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Certain innovative technologies applied to medical product development require novel evaluation approaches and/or regulations. Horizon scanning for such technologies will help regulators prepare, allowing earlier access to the product for patients and an improved benefit/risk ratio. This study investigates whether citation network analysis and text mining of scientific papers could be a tool for horizon scanning in the field of immunology, which has developed over a long period, and attempts to grasp the latest research trends. As the result of the analysis, the academic landscape of the immunology field was identified by classifying 90,450 papers (obtained from PubMED) containing the keyword "immune* and t lymph*" into 38 clusters. The clustering was indicative of the research landscape of the immunology field. To confirm this, immune checkpoint inhibitors were used as a retrospective test topic of therapeutics with new mechanisms of action. Retrospective clustering around immune checkpoint inhibitors was found, supporting this approach. The analysis of the research trends over the last 3 to 5 years in this field revealed several candidate topics, including ARID1A gene mutation, CD300e, and tissue resident memory T cells, which shows notable progress and should be monitored for future possible product development. Our results have demonstrated the possibility that citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of life science fields such as immunology. [ABSTRACT FROM AUTHOR]

Leukaemia is diagnosed conventionally by observing the peripheral blood and bone marrow smear using a microscope and with the help of advanced laboratory tests. Image processing-based methods, which are simple, fast, and cheap, can be used to detect and classify leukemic cells by processing and analysing images of microscopic smear. The proposed study aims to classify Acute Lymphoblastic Leukaemia (ALL) by Deep Learning (DL) based techniques. The study used Deep Convolutional Neural Networks (DNN s) to classify ALL according to WHO classification scheme without using any image segmentation and feature extraction that involves intense computations. Images from an online image bank of American Society of Haematology (ASH) were used for the classification. A classification accuracy of 94.12% is achieved by the study in isolating the B-cell and T-cell ALL images using a pretrained CNN AlexNet as well as LeukNet , a custom-made deep learning network designed by the proposed work. The study also compared the classification performances using three different training algorithms. The paper detailed the use of DNNs to classify ALL, without using any image segmentation and feature extraction techniques. Classification of ALL into subtypes according to the WHO classification scheme using image processing techniques is not available in literature to the best of the knowledge of the authors. The present study considered the classification of ALL only, and detection of other types of leukemic images can be attempted in future research. • Deep Learning based classification of ALL. • Classification of ALL based on WHO scheme. • ALL is classified into B – cell lymphoblasts and T – cell lymphoblasts. • Use of Convolutional Neural Networks (CNN) for leukaemia classification. • Leukaemia classification without image segmentation and feature extraction. [ABSTRACT FROM AUTHOR]

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Metastasis is the leading cause of death in cancer patients. Eliciting anti-tumor immune responses against lung metastasis is hindered by the immunosuppressive microenvironment. This study explored a biomimetic nanoformulation, comprising a nanovaccine (OP) that delivers tumor antigens and adjuvants spatially and temporally in a virus-like manner, and a pulmonary surfactant-biomimetic liposome with an immunomodulator, JQ1 (PS-JQ1). The findings of this study showed that intratracheal administration of OP+PS-JQ1 activated lung immune cells without concomitant excess inflammation, enhanced tumor antigen cross-presentation, generated a significantly high antigen-specific CD8+ T cell response, and reshaped the immunocellular composition in B16 melanoma tumor-bearing lung. OP+PS-JQ1 nanoformulation exhibited a striking immunotherapeutic efficacy, induced local and systemic tumor suppression, improved survival of mice, initiated immune memory that prevents recurrence of secondary tumors. This stable and nontoxic nanoformulation provides a simple, flexible, and robust strategy for augmenting anti-tumor immunity for metastatic cancer. Egg glue proteins are produced by female insects, which can make the eggs firmly attached to the oviposition sites, not affected by wind and rain. However, genes encoding insect egg glue proteins have not yet been reported, and the molecular mechanism underpinning their adhesion is still unknown. Our study makes a significant contribution to the literature as it identifies the sequence, structure, adhesive property, and mechanism of silkworm egg glue protein. Furthermore, it outlines key insights into the structure-function relationships associated with egg glue proteins. We believe that this paper will be of interest to the readership of your journal as it identifies the first complete sequence of insect egg glue proteins, thereby highlighting their potentials future applications in both the biomedical and technical fields. [Display omitted] [ABSTRACT FROM AUTHOR]

Anaplasma Marginale, a rickettsial gram-negative bacterium, is responsible for causing bovine anaplasmosis which has widely spread among the different parts of the world causing death among cattle. It is mainly spread through the transmission of infected ticks. The manifestation of infected ticks could be controlled to a limited extent. However, subsequently, it is very much necessary for the cattle to develop strong immunity against A. marginale. It could be possible if a subunit vaccine is created against the rickettsial bacteria and introduced into the blood of the cattle for trials. In this paper, we have conducted a study to develop a multi-epitope subunit vaccine against A.marginale by using reverse vaccinology process. Five highly immunogenic outer membrane proteins of A. marginale were selected such as MSP1a, MSP2, Vir B10, OMP1 and OMP11. These proteins bind to the MHC class I molecules of the epithelial cells of mammals and MHC class II molecules of the antigen-presenting cells such as B-cells. The MHC class I molecules present antigens to the cytotoxic t-lymphocytes whereas the MHC class II molecules present antigens to the helper t-lymphocytes thus, initiating a strong immune response among the bovine species. We constructed three vaccine sequences from which two vaccine constructs V2 and V3, were found to be stable with high solubility and negative allergenicity. We also performed molecular docking of the two refined vaccine constructs with Rp-105 (30% resemblance in sequence to TLR4) and TLR-9. The vaccines interacted with the receptors with high binding energy. The best-designed vaccine construct was then reverse transcribed and adapted for the host E.coli K12 strain. The reverse transcribed sequence was later inserted into the pET28a (+) vector for the cloning and expression of the vaccine. The study could be a better initiative for in vitro and in vivo practice in developing an effective vaccine against A. marginale. • The five Outer surface proteins- MSP1a, MSP2, Vir B10, OMP1, and OMP11 were the most antigenic. • The proposed epitopes displayed high antigenic scores, high conservancy and non allergenicity. • Both the modeled vaccine V2 and V3 interacted with the bovine receptors rp-105 (TLR4) and TLR9 with high binding energy. • The designed construct, V3 was adapted for E. coli (K12) for cloning and expression. • Sequence of vaccine constructs showed no similarity with human proteins. [ABSTRACT FROM AUTHOR]

• Oral submucous fibrosis (OSMF) is a fibrotic disease associated with myofibroblasts driven fibrosis. • Fibroblast activating factor (FAP) is expressed on such activated myofibroblasts. • Adoptive transfer of T cells that express a chimeric antigen receptor against FAP is proposed as a targeted immunotherapy for OSMF. • This therapy will reduce the fibrosis and down-regulate the myofibroblasts associated with malignant transformation events. Despite several advancements in understanding the pathogenesis of oral submucous fibrosis (OSMF), there is no definitive therapy for the complete remission of the disease process. This is attributed to the fact that any chronic fibrotic disease targeting myofibroblasts, the primary cells responsible for fibrosis is challenging. The betel quid-associated chemicals, predominantly, arecoline and arecaidine, advance the activation of resident fibroblasts to myofibroblasts in OSMF, resulting in uncontrolled and excessive production of collagen. The myofibroblasts, which are associated with the malignant transformation express fibroblast-activating protein (FAP) on their surface that could be selectively targeted for the treatment of OSMF. In the present paper, we propose that the adoptive transfer of T cells that express a chimeric antigen receptor against fibroblast activation protein (FAP CAR T cell therapy) results in a significant reduction in fibrosis and restoration of function in OSMF. The detailed procedural aspects of this therapy along with experimental designs are also discussed. Since myofibroblasts are involved in the malignant transformation of OSMF, the selective elimination of these cells will reduce the cancer development and ultimately the cancer burden. [ABSTRACT FROM AUTHOR]