Pairwise Instance Relation Augmentation for Long-tailed Multi-label Text Classification

Multi-label text classification (MLTC) is one of the key tasks in natural language processing. It aims to assign multiple target labels to one document. Due to the uneven popularity of labels, the number of documents per label follows a long-tailed distribution in most cases. It is much more challenging to learn classifiers for data-scarce tail labels than for data-rich head labels. The main reason is that head labels usually have sufficient information, e.g., a large intra-class diversity, while tail labels do not. In response, we propose a Pairwise Instance Relation Augmentation Network (PIRAN) to augment tailed-label documents for balancing tail labels and head labels. PIRAN consists of a relation collector and an instance generator. The former aims to extract the document pairwise relations from head labels. Taking these relations as perturbations, the latter tries to generate new document instances in high-level feature space around the limited given tailed-label instances. Meanwhile, two regularizers (diversity and consistency) are designed to constrain the generation process. The consistency-regularizer encourages the variance of tail labels to be close to head labels and further balances the whole datasets. And diversity-regularizer makes sure the generated instances have diversity and avoids generating redundant instances. Extensive experimental results on three benchmark datasets demonstrate that PIRAN consistently outperforms the SOTA methods, and dramatically improves the performance of tail labels

Electrical response and pore structure evolution affected by cyclical plasma breakdown

Artificial improvement of coal seam permeability is the key to solve the low gas drainage efficiency and prevent gas dynamic disaster. Plasma based on physical discharge is one of the effective means of coal seam antireflection. However, previous studies focus on the characterization of pore-fissure structure of single breakdown, ignore the polarization effect of plasma on coal, and lack of in-depth research on the electrical properties and the evolution characteristics of pore-fissure structure under the action of cyclical plasma of loaded coal. In this paper, the cyclical plasma breakdown experiments of coal samples were carried out. The voltage and current waveforms in the process of coal breakdown were monitored thorough combining with high-voltage attenuation rod and the Roche coil, and the variation of electrical parameters such as pre-breakdown period, plasma breakdown period, number of wave peaks, peak voltage, peak current and energy conversion efficiency were analyzed. The evolution of small pores, medium pores, large pores and micro cracks under the conditions of 1, 5, 10, 15 and 20 times of breakdown was tested by NMR. The fractal dimension of seepage pore was also discussed through geometric fractal theory. The results show that the pre-breakdown period is at the level of thousands of microseconds only for the first time, and then it will drop to tens of microseconds, while the plasma breakdown period shows a “ladder” growth with the increase of breakdown times. The energy conversion efficiency is maintained at 28.7%−55.9%, showing a trend of rapid increase at first and then stable, indicating that the polarization effect of plasma on the electrical properties of coal is limited. The growth rate of medium and large pores is the most obvious, and some micro fracture structures will achieve a “0” breakthrough, indicating that plasma will significantly improve the seepage of gas. The fractal dimension shows a decreasing trend after breakdown, which proves that the originally isolated pore structure will be connected by the fracture from the perspective of pore fracture space dimension. The similarity between the change trend of porosity and energy conversion efficiency shows that plasma has an impact on the electrical properties of coal, and the change of coal electrical properties will also have an impact on the distribution of plasma channels

Uranium Bioreduction and Biomineralization

Following the development of nuclear science and technology, uranium contamination has been an ever increasing concern worldwide because of its potential for migration from the waste repositories and long-term contaminated environments. Physical and chemical techniques for uranium pollution are expensive and challenging. An alternative to these technologies is microbially mediated uranium bioremediation in contaminated water and soil environments due to its reduced cost and environmental friendliness. To date, four basic mechanisms of uranium bioremediation-uranium bioreduction, biosorption, biomineralization, and bioaccumulation-have been established, of which uranium bioreduction and biomineralization have been studied extensively. The objective of this review is to provide an understanding of recent developments in these two fields in relation to relevant microorganisms, mechanisms, influential factors, and obstacles

High‐Titer Hepatitis C Virus Production in a Scalable Single‐Use High Cell Density Bioreactor

Hepatitis C virus (HCV) infections pose a major public health burden due to high chronicity rates and associated morbidity and mortality. A vaccine protecting against chronic infection is not available but would be important for global control of HCV infections. In this study, cell culture-based HCV production was established in a packed-bed bioreactor (CelCradle™) aiming to further the development of an inactivated whole virus vaccine and to facilitate virological and immunological studies requiring large quantities of virus particles. HCV was produced in human hepatoma-derived Huh7.5 cells maintained in serum-free medium on days of virus harvesting. Highest virus yields were obtained when the culture was maintained with two medium exchanges per day. However, increasing the total number of cells in the culture vessel negatively impacted infectivity titers. Peak infectivity titers of up to 7.2 log(10) focus forming units (FFU)/mL, accumulated virus yields of up to 5.9 × 10(10) FFU, and a cell specific virus yield of up to 41 FFU/cell were obtained from one CelCradle™. CelCradle™-derived and T flask-derived virus had similar characteristics regarding neutralization sensitivity and buoyant density. This packed-bed tide-motion system is available with larger vessels and may thus be a promising platform for large-scale HCV production

SARS-COV-2 production in a single-use scalable high cell density bioreactor

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and the fast development of first-generation vaccines have demonstrated the value of applying a variety of vaccine technology platforms (1). Inactivated vaccines represent a well-known approach, and their manufacturing depends on high-yield virus production in appropriate biosafety level facilities. This study (2) aimed to establish efficient Vero (WHO) cell-based and animal component-free SARS-CoV-2 production in the CelCradle bioreactor (Esco Aster Pte Ltd.). The single-use culture vessels pre-packed with 0.1 L BioNOCII carriers are highly useful for small scale cultivation of adherent cell lines. Cultures were seeded with 1.5 × 10⁸ cells and total cell numbers peaked at 9 days post cell seeding (dpcs) with 2.7–2.8 × 10⁹ cells/vessel in non-infected cultures. To produce virus, cultures were infected at 7 dpcs at total cell numbers of 2.2–2.5 × 10⁹ cells/vessel at a multiplicity of infection of 0.006. Harvest of virus-containing supernatant twice instead of once per day improved the virus yield by 2–7 fold. Introducing a temperature shift from 37°C to 33°C upon the time of infection improved virus yield by 2–9 fold with a considerable decline of infectious titer only after 72 h post infection (hpi). Infectious titers peaked at 7.3 log₁₀ 50% tissue culture infectious dose (TCID₅₀)/mL at 72 hpi, and a total of 10.5 log₁₀ TCID₅₀ were produced in ~5 L (11 harvests). While trypsin has been reported to enhance SARS-CoV-2 spread in cell culture, addition of 0.5% recombinant trypsin from the time of infection did not affect virus yield. Overall, animal component-free production of SARS-CoV-2 in Vero (WHO) cells was successfully established in a single-use packed-bed bioreactor. β-propiolactone inactivated SARS-CoV-2 from this study was immunogenic and induced neutralizing antibodies in mice with mean 50% neutralization titers of 1/150 or 1/580 after three immunizations with doses containing 0.1 µg or 0.5 µg S1 protein, respectively. The CelCradle represents a scalable technology and is a small version of the TideXCell system applying single-use culture vessels with packed-bed volumes of up to 100 L. The potential rapid response to outbreaks with inactivated vaccines has been demonstrated in the SARS-CoV-2 pandemic (1). Vero cells are susceptible to a wide range of viral pathogens (3), and these scalable single-use bioreactors provide a high level of flexibility and potentially decreased response time for production of future emerging viruses for vaccine purposes. References: (1) Poland 2020 Lancet [PMID: 33065034], (2) Offersgaard 2021 Vaccines [PMID: 34209694], (3) Barret 2009 Expert Rev. Vaccines [PMID: 19397417

Increased CD45RA+FoxP3low Regulatory T Cells with Impaired Suppressive Function in Patients with Systemic Lupus Erythematosus

BACKGROUND: The role of naturally occurring regulatory T cells (Treg) in the control of the development of systemic lupus erythematosus (SLE) has not been well defined. Therefore, we dissect the phenotypically heterogeneous CD4(+)FoxP3(+) T cells into subpopulations during the dynamic SLE development. METHODLOGY/PRINCIPAL FINDINGS: To evaluate the proliferative and suppressive capacities of different CD4(+) T cell subgroups between active SLE patients and healthy donors, we employed CD45RA and CD25 as surface markers and carboxyfluorescein diacetatesuccinimidyl ester (CFSE) dilution assay. In addition, multiplex cytokines expression in active SLE patients was assessed using Luminex assay. Here, we showed a significant increase in the frequency of CD45RA(+)FoxP3(low) naive Treg cells (nTreg cells) and CD45RA(-)FoxP3(low) (non-Treg) cells in patients with active SLE. In active SLE patients, the increased proportions of CD45RA(+)FoxP3(low) nTreg cells were positively correlated with the disease based on SLE disease activity index (SLEDAI) and the status of serum anti-dsDNA antibodies. We found that the surface marker combination of CD25(+)CD45RA(+) can be used to defined CD45RA(+)FoxP3(low) nTreg cells for functional assays, wherein nTreg cells from active SLE patients demonstrated defective suppression function. A significant correlation was observed between inflammatory cytokines, such as IL-6, IL-12 and TNFα, and the frequency of nTreg cells. Furthermore, the CD45RA(+)FoxP3(low) nTreg cell subset increased when cultured with SLE serum compared to healthy donor serum, suggesting that the elevated inflammatory cytokines of SLE serum may promote nTreg cell proliferation/expansion. CONCLUSIONS/SIGNIFICANCE: Our results indicate that impaired numbers of functional CD45RA(+)FoxP3(low) naive Treg cell and CD45RA(-)FoxP3(low) non-suppressive T cell subsets in inflammatory conditions may contribute to SLE development. Therefore, analysis of subsets of FoxP3(+) T cells, using a combination of FoxP3, CD25 and CD45RA, rather than whole FoxP3(+) T cells, will help us to better understand the pathogenesis of SLE and may lead to the development of new therapeutic strategies

Does Head Label Help for Long-Tailed Multi-Label Text Classification

Multi-label text classification (MLTC) aims to annotate documents with the most relevant labels from a number of candidate labels. In real applications, the distribution of label frequency often exhibits a long tail, i.e., a few labels are associated with a large number of documents (a.k.a. head labels), while a large fraction of labels are associated with a small number of documents (a.k.a. tail labels). To address the challenge of insufficient training data on tail label classification, we propose a Head-to-Tail Network (HTTN) to transfer the meta-knowledge from the data-rich head labels to data-poor tail labels. The meta-knowledge is the mapping from few-shot network parameters to many-shot network parameters, which aims to promote the generalizability of tail classifiers. Extensive experimental results on three benchmark datasets demonstrate that HTTN consistently outperforms the state-of-the-art methods. The code and hyper-parameter settings are released for reproducibility