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Multimodal machine translation (MMT) is a method that uses visual information to guide text translation. However, recent studies have engendered controversy regarding the extent to which MMT can contribute to the improvement of text-enhanced translation. To explore whether the MMT model can improve translation performance, we use the current Neural Machine Translation (NMT) system for evaluation at Multi30K dataset. Specifically, we judge the performance of the MMT model by comparing the difference between the NMT model and the MMT model. At the same time, we conduct text and multimodal degradation experiments to verify whether vision can play a role. We explored the performance of the NMT model and the MMT model for sentences of different lengths to clarify the pros and cons of the MMT model. We found that the performance of the current NMT model surpasses that of the MMT model, suggesting that the impact of visual features might be less significant. Visual features seem to exert influence primarily when a substantial number of words in the source text are masked. [ABSTRACT FROM AUTHOR]

Pollen allergy is a common disease in the department of allergy, and its incidence is increasing year by year, seriously affecting human health. As an important task in palynology, pollen identification is widely used in several fields, such as pollen allergy meteorological index forecasting. Despite its wide range of applications, pollen identification is still, in most cases, carried out manually by professionals, and the whole procedure is tedious and time-consuming. In the last few years, the convolutional neural network based on deep learning has demonstrated excellent performance in visual tasks, such as image recognition. Applying a deep learning solution for recognizing the pollen grains can enhance the pollen identification accuracy and reduce human participation time. In this study, we designed a pollen recognition model on the base of DenseNet combined with an improved dual attention module, which can effectively enhance the pollen identification accuracy by remodeling features in two dimensions: space and channel. Our attention module can be easily integrated into other CNNs and Vision Transformers, and both have a different magnitude of performance improvement. In addition to that, our method has better recognition performance than other most SOTA attention methods. During the experiment, we used a self-built pollen dataset and four public datasets. The proposed method can achieve up to 96.1 % classification accuracy, 94.9 % recall, 95.2 % precision, and 95.6 % F1 score on the self-built electron-microscopic pollen dataset. In addition, the same 1–2% performance improvement can be obtained on the public datasets and all experiments were trained from scratch. [ABSTRACT FROM AUTHOR]

Maize is a widely cultivated crop in the world, so it is of great significance to identify maize diseases efficiently. We propose to introduce the Convolutional Block Attention Module (CBAM) into the autoencoder. Enhancing feature interpretability using image reconstruction techniques in maize leaf disease identification. In this work, the discrete wavelet transform was used to carry out preliminary dimensionality reduction for images. CBAM deduced the attention diagram of feature maps from space and channel respectively in the encoder, extracted image features, and eventually compressed them to Latent-space for classification. The decoder uses Latent-space as input to reconstruct the original image. In the testing phase, only the encoder is used for prediction. The experimental dataset used maize data from PlantVillage. The average accuracy of the model reached 99.44% and the training time was 123s. Compared with MobileNet, VGG16, Inception V3, ResNet-50, DenseNet201, this model has a good performance on maize data. [ABSTRACT FROM AUTHOR]

Long‐term complications from coronavirus disease 2019 (COVID‐19) are concerning, as survivors can develop subclinical multiorgan dysfunction. It is unknown if such complications are due to prolonged inflammation, and severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) vaccination may reduce sequela. We conducted a prospective longitudinal study on hospitalized patients over 24 months. Clinical symptoms were collected by self‐reporting during follow‐up, along with blood samples for quantification of inflammatory markers and immune cell frequencies. All patients were given one dose of mRNA vaccine at 12−16 months. Their immune profiles at 12 and 24 months were compared. Approximately 37% and 39% of our patients reported post‐COVID‐19 symptoms at 12 and 24 months, respectively. The proportion of symptomatic patients with more than one symptom decreased from 69% at 12 months to 56% at 24 months. Longitudinal cytokine profiling revealed a cluster of individuals with persistently high inflammatory cytokine levels 12 months after infection. Patients with prolonged inflammation showed elevated terminally differentiated memory T cells in their blood; 54% had symptoms at 12 months. The majority of inflammatory markers and dysregulated immune cells in vaccinated patients recovered to a healthy baseline at 24 months, even though symptoms persisted. Post‐COVID‐19 symptoms can linger for 2 years after the initial infection and are associated with prolonged inflammation. Prolonged inflammation in hospitalized patients resolves after 2 years. We define a set of analytes associated with persistent inflammation and presence of symptoms, which could be useful biomarkers for identifying and monitoring high‐risk survivors. [ABSTRACT FROM AUTHOR]

Large numbers of neutrophils infiltrate tumors and comprise a notable component of the inflammatory tumor microenvironment. While it is established that tumor cells exhibit the Warburg effect for energy production, the contribution of the neutrophil metabolic state to tumorigenesis is unknown. Here, we investigated whether neutrophil infiltration and metabolic status promotes tumor progression in an orthotopic mouse model of pancreatic ductal adenocarcinoma (PDAC). We observed a large increase in the proportion of neutrophils in the blood and tumor upon orthotopic transplantation. Intriguingly, these tumor-infiltrating neutrophils up-regulated glycolytic factors and hypoxia-inducible factor 1-alpha (HIF-1α) expression compared to neutrophils from the bone marrow and blood of the same mouse. This enhanced glycolytic signature was also observed in human PDAC tissue samples. Strikingly, neutrophil-specific deletion of HIF-1α (HIF-1αΔNφ) significantly reduced tumor burden and improved overall survival in orthotopic transplanted mice, by converting the pro-tumorigenic neutrophil phenotype to an anti-tumorigenic phenotype. This outcome was associated with elevated reactive oxygen species production and activated natural killer cells and CD8+ cytotoxic T cells compared to littermate control mice. These data suggest a role for HIF-1α in neutrophil metabolism, which could be exploited as a target for metabolic modulation in cancer. [ABSTRACT FROM AUTHOR]

Pollen identification is a sub-discipline of Palynology, which has broad applications in several fields such as allergy control, paleoclimate reconstruction, criminal investigation, and petroleum exploration. Among these, pollen allergy is a common and frequent disease worldwide. Accurate and rapid identification of pollen species under the electron microscope help medical staff in pollen forecast and interrupt the natural course of pollen allergy. The current pollen species identification needs to rely on professional researchers to identify pollen particles in pictures manually, and this time-consuming and laborious way cannot meet the requirements of pollen forecasting. Recently, the self-attention based Transformer has attracted considerable attention in vision tasks, such as image classification. However, pure self-attention lacks local operations on pixels and requires large-scale dataset pretraining to achieve comparable performance to convolutional neural networks (CNN). In this study, we propose a new Vision Transformer pipeline for image classification. First, we design a FeatureMap-to-Token (F2T) module to perform token embedding on the input image. A global self-attention operation is performed on the basis of tokens with local information, and the hierarchical design of CNN is applied to the Vision Transformer, combining local and global strengths in multiscale spaces. Second, we use a distillation strategy to learn the feature representation in the output space of the teacher network to further learn the inductive bias in the CNN to improve the recognition accuracy. Experiments demonstrate that the proposed model achieves CNN-equivalent performance under the same conditions after being trained from scratch on the electron-microscopic pollen dataset. It also requires less model parameters and training time. Code for the model is available at https://github.com/dkbshuai/PyTorch-Our-S. [ABSTRACT FROM AUTHOR]

Background: The ichthyoses are rare genetic keratinizing disorders that share the characteristics of an impaired epidermal barrier and increased risk of microbial infections. Although ichthyotic diseases share a T helper (Th) 17 cell immune signature, including increased expression of antimicrobial peptides, the skin microbiota of ichthyoses is virtually unexplored. Objectives: To analyse the metagenome profile of skin microbiome for major congenital ichthyosis subtypes. Methods: Body site‐matched skin surface samples were collected from the scalp, upper arm and upper buttocks of 16 healthy control participants and 22 adult patients with congenital forms of ichthyosis for whole metagenomics sequencing analysis. Results: Taxonomic profiling showed significant shifts in bacteria and fungi abundance and sporadic viral increases across ichthyosis subtypes. Cutibacterium acnes and Malassezia were significantly reduced across body sites, consistent with skin barrier disruption and depletion of lipids. Microbial richness was reduced, with specific increases in Staphylococcus and Corynebacterium genera, as well as shifts in fungal species, including Malassezia. Malassezia globosa was reduced at all body sites, whereas M. sympodialis was reduced in the ichthyotic upper arm and upper buttocks. Malassezia slooffiae, by contrast, was strikingly increased at all body sites in participants with congenital ichthyosiform erythroderma (CIE) and lamellar ichthyosis (LI). A previously undescribed Trichophyton species was also detected as sporadically colonizing the skin of patients with CIE, LI and epidermolytic ichthyosis subtypes. Conclusions: The ichthyosis skin microbiome is significantly altered from healthy skin with specific changes predominating among ichthyosis subtypes. Skewing towards the Th17 pathway may represent a response to the altered microbial colonization in ichthyosis. What is already known about this topic?The skin microbiome of congenital ichthyoses is largely unexplored.Microbes play an important role in pathogenesis, as infections are common.The relative abundances of staphylococci and corynebacteria is increased in the cutaneous microbiome of patients with Netherton syndrome, but extension of these abundances to all congenital ichthyoses is unexplored. What does this study add?A common skin microbiome signature was observed across congenital ichthyoses.Distinct microbiome features were associated with ichthyosis subtypes.Changes in microbiome may contribute to T helper 17 cell immune polarization. What is the translational message?These data provide the basis for comparison of the microbiome with lipidomic and transcriptomic alterations in these forms of ichthyosis and consideration of correcting the dysbiosis as a therapeutic intervention. [ABSTRACT FROM AUTHOR]

Background: Human rhinoviruses (HRVs) are frequently associated with asthma exacerbations, and have been found in the airways of asthmatic patients. While HRV‐induced acute infection is well‐documented, it is less clear whether the nasal epithelium sustains prolonged HRV infections along with the associated activation of host immune responses. Objective: To investigate sustainably regulated host responses of human nasal epithelial cells (hNECs) during HRV persistence. Methods: Using a time‐course study, HRV16 persistence and viral replication dynamics were established using an in vitro infection model of hNECs. RNA sequencing was performed on hNECs in the early and late stages of infection at 3 and 14 days post‐infection (dpi), respectively. The functional enrichment of differentially expressed genes (DEGs) was evaluated using gene ontology (GO) and Ingenuity pathway analysis. Results: HRV RNA and protein expression persisted throughout prolonged infections, even after decreased production of infectious virus progeny. GO analysis of unique DEGs indicated altered regulation of pathways related to ciliary function and airway remodeling at 3 dpi and serine‐type endopeptidase activity at 14 dpi. The functional enrichment of shared DEGs between the two time‐points was related to interferon (IFN) and cytoplasmic pattern recognition receptor (PRR) signaling pathways. Validation of the sustained regulation of candidate genes confirmed the persistent expression of RIG‐I and revealed its close co‐regulation with interferon‐stimulated genes (ISGs) during HRV persistence. Conclusions: The persistence of HRV RNA does not necessarily indicate an active infection during prolonged infection. The sustained expression of RIG‐I and ISGs in response to viral RNA persistence highlights the importance of assessing how immune‐activating host factors can change during active HRV infection and the immune regulation that persists thereafter. [ABSTRACT FROM AUTHOR]

The advent of the Omicron variant globally has hastened the requirement for a booster vaccination dose to confer continuous protection against symptomatic SARS-CoV2 infection. However, different vaccines are available in different countries, and individuals who had adverse reactions to certain vaccine types require heterologous vaccine boosters. To understand the efficacy of different vaccination regimens in inducing humoral responses to SARS-CoV2, we examined plasma antibodies and frequencies of Omicron RBD-specific B cells in individuals who had different priming-booster vaccination regimens. We found that individuals with three homologous doses of mRNA vaccines had higher levels of IgG of all subclasses against RBD of Omicron than individuals with three homologous doses of inactivated virus vaccine. A booster with mRNA vaccine resulted in significant increases in median levels of RBD-reactive IgG1 (17–19 fold) and IgG3 (2.3–3.3 fold) as compared to individuals receiving inactivated virus booster shots regardless of priming vaccine types. More importantly, individuals who received a booster dose of mRNA vaccine, irrespective of the priming vaccine, had antibodies with higher neutralizing capability against the Omicron variant than those who received a booster dose of inactivated virus vaccine. Corroborating the antibody results, boosting with the mRNA vaccine increased the frequencies of Omicron RBD-binding B cells by (1.5–3.3 fold) regardless of priming vaccine types. Together, our data demonstrate that an mRNA vaccine (BNT162b2 or mRNA-1273) booster enhances humoral responses against the Omicron variant in individuals vaccinated with either two prior doses of mRNA or inactivated virus vaccine (CoronaVac or BBIBP-CorV), potentially providing more effective protection against SARS-CoV-2 infection, particularly by the Omicron variant. [ABSTRACT FROM AUTHOR]

Conversely, tissue neutrophil association with LM scores in N-ERD patients suggests that neutrophils contribute to the severity of the polyp burden in N-ERD. Neutrophilic inflammation and epithelial barrier disruption in nasal polyps characterize non-steroidal anti-inflammatory drug exacerbated respiratory disease Neutrophil counts were higher in the nasal polyp tissues of N-ERD patients (8.5 cells per hpf (IQR 3-25) vs. 2.5 cells (IQR 2-5) in non-N-ERD ( I p i = .026, Figure 1B). [Extracted from the article]

Various forms of immunotherapy, such as checkpoint blockade immunotherapy, are proving to be effective at restoring T cell-mediated immune responses that can lead to marked and sustained clinical responses, but only in some patients and cancer types [1]- [4]. Patients and tumours may respond unpredictably to immunotherapy partly owing to heterogeneity of the immune composition and phenotypic profiles of tumour-infiltrating lymphocytes (TILs) within individual tumours and between patients [5], [6]. Although there is evidence that tumour-mutation-derived neoantigen-specific T cells play a role in tumour control [2], [4], [7]- [10], in most cases the antigen specificities of phenotypically diverse tumour-infiltrating T cells are largely unknown. Here we show that human lung and colorectal cancer CD8+ TILs can not only be specific for tumour antigens (for example, neoantigens), but also recognize a wide range of epitopes unrelated to cancer (such as those from Epstein-Barr virus, human cytomegalovirus or influenza virus). We found that these bystander CD8+ TILs have diverse phenotypes that overlap with tumour-specific cells, but lack CD39 expression. In colorectal and lung tumours, the absence of CD39 in CD8+ TILs defines populations that lack hallmarks of chronic antigen stimulation at the tumour site, supporting their classification as bystanders. Expression of CD39 varied markedly between patients, with some patients having predominantly CD39− CD8+ TILs. Furthermore, frequencies of CD39 expression among CD8+ TILs correlated with several important clinical parameters, such as the mutation status of lung tumour epidermal growth factor receptors. Our results demonstrate that not all tumour-infiltrating T cells are specific for tumour antigens, and suggest that measuring CD39 expression could be a straightforward way to quantify or isolate bystander T cells. Human lung and colorectal tumours contain a population of tumour-infiltrating lymphocytes that are specific for tumour-unrelated antigens and, unlike tumour-antigen-specific tumour-infiltrating lymphocytes, do not express CD39. [ABSTRACT FROM AUTHOR]

During gestation the developing human fetus is exposed to a diverse range of potentially immune-stimulatory molecules including semi-allogeneic antigens from maternal cells, substances from ingested amniotic fluid, food antigens, and microbes. Yet the capacity of the fetal immune system, including antigen-presenting cells, to detect and respond to such stimuli remains unclear. In particular, dendritic cells, which are crucial for effective immunity and tolerance, remain poorly characterized in the developing fetus. Here we show that subsets of antigen-presenting cells can be identified in fetal tissues and are related to adult populations of antigen-presenting cells. Similar to adult dendritic cells, fetal dendritic cells migrate to lymph nodes and respond to toll-like receptor ligation; however, they differ markedly in their response to allogeneic antigens, strongly promoting regulatory T-cell induction and inhibiting T-cell tumour-necrosis factor-α production through arginase-2 activity. Our results reveal a previously unappreciated role of dendritic cells within the developing fetus and indicate that they mediate homeostatic immune-suppressive responses during gestation. [ABSTRACT FROM AUTHOR]

Wharton’s jelly-derived Mesenchymal Stem Cells (MSCs) isolated from newborns with intrauterine fetal growth restriction were previously shown to exert anabolic features including insulin hypersensitivity. Here, we extend these observations and demonstrate that MSCs from small for gestational age (SGA) individuals have decreased mitochondrial oxygen consumption rates. Comparing normally grown and SGA MSCs using next generation sequencing studies, we measured global transcriptomic and epigenetic profiles and identified E2F1 as an over-expressed transcription factor regulating oxidative metabolism in the SGA group. We further show that E2F1 regulates the differential transcriptome found in SGA derived MSCs and is associated with the activating histone marks H3K27ac and H3K4me3. One of the key genes regulated by E2F1 was found to be the fatty acid elongase ELOVL2, a gene involved in the endogenous synthesis of docosahexaenoic acid (DHA). Finally, we shed light on how the E2F1-ELOVL2 pathway may alter oxidative respiration in the SGA condition by contributing to the maintenance of cellular metabolic homeostasis. [ABSTRACT FROM AUTHOR]

The article discusses a study related to filling-succession of sedimentary basin for the lower Jurassic of the Yangtze in China. It mentions that theory of sequence stratigraphy, the measured field profile and logging data related to sedimentary basin. It also informs about Tongzuyuan Group of Lower Jurassic in the Jingmen-Dangyang region to the east of the Huangling anticline, with the largest thickness, contains three third-order sequences.