpolarizing the resting membrane potential, thereby increasing Na+ channel availability for action potential propagation. We speculate on why nodes of Ranvier contain a mechanosensitive K+ channel.

Rationale: Lung cancer is the leading cause of cancer death worldwide, and treatment options are limited to mainly cytotoxic agents. Here we reveal a novel role of miR-150 in non-small cell lung cancer (NSCLC) development and seek potential new therapeutic targets. Methods: The miR-150-mediated autophagy dysfunction in NSCLC cells were examined using molecular methods in vitro and in vivo. The upstream regulatory element and downstream target of miR-150 were identified in vitro and validated in vivo. Potential therapeutic methods (anti-c-myc or anti-miR-150) were tested in vitro and in vivo. Clinical relevance of the c-myc/miR-150/EPG5 axis in NSCLC was validated in human clinical samples and large genomics database. Results: miR-150 blocked the fusion of autophagosomes and lysosomes through directly repressing EPG5. The miR-150-mediated autophagy defect induced ER stress and increased cellular ROS levels and DNA damage response, and promoted NSCLC cell proliferation and tumor growth. Knockdown of EPG5 promoted NSCLC cell proliferation, and attenuated the effects of miR-150. c-myc gene was identified as a miR-150 transcriptional factor which increased miR-150 accumulation, therefore pharmacologically or genetically inhibiting c-myc/miR-150 expression significantly inhibited NSCLC cell growth in vitro and in vivo. Both c-myc and miR-150 were significantly over-expressed in NSCLC, while EPG5 was down-regulated in NSCLC. Expression levels of these molecules were well correlated, and also well correlated with patient survival. Conclusions: Our findings suggest that c-myc/miR-150/EPG5 mediated dysfunction of autophagy contributes to NSCLC development, which may provide a potential new diagnostic and therapeutic target in NSCLC.

Good acoustical behavior is one of the most important factor in the light-weight design. The acoustic metametamaterials are promising solutions to achieve the improvements in this field. With their repeat- ing structure in periodicity, an excellent sound reduction effect can be achieved. According to the litera- ture research, there are various of acoustic metamaterial designs with different materials and structures. However, there are still challenges to find a model, which can be both manufactured and simulated and meanwhile the results agree with each other. On the one hand, the manufacturing method (3D-printing technology) has error potentials when building small-size models. This will lead to a wrong value in experiments. On the other hand, the simulation environment is idealized, which cause a deviation between simulation results and experimental results. Obviously, the acoutic physical domain has some unavoidable uncertenties. It is difficult to explore the propagation of acoustic waves in different media materials. This thesis aims to propose possible acoustic metamaterial designs based on the literature research. These models can be both manufactured by 3D-printing technology and simulated in software. The focus of thesis is to find a simulation process, in which the experiments machted results can be calculated. The properties of acoustic metamaterials, which can be evaluataed and compared by experiments and simulations, are also explained and analyzed. The first few chapters give an overview about state of the art. The history and development as well as categories of metamaterials are introduced. After that, the important physical parameters and academica models as well as possible analytical methods of acoustical metamaterials are explained. Possible math- ematical calculation methods are compared with Finite-element method specially for software. Based on the literature research different prototype designs are proposed. Before explain the simulation pro

Jing Qu,1 Weiwei Wang,1 Yanfei Feng,1 Longxing Niu,1 Mingzhong Li,1 Jicheng Yang,2 Yufeng Xie3 1National Engineering Laboratory for Modern Silk, College of Textile and Clothing Engineering, Soochow University, Suzhou 215123, People′s Republic of China; 2Cell and Molecular Biology Institute, College of Medicine, Soochow University, Suzhou 215123, People′s Republic of China; 3Department of Oncology, First Affiliated Hospital of Soochow University, Suzhou 215006, People′s Republic of ChinaCorrespondence: Mingzhong LiNational Engineering Laboratory for Modern Silk, College of Textile and Clothing Engineering, Soochow University, No. 199 Ren’ai Road, Suzhou 215123, People’s Republic of ChinaTel +86-512-6706-1150Fax +86-512-6724-6786Email mzli@suda.edu.cnYufeng XieDepartment of Oncology, First Affiliated Hospital of Soochow University, No.188 Shizi Road, Suzhou 215006, People′s Republic of ChinaTel +86-512-6778-0645Email sdxyf@163.comIntroduction: Cancer gene therapy requires both effective tumor suppressor genes and safe vectors that express target genes efficiently. Inhibitor of growth 4 (ING4) inhibits tumor growth via multiple pathways. Interleukin-24 (IL-24) also has tumor-suppressive activity against a broad spectrum of human cancers. Adenovirus (Ad) vectors exhibit high infection efficiency, but potential toxicity related to high doses of adenovirus has led to careful reconsideration of their use in human clinical trials. Antheraea pernyi silk fibroin (ASF) is a cytocompatible and biodegradable natural polymer, and it possesses Arg–Gly–Asp sequences exhibiting a high binding affinity and selectivity for αvβ3 and αvβ5 integrin receptors, which are overexpressed in tumor vessels and most tumor cells.Methods: In this study, an Arg-Gly-Asp peptide-modified Ad vector coexpressing ING4 and IL-24 was constructed by homologous recombination of the dual gene

TRAAK is a membrane tension-activated K+ channel that has been associated through behavioral studies to mechanical nociception. We used specific monoclonal antibodies in mice to show that TRAAK is localized exclusively to nodes of Ranvier, the action potential propagating elements of myelinated nerve fibers. Approximately 80 percent of myelinated nerve fibers throughout the central and peripheral nervous system contain TRAAK in what is likely an all-nodes or no-nodes per axon fashion. TRAAK is not observed at the axon initial segment where action potentials are first generated. We used polyclonal antibodies, the TRAAK inhibitor RU2 and node clamp amplifiers to demonstrate the presence and functional properties of TRAAK in rat nerve fibers. TRAAK contributes to the 'leak' K+ current in mammalian nerve fiber conduction by hyperpolarizing the resting membrane potential, thereby increasing Na+ channel availability for action potential propagation. We speculate on why nodes of Ranvier contain a mechanosensitive K+ channel.

Mycosis fungoides (MF), the most common type of cutaneous T-cell lymphoma, is believed to represent a clonal expansion of a transformed skin-resident memory T cell. T-cell receptor (TCR) clonality (ie, identical sequences of rearranged TCRa, TCRb, and TCRg), the key premise of this hypothesis, has been difficult to document conclusively because malignant cells are not readily distinguishable from the tumor-infiltrating reactive lymphocytes that contribute to the TCR clonotypic repertoire of MF. Here, we have successfully adopted targeted whole-exome sequencing (WES) to identify the repertoire of rearranged TCR genes in tumor-enriched samples from patients with MF. Although some of the investigated MF biopsies had the expected frequency of monoclonal rearrangements of TCRg corresponding to that of tumor cells, the majority of the samples presented multiple TCRg, TCRa, and TCRb clonotypes by WES. Our findings are compatible with the model in which the initial malignant transformation in MF does not occur in mature memory T cells but rather at the level of T-lymphocyte progenitors before TCRb or TCRa rearrangements. We have also shown that WES can be combined with whole-transcriptome sequencing in the same sample, which enables comprehensive characterization of the TCR repertoire in relation to tumor content. WES/whole-transcriptome sequencing might be applicable to other types of T-cell lymphomas to determine clonal dominance and clonotypic heterogeneity in these malignancies.

Huiyuan Zhang,1 Weiwei Wang,1 Qian Du21Department of Neurology, Liaocheng People’s Hospital, Liaocheng, Shandong, 252000, People’s Republic of China; 2EEG Room, Liaocheng People’s Hospital, Liaocheng, Shandong 252000, People’s Republic of ChinaBackground: Bupivacaine (Bup) is the most commonly used local anesthetic. However, Bup induces cytotoxicity, especially in older patients. Recent reports have indicated that andrographolide (Andro) exhibits protective effects on human neurons. Nevertheless, whether Andro can inhibit Bup-induced cytotoxicity remains unclear. As such, we investigated the effect of Andro on Bup-induced cytotoxicity of SH-SY5Y cells in the present study.Methods: Western blotting was used to examine expression of Bax, Bcl2, active caspase 3, p-Akt, and p-mTOR in SH-SY5Y cells. In addition, ELISA was used to detect levels of total glutathione and reactive oxygen species in cells.Results: We found that Andro attenuated Bup-induced cytotoxicity of SH-SY5Y cells. In addition, Andro inhibited Bup-induced apoptosis via downregulating the expression of Bax and active caspase 3 and upregulating the proteins Bcl2, p-Akt, and p-mTOR in SH-SY5Y cells. Moreover, Andro alleviated Bup-induced oxidative damage in SH-SY5Y cells via downregulating the level of reactive oxygen species and upregulating of the level of total glutathione. More significantly, inhibition of Akt abolished the protective effect of Andro in Bup-treated SH-SY5Y cells.Conclusion: Our findings indicated that Andro played a neuroprotective role via preserving Akt/mTOR activity and increasing antioxidative status in Bup-treated SH-SY5Y cells. Therefore, Andro may be a potential agent for the treatment of human cytotoxicity induced by Bup.Keywords: andrographolide, bupivacaine, apoptosis, Akt, cytotoxicity

ObjectivePrimary sclerosing cholangitis (PSC) is a genetically complex, inflammatory bile duct disease of largely unknown aetiology often leading to liver transplantation or death. Little is known about the genetic contribution to the severity and progression of PSC. The aim of this study is to identify genetic variants associated with PSC disease progression and development of complications.DesignWe collected standardised PSC subphenotypes in a large cohort of 3402 patients with PSC. After quality control, we combined 130 422 single nucleotide polymorphisms of all patients-obtained using the Illumina immunochip-with their disease subphenotypes. Using logistic regression and Cox proportional hazards models, we identified genetic variants associated with binary and time-to-event PSC subphenotypes.ResultsWe identified genetic variant rs853974 to be associated with liver transplant-free survival (p=6.07×10-9). Kaplan-Meier survival analysis showed a 50.9% (95% CI 41.5% to 59.5%) transplant-free survival for homozygous AA allele carriers of rs853974 compared with 72.8% (95% CI 69.6% to 75.7%) for GG carriers at 10 years after PSC diagnosis. For the candidate gene in the region, RSPO3, we demonstrated expression in key liver-resident effector cells, such as human and murine cholangiocytes and human hepatic stellate cells.ConclusionWe present a large international PSC cohort, and report genetic loci associated with PSC disease progression. For liver transplant-free survival, we identified a genome-wide significant signal and demonstrated expression of the candidate gene RSPO3 in key liver-resident effector cells. This warrants further assessments of the role of this potential key PSC modifier gene.

A study is presented of the recovery of nickel from high-iron-content laterite ore (1.14% Ni; 0.09% Co; 39.4% Fe) used in the Ramu Ni/Co project, Papua New Guinea (PNG) by mixing with sulphuric acid, curing and sulphation roasting, followed by aqueous leaching. The effects of sulphuric acid/ore ratio and roasting temperature on metal recoveries are described. The results indicate that, under optimal conditions of sulphuric acid/ore ratio of 0.45:1, curing at 180 degrees C (4 h), sulphation roasting at 650 degrees C (4 h), and water leaching at liquid/solid ratio of 7:1 and temperature of 80 degrees C (4 h), recoveries of nickel and iron are ca. 100 and 2%, respectively. In addition, the process is compared with a preliminary agitation tank leaching test (direct sulphuric acid leaching of ore) and with the currently used high-pressure acid-leaching process., A study is presented of the recovery of nickel from high-iron-content laterite ore (1.14% Ni; 0.09% Co; 39.4% Fe) used in the Ramu Ni/Co project, Papua New Guinea (PNG) by mixing with sulphuric acid, curing and sulphation roasting, followed by aqueous leaching. The effects of sulphuric acid/ore ratio and roasting temperature on metal recoveries are described. The results indicate that, under optimal conditions of sulphuric acid/ore ratio of 0.45:1, curing at 180 degrees C (4 h), sulphation roasting at 650 degrees C (4 h), and water leaching at liquid/solid ratio of 7:1 and temperature of 80 degrees C (4 h), recoveries of nickel and iron are ca. 100 and 2%, respectively. In addition, the process is compared with a preliminary agitation tank leaching test (direct sulphuric acid leaching of ore) and with the currently used high-pressure acid-leaching process.

Shaofeng Lou,1 Xiuyuan Zhang,2 Mingming Zhang,2 Shenglu Ji,1 Weiwei Wang,2 Ju Zhang,1 Chen Li,2 Deling Kong1,2 1Key Laboratory of Bioactive Materials, Ministry of Education, College of Life Sciences, Nankai University, 2Tianjin Key Laboratory of Biomaterial Research, Institute of Biomedical Engineering, Chinese Academy of Medical Science, Tianjin, People’s Republic of China Abstract: A reductase-cleavable and thermo-responsive star-shaped polymer nanogel was prepared via an “arm-first” atom transfer radical polymerization approach. The nanogel consists of a thermo- and redox-sensitive core and a zwitterionic copolymer block. The dual sensitive core is composed of poly(N-isopropylacrylamide) that is formed by disulfide crosslinking of N-isopropylacrylamide. The zwitterionic copolymer block contains a poly(sulfobetaine methacrylate) component, a known anti-adsorptive moiety that extends blood circulation time, and a lactose motif of poly(2-lactobionamidoethyl methacrylamide) that specifically targets the asialoglycoprotein receptors (ASGP-Rs) of hepatoma. Doxorubicin (DOX) was encapsulated into the cross-linked nanogels via solvent extraction/evaporation method and dialysis; average diameter of both blank and DOX-loaded nanogels was ~120 nm. The multi-responsiveness of nanogel drug release in different temperatures and redox conditions was assessed. After 24 h, DOX release was only ~20% at 30°C with 0 mM glutathione (GSH), whereas over 90% DOX release was observed at 40°C and 10 mM GSH, evidence of dual responsiveness to temperature and reductase GSH. The IC50 value of DOX-loaded nanogels was much lower in human hepatoma (HepG2) cells compared to non-hepatic HeLa cells. Remarkably, DOX uptake of HepG2 cells differed substantially in the presence and absence of galactose (0.31 vs 1.42 µg/mL after 48 h of incubation). The difference was non-detectable in HeLa cells (1.21 vs 1.57 µg/mL after 48 h of incuba

Retroviruses have been foundational in cancer research since early studies identified protooncogenes as targets for insertional mutagenesis. Integration of murine gamma-retroviruses into the host genome favours promoters and enhancers and entails interaction of viral integrase with host BET/bromodomain factors. We report that this integration pattern is conserved in feline leukaemia virus (FeLV), a gamma-retrovirus that infects many human cell types. Analysis of FeLV insertion sites in the MCF-7 mammary carcinoma cell line revealed strong bias towards active chromatin marks with no evidence of significant post-integration growth selection. The most prominent FeLV integration targets had little overlap with the most abundantly expressed transcripts, but were strongly enriched for annotated cancer genes. A meta-analysis based on several gamma-retrovirus integration profiling (GRIP) studies in human cells (CD34+, K562, HepG2) revealed a similar cancer gene bias but also remarkable cell-type specificity, with prominent exceptions including a universal integration hotspot at the long non-coding RNA MALAT1. Comparison of GRIP targets with databases of super-enhancers from the same cell lines showed that these have only limited overlap and that GRIP provides unique insights into the upstream drivers of cell growth. These observations elucidate the oncogenic potency of the gamma-retroviruses and support the wider application of GRIP to identify the genes and growth regulatory circuits that drive distinct cancer types., Pattern Recognition and Bioinformatics