Agri-food supply chain management : Bibliometric and content analyses

Agri-food supply chain management (ASCM) research has gained attraction in recent years. This study aims to examine the knowledge structure, trace the evolution of, and propose future research directions for ASCM by a systematic literature review combined with bibliometric and content analyses. A total of 1770 articles were selected from Scopus for bibliometric analyses. We conducted a content analysis based on 188 articles in six clusters selected from the co-citation analysis. This review provides insights into key authors, their affiliations, journal quality, and the prestige of the reviewed articles, aspects that have not been fully captured or evaluated by previous reviews. Using bibliometric tools, we identified six clusters for ASCM, based on which, future research directions are proposed. Content analysis provides additional insights in each cluster. In particular, sustainability runs through all the themes identified except for one

A New Convolutional Neural Network Architecture for Automatic Segmentation of Overlapping Human Chromosomes

In clinical diagnosis, karyotyping is carried out to detect genetic disorders due to chromosomal aberrations. Accurate segmentation is crucial in this process that is mostly operated by experts. However, it is time-consuming and labor-intense to segment chromosomes and their overlapping regions. In this research, we look into the automatic segmentation of overlapping pairs of chromosomes. Different from standard semantic segmentation applications that mostly detect object regions or boundaries, this study attempts to predict not only non-overlapping regions but also the order of superposition and opaque regions of the underlying chromosomes. We propose a novel convolutional neural network called Compact Seg-UNet with enhanced deep feature learning capability and training efficacy. To address the issue of unrealistic images in use characterized by overlapping regions of higher color intensities, we propose a novel method to generate more realistic images with opaque overlapping regions. On the segmentation performance of overlapping chromosomes for this new dataset, our Compact Seg-UNet model achieves an average IOU score of 93.44% ± 0.26 which is significantly higher than the result of a simplified U-Net reported by literature by around 6.08%. The corresponding F1 score also increases from 0.9262 ± 0.1188 to 0.9596 ± 0.0814

A Novel Application of Image-to-Image Translation: Chromosome Straightening Framework by Learning from a Single Image

In medical imaging, chromosome straightening plays a significant role in the pathological study of chromosomes and in the development of cytogenetic maps. Whereas different approaches exist for the straightening task, typically geometric algorithms are used whose outputs are characterized by jagged edges or fragments with discontinued banding patterns. To address the flaws in the geometric algorithms, we propose a novel framework based on image-to-image translation to learn a pertinent mapping dependence for synthesizing straightened chromosomes with uninterrupted banding patterns and preserved details. In addition, to avoid the pitfall of deficient input chromosomes, we construct an augmented dataset using only one single curved chromosome image for training models. Based on this framework, we apply two popular image-to-image translation architectures, U-shape networks and conditional generative adversarial networks, to assess its efficacy. Experiments on a dataset comprised of 642 real-world chromosomes demonstrate the superiority of our framework, as compared to the geometric method in straightening performance, by rendering realistic and continued chromosome details. Furthermore, our straightened results improve the chromosome classification by 0.98%-1.39% mean accuracy.Comment: This work has been accepted by CISP-BMEI202

HLA alleles, COVID-19 vaccine antibody response and real-world breakthrough outcomes

The rapid development, approval, and global distribution of COVID-19 vaccines represent an unprecedented intervention in public health history, with over 13 billion doses administered worldwide in two years. However, our understanding of the HLA genetic underpinnings of COVID-19 vaccine-induced antibody responses and their clinical implications for breakthrough outcomes remain limited. To bridge this knowledge gap, we designed and performed a series of genetic and epidemiological analyses among 368,098 vaccinated individuals, and a subset of 194,371 participants who had antibody serology tests. Firstly, we corroborated earlier findings that SNPs associated with antibody response were predominantly located in Major Histocompatibility Complex region, and that the expansive HLA-DQB106 allele family was linked to better antibody responses. However, our findings contest the claim that DQB106 alleles alone significantly impact breakthrough risks. Additionally, our results suggest that the specific DQB106:04 subtype could be the true causal allele, as opposed to the previously reported DQB106:02. Secondly, we identified and validated six new functional HLA alleles that independently contribute to vaccine-induced antibody responses. Moreover, we unravelled additive effects of variations across multiple HLA genes that, concurrently, change the risk of clinically relevant breakthrough COVID-19 outcomes. Finally, we detangled the overall vaccine effectiveness and showed that antibody positivity accounts for approximately 20% protection against breakthrough infection and 50% against severe outcomes. These novel findings provide robust population evidence demonstrating how variations within HLA genes strongly, collectively, and causally influence vaccine-induced antibody responses, and the risk of COVID-19 breakthrough infection and related outcomes, with implications for subsequent functional research and personalised vaccination

Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes

The rapid global distribution of COVID-19 vaccines, with over a billion doses administered, has been unprecedented. However, in comparison to most identified clinical determinants, the implications of individual genetic factors on antibody responses post-COVID-19 vaccination for breakthrough outcomes remain elusive. Here, we conducted a population-based study including 357,806 vaccinated participants with high-resolution HLA genotyping data, and a subset of 175,000 with antibody serology test results. We confirmed prior findings that single nucleotide polymorphisms associated with antibody response are predominantly located in the Major Histocompatibility Complex region, with the expansive HLA-DQB1*06 gene alleles linked to improved antibody responses. However, our results did not support the claim that this mutation alone can significantly reduce COVID-19 risk in the general population. In addition, we discovered and validated six HLA alleles (A*03:01, C*16:01, DQA1*01:02, DQA1*01:01, DRB3*01:01, and DPB1*10:01) that independently influence antibody responses and demonstrated a combined effect across HLA genes on the risk of breakthrough COVID-19 outcomes. Lastly, we estimated that COVID-19 vaccine-induced antibody positivity provides approximately 20% protection against infection and 50% protection against severity. These findings have immediate implications for functional studies on HLA molecules and can inform future personalised vaccination strategies

Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes

The rapid global distribution of COVID-19 vaccines, with over a billion doses administered, has been unprecedented. However, in comparison to most identified clinical determinants, the implications of individual genetic factors on antibody responses post-COVID-19 vaccination for breakthrough outcomes remain elusive. Here, we conducted a population-based study including 357,806 vaccinated participants with high-resolution HLA genotyping data, and a subset of 175,000 with antibody serology test results. We confirmed prior findings that single nucleotide polymorphisms associated with antibody response are predominantly located in the Major Histocompatibility Complex region, with the expansive HLA-DQB1*06 gene alleles linked to improved antibody responses. However, our results did not support the claim that this mutation alone can significantly reduce COVID-19 risk in the general population. In addition, we discovered and validated six HLA alleles (A*03:01, C*16:01, DQA1*01:02, DQA1*01:01, DRB3*01:01, and DPB1*10:01) that independently influence antibody responses and demonstrated a combined effect across HLA genes on the risk of breakthrough COVID-19 outcomes. Lastly, we estimated that COVID-19 vaccine-induced antibody positivity provides approximately 20% protection against infection and 50% protection against severity. These findings have immediate implications for functional studies on HLA molecules and can inform future personalised vaccination strategies.</p

Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes

The rapid global distribution of COVID-19 vaccines, with over a billion doses administered, has been unprecedented. However, in comparison to most identified clinical determinants, the implications of individual genetic factors on antibody responses post-COVID-19 vaccination for breakthrough outcomes remain elusive. Here, we conducted a population-based study including 357,806 vaccinated participants with high-resolution HLA genotyping data, and a subset of 175,000 with antibody serology test results. We confirmed prior findings that single nucleotide polymorphisms associated with antibody response are predominantly located in the Major Histocompatibility Complex region, with the expansive HLA-DQB1*06 gene alleles linked to improved antibody responses. However, our results did not support the claim that this mutation alone can significantly reduce COVID-19 risk in the general population. In addition, we discovered and validated six HLA alleles (A*03:01, C*16:01, DQA1*01:02, DQA1*01:01, DRB3*01:01, and DPB1*10:01) that independently influence antibody responses and demonstrated a combined effect across HLA genes on the risk of breakthrough COVID-19 outcomes. Lastly, we estimated that COVID-19 vaccine-induced antibody positivity provides approximately 20% protection against infection and 50% protection against severity. These findings have immediate implications for functional studies on HLA molecules and can inform future personalised vaccination strategies.</p

Overcoming EGFR T790M and C797S resistance with mutant-selective allosteric inhibitors

EGFR tyrosine kinase inhibitors (TKIs) gefitinib, erlotinib and afatinib are approved treatments for non-small cell lung cancers harboring activating mutations in the EGFR kinase1,2, but resistance arises rapidly, most frequently due to the secondary T790M mutation within the ATP-site of the receptor.3,4 Recently developed mutant-selective irreversible inhibitors are highly active against the T790M mutant5,6, but their efficacy can be compromised by acquired mutation of C797, the cysteine residue with which they form a key covalent bond7. All current EGFR TKIs target the ATP-site of the kinase, highlighting the need for therapeutic agents with alternate mechanisms of action. Here we describe rational discovery of EAI045, an allosteric inhibitor that targets selected drug-resistant EGFR mutants but spares the wild type receptor. A crystal structure shows that the compound binds an allosteric site created by the displacement of the regulatory C-helix in an inactive conformation of the kinase. The compound inhibits L858R/T790M-mutant EGFR with low-nanomolar potency in biochemical assays, but as a single agent is not effective in blocking EGFR-driven proliferation in cells due to differential potency on the two subunits of the dimeric receptor, which interact in an asymmetric manner in the active state8. We observe dramatic synergy of EAI045 with cetuximab, an antibody therapeutic that blocks EGFR dimerization9,10, rendering the kinase uniformly susceptible to the allosteric agent. EAI045 in combination with cetuximab is effective in mouse models of lung cancer driven by L858R/T790M EGFR and by L858R/T790M/C797S EGFR, a mutant that is resistant to all currently available EGFR TKIs. More generally, our findings illustrate the utility of purposefully targeting allosteric sites to obtain mutant-selective inhibitors

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Subtitling of the drama Nirvana in Fire: a multimodal approach

The purpose of this study is to examine subtitle translation from a multi-modal perspective considering not only the spoken mode, but also other important resources such as sound effects, music, moving images, and written text. The study focuses on episodes 1-10 of the Chinese costume drama Nirvana in Fire and aims to contribute to the development of a theoretical framework that fully takes into account the diverse modes involved in subtitle translation. A theoretical framework based on Delabastita's (1990) theory of shifts will be employed, which assumes that meaning in audiovisual texts is conveyed through the use of a combination of signs related to various acoustic and visual codes. Through the case study of this drama, the study has made significant findings in three interrelated areas: (1) the identification of intersemiotic shifts in the subtitle translation of Nirvana in Fire, (2) the examination of the role and interaction of various modes in the translation process, and (3) the investigation of the causes of these intersemiotic shifts. It can be concluded that five intersemiotic shifts were identified in the subtitling of this drama. Moreover, the verbal and non-verbal modes interact dynamically in response to the requirements of semiotic processes. Lastly, the intersemiotic shifts are found to occur for a variety of reasons, including technical, discourse, and cultural constraints. Key words: subtitle translation; Nirvana in Fire; multimodality; intersemiotic shift; constraintsMaster of Arts (Translation and Interpretation