Miracle-dz/UniFAR-FTUs huggingface dataset:
Sublethal Staphylococcal Enterotoxin B Challenge Model in Pigs To Evaluate Protection following Immunization with a Soybean-Derived Vaccine

ABSTRACT In an effort to develop a sustainable platform for manufacturing protein-based vaccine candidates, we expressed a triple mutant of staphylococcal enterotoxin B carrying the L45R, Y89A, and Y94A modifications in transgenic soybean seeds (soy-mSEB). Soy-mSEB possessed no detectable superantigen activity in vitro. We found that this soybean-derived, nontoxic mutant of SEB could be stably expressed, stored in seeds for extended periods at room temperature without degradation, and easily purified from contaminating soy proteins. Vaccination of pigs with purified soy-mSEB, or the identical triple mutant expressed in Escherichia coli (E. coli-mSEB), resulted in high antibody titers against the native toxin in immunized animals. In fact, titers were indistinguishable regardless of the immunogen used, demonstrating the equivalence of soy-mSEB and E. coli-mSEB vaccinations. Antisera from either immunized group were able to block native SEB superantigen activity in an in vitro neutralization assay. Similar results were obtained when immunized animals were challenged with a sublethal dose of native toxin. Significant reductions in toxin-induced serum cytokine levels were observed in soy-mSEB- and E. coli-mSEB-immunized pigs compared to control animals. The reductions in SEB-induced cytokine responses were similar regardless of the immunogen used for vaccination. Surprisingly, however, some clinical symptoms, such as prostration, lethargy, emesis, and/or diarrhea, were still observed in all immunized animals. These studies demonstrate the potential for soybean-derived proteins as a platform technology for sustainable vaccine manufacturing and the usefulness of a sublethal challenge model in pigs for evaluating the efficacy of potential SEB vaccine candidates.
Exercise and Sleep Deprivation Do Not Change Cytokine Expression Levels in Patients with Chronic Fatigue Syndrome

ABSTRACT A major hypothesis regarding the cause of chronic fatigue syndrome (CFS) is immune dysregulation, thought to be reflected in upregulated proinflammatory cytokines leading to the symptoms that are characteristic of this illness. Because the symptoms worsen with physical exertion or sleep loss, we hypothesized that we could use these stressors to magnify the underlying potential pathogenic abnormalities in the cytokine systems of people with CFS. We conducted repeat blood sampling for cytokine levels from healthy subjects and CFS patients during both postexercise and total sleep deprivation nights and assayed for protein levels in the blood samples, mRNA activity in peripheral blood lymphocytes (PBLs), and function in resting and stimulated PBLs. We found that these environmental manipulations did not produce clinically significant upregulation of proinflammatory cytokines. These data do not support an important role of immune dysregulation in the genesis of stress-induced worsening of CFS.
Interacting Roles of Immune Mechanisms and Viral Load in the Pathogenesis of Crimean-Congo Hemorrhagic Fever

ABSTRACT Until now, the pathogenesis of Crimean-Congo hemorrhagic fever (CCHF) has not been well described. However, it has been hypothesized that it could be a result of the direct injury of virus-infected tissues in combination with the indirect effects of host immune responses, including cytokines. To shed more light on the role of viral load and cytokines, differential influences of CCHF virus (CCHFV) RNA load, antibody response, and cytokine production on severity and outcome of the disease were studied in sera of 46 patients with confirmed acute CCHF from Kosovo. In this study, viral load proved to be strongly related to the severity and outcome of the disease, with higher viral loads detected in patients with fatal outcomes than in surviving patients. Also, patients with fatal outcome had on average a weaker antibody response, if one was present at all. High levels of interleukin-10 (IL-10), gamma interferon (IFN-γ), and tumor necrosis factor alpha (TNF-α) were associated with poor outcome, since detected concentrations were highest in patients with fatal outcome and lowest in patients with moderate disease course. Additionally, a positive linear dependence between viral load and these cytokines was observed. Interestingly, reduced levels of IL-12 were detected in all CCHF patients. Our study favors the hypothesis that CCHF could be a result of a delayed and downregulated immune response caused by IL-10, which leads to an increased replication and spread of CCHFV throughout the body. This consequently triggers increased production of IFN-γ and TNF-α, cytokines mediating vascular dysfunction, disseminated intravascular coagulation, organ failure, and shock.
A Relation-Based Page Rank Algorithm for Semantic Web Search Engines

With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general-purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. The next-generation Web architecture, represented by the Semantic Web, provides the layered architecture possibly allowing overcoming this limitation. Several search engines have been proposed, which allow increasing information retrieval accuracy by exploiting a key content of semantic Web resources, that is, relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. In this paper, we propose a relation-based page rank algorithm to be used in conjunction with semantic Web search engines that simply relies on information that could be extracted from user queries and on annotated resources. Relevance is measured as the probability that a retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition.
Antigen-Specific Memory B-Cell Responses in Bangladeshi Adults after One- or Two-Dose Oral Killed Cholera Vaccination and Comparison with Responses in Patients with Naturally Acquired Cholera

ABSTRACT The mediators of protective immunity against cholera are currently unknown, but memory B-cell responses may play a central role in facilitating long-term and anamnestic responses against Vibrio cholerae, the cause of cholera. We compared memory B-cell responses in adults with natural cholera in Bangladesh (n = 70) to responses in Bangladeshi adults after one-dose (n = 30) or two-dose (n = 30) administration of an oral killed cholera vaccine, WC-rBS (Dukoral; Crucell), assessing the responses at the acute stage of disease or prevaccination and then on days 3, 30, 90, 180, 270, and 360. Individuals with natural cholera developed prominent vibriocidal and plasma anti-cholera toxin B subunit (CtxB) and lipopolysaccharide (LPS) IgG and IgA responses, but these responses returned to baseline by 1 year of follow-up. Vaccinees developed plasma anti-CtxB and anti-LPS IgG and IgA responses that were generally comparable to those in individuals recovering from natural disease, but vibriocidal responses were lower in vaccinees than in infected patients. Individuals recovering from natural disease developed memory B-cell IgG and IgA anti-CtxB and anti-LPS responses by day 30, and these responses were detectable through at least days 180 to 360. In contrast, we detected no IgA or IgG memory B-cell responses to LPS in vaccinees; anti-CtxB IgA responses were only detectable on day 30, and anti-CtxB IgG responses were detectable until days 90 to 180, compared to days 270 to 360 in patients. These findings may explain in part the relatively short-term protection afforded by oral cholera vaccination compared to natural disease.
Measurement of Phenotype and Absolute Number of Circulating Heparin-Binding Hemagglutinin, ESAT-6 and CFP-10, and Purified Protein Derivative Antigen-Specific CD4 T Cells Can Discriminate Active from Latent Tuberculosis Infection

ABSTRACT The tuberculin skin test (TST) and interferon gamma (IFN-γ) release assays (IGRAs) are used as adjunctive tests for the evaluation of suspected cases of active tuberculosis (TB). However, a positive test does not differentiate latent from active TB. We investigated whether flow cytometric measurement of novel combinations of intracellular cytokines and surface makers on CD4 T cells could differentiate between active and latent TB after stimulation with Mycobacterium tuberculosis-specific proteins. Blood samples from 60 patients referred to the Singapore Tuberculosis Control Unit for evaluation for active TB or as TB contacts were stimulated with purified protein derivative (PPD), ESAT-6 and CFP-10, or heparin-binding hemagglutinin (HBHA). The CD4 T cell cytokine response (IFN-γ, interleukin-2 [IL-2], interleukin-17A [IL-17A], interleukin-22 [IL-22], granulocyte-macrophage colony-stimulating factor [GM-CSF], and tumor necrosis factor alpha [TNF-α]) and surface marker expression (CD27, CXCR3, and CD154) were then measured. We found that the proportion of PPD-specific CD4 T cells, defined as CD154+ TNF-α+ cells that were negative for CD27 and positive for GM-CSF, gave the strongest discrimination between subjects with latent and those with active TB (area under the receiver operator characteristic [ROC] curve of 0.9277; P < 0.0001). Also, the proportions and absolute numbers of HBHA-specific CD4 T cells were significantly higher in those with latent TB infection, particularly CD154+ TNF-α+ IFN-γ+ IL-2+ and CD154+ TNF-α+ CXCR3+. Finally, we found that the ratio of ESAT-6- and CFP-10-responding to HBHA-responding CD4 T cells was significantly different between the two study populations. In conclusion, we found novel markers of M. tuberculosis-specific CD4 cells which differentiate between active and latent TB.
GRANULOCYTOSIS INDUCED BY INCREASING SYMPATHETIC NERVE ACTIVITY CONTRIBUTES TO THE INCIDENCE OF ACUTE APPENDICITIS

Since the incidence of acute appendicitis seems to vary with weather, we investigated the underlying mechanism. When ll2 patients who had undergone appendectomy were classified into three groups according to atmospheric pressure at the time of onset, gangrenous cases (high infiltration of granulocytes) were much greater in frequency than catarrhal cases (no infiltration of granulocytes) at high pressure. At low pressure, the situation was the reverse. The variation of granulocytes and lymphocytes in the blood as related to atmospheric pressure and heart rate was examined in healthy donors. Granulocytosis was seen with increased sympathetic activity (high heart rate) at high pressure, whereas lymphocytosis was seen with increased parasympathetic activity (low heart rate) at low pressure. Taken together with the results from patients, in which gangrenous cases showed granulocytosis in the blood as well as in the appendix while catarrhal cases showed lymphocytosis in the blood and appendix, it is presumed that granulocytosis induced by increased sympathetic activity might be related to the onset of gangrenous appendicitis. Experimental results using human and mouse materials indicated that catecholamines induce granulocytosis via their adrenergic receptors. Even in gangrenous cases, bacteria were not detected in the vicinity of granulocytes in the appendix by electron microscopy. The present results seem to shed important light on the etiology of suppurative diseases. Many clinicians have observed that the disease state in some patients deteriorates under the influence of weather (2, 3, 5-7, 32, 35, 39). However, it is difficult to determine the mechanism underlying the host defence system related to climatic factors. One of the authors in this study has noticed for the past l0 years that severe cases of appendicitis, including perforation, tend to occur at high atmospheric pressure accompanying fine weather. To determine whether this experience is more than just incidental, 112 cases of appendicitis were examined in terms of the type of appendicitis and atmospheric pressure at the onset of disease; Although appendicitis itself occurs under conditions of any atmospheric pressure, gangrenous cases of appendicitis occur much more frequently at the time of high atmospheric pressure. We also focused our attention on the host defense system, especially on how the ratio of granulocytes and lymphocytes in the peripheral blood as well as in the appendix varies depending on atmospheric pressure in healthy donors and patients. It was demonstrated that granulocytosis occurred more frequently under high atmospheric pressure, whereas lymphocytosis occurred more frequently under low atmospheric pressure. A similar variation depending on atmospheric pressure was also seen in the blood and the appendix of patients. When we are exposed to high atmospheric pres-
Safety and Immunogenicity of DNA Prime and Modified Vaccinia Ankara Virus-HIV Subtype C Vaccine Boost in Healthy Adults

ABSTRACT A randomized, double-blind, placebo-controlled phase I trial was conducted in 32 HIV-uninfected healthy volunteers to assess the safety and immunogenicity of 3 doses of DNA vaccine (Advax) plus 1 dose of recombinant modified vaccinia virus Ankara (MVA) (TBC-M4) or 3 doses of TBC-M4 alone (groups A and B, respectively). Both vaccine regimens were found to be safe and well tolerated. Gamma interferon (IFN-γ) enzyme-linked immunosorbent spot (ELISPOT) assay responses were detected in 1/10 (10%) individuals in group A after three Advax primes and in 9/9 individuals (100%) after the MVA boost. In group B, IFN-γ ELISPOT responses were detected in 6/12 (50%) and 7/11 (64%) individuals after the second and third MVA vaccinations, respectively. Responses to all vaccine components, but predominantly to Env, were seen. The breadth and magnitude of the T cell response and viral inhibition were greater in group A than in group B, indicating that the quality of the T-cell response was enhanced by the DNA prime. Intracellular cytokine staining indicated that the T-cell responses were polyfunctional but were skewed toward Env with a CD4+ phenotype. At 2 weeks after the last vaccination, HIV-specific antibody responses were detected in all (100%) group B and 1/11 (9.1%) group A vaccinees. Vaccinia virus-specific responses were detected in all (100%) group B and 2/11 (18.2%) group A vaccinees. In conclusion, HIV-specific T-cell responses were seen in the majority of volunteers in groups A and B but with a trend toward greater quality of the T-cell response in group A. Antibody responses were better in group B than in group A.
Learning rotation invariance in deep hierarchies using circular symmetric filters

Deep hierarchical models for feature learning have emerged as an effective technique for object representation and classification in recent years. Though the features learnt using deep models have shown lot of promise towards achieving invariance to data transformations, this primarily comes at the expense of using much larger training data and model size. In the proposed work we devise a novel technique to incorporate rotation invariance, while training the deep model parameters. The convolution weight parameters in the network architecture are constrained to exhibit circular symmetry resulting in “rotation equivariance” of output feature maps. Rotation invariance is further achieved by max-pooling of the feature maps later in the hierarchy. We also show that by incorporating circular symmetry constraint into the training loss function, rotation invariance can be achieved with-in deep neural network framework with much lesser training data and model parameters. Our experiment results evaluated on rotated MNIST dataset further objectively validate the contribution.
The Transforming Growth Factor (cid:2) 1/Interleukin-31 Pathway Is Upregulated in Patients with Hepatitis B Virus-Related Acute-on-Chronic Liver Failure and Is Associated with Disease Severity and Survival

The transforming growth factor (cid:2) 1/interleukin-31 (TGF- (cid:2) 1/IL-31) pathway plays an important role in the process of cell injury and inﬂammation. The purpose of this work was to explore the role of the TGF- (cid:2) 1/IL-31 pathway in the cytopathic process of hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF). The quantitative serum levels of TGF- (cid:2) 1, IL-9, IL-10, IL-17, IL-22, IL-23, IL-31, IL-33, and IL-35 were analyzed among chronic hepatitis B (CHB) patients ( n (cid:3) 17), ACLF patients ( n (cid:3) 18), and normal control (NC) subjects ( n (cid:3) 18). Disease severity in patients with ACLF was assessed using the model for end-stage liver disease (MELD) and Child-Pugh scores. Serum TGF- (cid:2) 1 levels were strongly positively correlated with IL-31 in all subjects, and both of them were positively correlated with IL-17, IL-22, and IL-33. In CHB and ACLF patients, serum levels of TGF- (cid:2) 1 and IL-31 were both increased signiﬁcantly compared with those in NC subjects and positively correlated with total bilirubin (TBil) and alpha-fetoprotein (AFP) levels. ACLF patients showed the highest levels of TGF- (cid:2) 1 and IL-31, which were positively correlated with Child-Pugh scores. Furthermore, the recovery from the liver injury in CHB was accompanied by decreased TGF- (cid:2) 1 and IL-31 levels. More importantly, serum levels of TGF- (cid:2) 1 and IL-31 were markedly upregulated in ACLF nonsurvivors, and IL-31 displayed the highest sensitivity and speciﬁcity (85.7% and 100.0%, respectively) in predicting nonsurvival of ACLF patients. Increasing activity of the TGF- (cid:2) 1/IL-31 pathway is well correlated with the extent of liver injury, disease severity, and nonsurvival of ACLF patients, while reducing activity is detected along the recovery from liver injury in CHB, suggesting its potential role in the pathogenesis of liver injury during chronic HBV infection.
Joint CTC-attention based end-to-end speech recognition using multi-task learning

Recently, there has been an increasing interest in end-to-end speech recognition that directly transcribes speech to text without any predefined alignments. One approach is the attention-based encoder-decoder framework that learns a mapping between variable-length input and output sequences in one step using a purely data-driven method. The attention model has often been shown to improve the performance over another end-to-end approach, the Connectionist Temporal Classification (CTC), mainly because it explicitly uses the history of the target character without any conditional independence assumptions. However, we observed that the performance of the attention has shown poor results in noisy condition and is hard to learn in the initial training stage with long input sequences. This is because the attention model is too flexible to predict proper alignments in such cases due to the lack of left-to-right constraints as used in CTC. This paper presents a novel method for end-to-end speech recognition to improve robustness and achieve fast convergence by using a joint CTC-attention model within the multi-task learning framework, thereby mitigating the alignment issue. An experiment on the WSJ and CHiME-4 tasks demonstrates its advantages over both the CTC and attention-based encoder-decoder baselines, showing 5.4–14.6% relative improvements in Character Error Rate (CER).
Erratum to "Mining Distinction and Commonality across Multiple Domains Using Generative Model for Text Classification"

The distribution difference among multiple domains has been exploited for cross-domain text categorization in recent years. Along this line, we show two new observations in this study. First, the data distribution difference is often due to the fact that different domains use different index words to express the same concept. Second, the association between the conceptual feature and the document class can be stable across domains. These two observations actually indicate the distinction and commonality across domains. Inspired by the above observations, we propose a generative statistical model, named Collaborative Dual-PLSA (CD-PLSA), to simultaneously capture both the domain distinction and commonality among multiple domains. Different from Probabilistic Latent Semantic Analysis (PLSA) with only one latent variable, the proposed model has two latent factors y and z, corresponding to word concept and document class, respectively. The shared commonality intertwines with the distinctions over multiple domains, and is also used as the bridge for knowledge transformation. An Expectation Maximization (EM) algorithm is developed to solve the CD-PLSA model, and further its distributed version is exploited to avoid uploading all the raw data to a centralized location and help to mitigate privacy concerns. After the training phase with all the data from multiple domains we propose to refine the immediate outputs using only the corresponding local data. In summary, we propose a two-phase method for cross-domain text classification, the first phase for collaborative training with all the data, and the second step for local refinement. Finally, we conduct extensive experiments over hundreds of classification tasks with multiple source domains and multiple target domains to validate the superiority of the proposed method over existing state-of-the-art methods of supervised and transfer learning. It is noted to mention that as shown by the experimental results CD-PLSA for the collaborative training is more tolerant of distribution differences, and the local refinement also gains significant improvement in terms of classification accuracy.
Domain adaptation of DNN acoustic models using knowledge distillation

Constructing deep neural network (DNN) acoustic models from limited training data is an important issue for the development of automatic speech recognition (ASR) applications that will be used in various application-specific acoustic environments. To this end, domain adaptation techniques that train a domain-matched model without overfitting by lever-aging pre-constructed source models are widely used. In this paper, we propose a novel domain adaptation method for DNN acoustic models based on the knowledge distillation framework. Knowledge distillation transfers the knowledge of a teacher model to a student model and offers better generalizability of the student model by controlling the shape of posterior probability distribution of the teacher model, which was originally proposed for model compression. We apply this framework to model adaptation. Our domain adaptation method avoids overfitting of the adapted model trained on limited data by transferring the knowledge of the source model to the adapted model by distillation. Experiments show that the proposed method can effectively avoid the overfitting of convolutional neural network based acoustic models and yield lower error rates than conventional adaptation methods.