TUL Herbarium presents collections from Tula Oblast stored at the Tula State Lev Tolstoy Pedagogical University, Russia, which is an educational and scientific institution that supports various types of scientific activities, including research on biodiversity and nature conservation. The university is a holder of some biological collections, such as herbarium of vascular plants, mosses and fungi collected mainly throughout Tula Oblast and from adjacent regions.https://plant.depo.msu.ru/) and GBIF (https://doi.org/10.15468/ca08cm).The collections of vascular plants  were imaged in December 2019 and January 2020. Databasing and georeferencing of the specimens from the TUL Herbarium was performed by the staff members of the Tula State Lev Tolstoy Pedagogical University and Tula Local History Museum. Digital collections of the TUL Herbarium are fully available in the Moscow Digital Herbarium ( TUL is an acronym of the Herbarium of the Tula State Lev Tolstoy Pedagogical University (TSPU), Russia, which is the main custodian of the herbarium collections from Tula Oblast and one of the oldest in Tula institutions with the natural history collections. The acronym was assigned to the Herbarium in 2019 .Geography & Nature2. It borders Moscow Oblast in the north, Ryazan Oblast in the east, Lipetsk Oblast in the southeast, Oryol Oblast in the southwest and Kaluga Oblast in the west. The climate is moderate continental, with precipitation declining from 575 mm in the northwest to 470 mm in the southeast, average July temperature is about +19...+20°C and average January temperature is −10...−9°C.Tula Oblast is located in the Central Federal District of Russia, covering an area of 25,700 kmVegetation of Tula Oblast includes zones of broadleaved forests in the central part, forest-steppe in the south and east and a narrow strip of the ecotone subtaiga zone in the west and north. The combination of three vegetation zones contributes to the significant diversity of the flora, which includes both northern and southern elements.Historical backgroundTula State Lev Tolstoy Pedagogical University was founded on 19 September 1938 as a federal institution of higher education with the name Tula State Pedagogical Institute. On 18 July 1958, it was named after Lev Tolstoy. On 24 December 1994, it was awarded the status of State Pedagogical University.The collecting of plant specimens began in the 1960s, when the Faculty of Chemistry and Biology was launched at the Tula State Pedagogical Institute (TSPI). The first collections were made by the students during their summer field practices, as well as from individual assignments on the Botany course. The first herbarium specimens have non-standard appearance and size, since the paper for the specimens was chosen by students at random and it was often cut out manually and then covered with tracing paper attached on the left edge to preserve dry plants. There are ca. 100 those non-standard sheets from the 1960s.In the 1970s, institute students were the main contributors to the herbarium collections. The specimens acquired a bit more standardised appearance and constant size of sheets 25 x 34 cm, but still differed from the 28 x 42 cm size accepted in the major Russian herbaria. The majority of specimens were supplied with a standard pre-printed label, which included the heading of Tula State Lev Tolstoy Pedagogical Institute in Russian  consisting of 2,104 specimens was gifted by his relatives to the Herbarium. Alyushin was a school teacher and skilled naturalist, who especially loved Botany. In 1941–1945, he also worked at the Tula Local History Museum  Within Alyushin's collections stored in the TUL Herbarium, there are four specimens of Konstantin Semenovich Dubensky. Dubensky was a teacher of Natural Science at the Tula Real School and Women's Gymnasium in the 1900s–1920s Fig. . He condProbably, at the same time, the Herbarium received 13 specimens of plants collected by the botanist V.A. Arsenyev in 1931. Unfortunately, the exact information about their origin is unknown.The period 1987–1999 became the most productive time for the accumulation of plant specimens in the TUL Herbarium . Several scientific research activities, based on intensive collection expeditions across Tula Oblast, were completed at that time, like "Flora of Tula Oblast" , "AdventFungi"  and the preparation of the "Red Data Book: Specially Protected Natural Areas of Tula Oblast"  and "RedFungi" . TherefoFungi" .After 2010, the Herbarium continued to be filled mainly by the collections of students, but their collections were transferred to the educational collection, which is used during lab classes and is not part of the Herbarium. However, in 2018–2019, the TUL Herbarium was replenished with recently-collected specimens due to the preparation of the second edition of the regional "Red Data Book" and monitoring of the protected natural areas . It shou2) in the building of the Faculty of Natural Sciences of Tula State Lev Tolstoy Pedagogical University located on 125, Lenina Prospect, in Tula. There is no special regular staff in the TUL Herbarium.Today, the Herbarium occupies one room  ― general management and supervision of the project, preparation of collections for digitisation, databasing of specimens, georeferencing;Alexey Seregin (Lomonosov Moscow State University) ― project design, general consulting, management and supervision of imaging and other digitisation activities, online publication of the collections, identification of specimens;Irina Sheremetyeva  ― identification of specimens and verification of earlier definitions, collection of fresh specimens;Lyudmila Khoroon  ― identification and verification of specimens, preparation of collections for digitisation;Alexander Lakomov  ― georeferencing;Dina Zatsarinnaya  ― georeferencing, preparation for digitisation of the collections of Tula Local History Museum (in process);Elena Volkova (Tula State University) ― preparation for digitisation of the collections of Tula State University and State Museum Reserve "Kulikovo field" (in process);Oleg Platko (Lomonosov Moscow State University) ― online publication of the collections, data audit, database administration.Tula OblastProject Background and Aims. Biodiversity conservation is an urgent task for mankind. This environmental challenge is particularly acute in the Tula Oblast characterised by a highly-developed industry, a high proportion of agricultural land, as well as by a low proportion of protected natural areas. The project aimed at the inventory of vascular plant diversity at a new level. For the first time in Tula Oblast, a text database and GIS-module with geolocations have been complemented by the Library of high quality images of herbarium collections. The goal of the project is to assess the actual diversity and spatial structure of the Tula flora by combining various data sources on a single platform, visualising all the available information by digitising data and creating a multifunctional electronic resource with an open access. The main scientific idea is to make the Tula flora visible to the global community.Project steps.To combine the data on five herbarium collections made in Tula Oblast , Tula State University, Tula Local History Museum, State Museum Reserve "Kulikovo field" and Moscow State University (MW));to image herbarium specimens;to supplement the materials with photographs of plants in the wild;to outwork a database of label transcriptions;to georeference every specimen;to create a regional information online resource "Digital Herbarium of Tula Oblast" .https://plant.depo.msu.ru/), including 9,000 specimens from the TUL Herbarium. We also made transcriptions of 12,991 labels and georeferencing of 12,909 specimens. Finally, the dataset of the TUL Herbarium has been published in GBIF and the dataset of MW has been published separately (The project is scheduled to run for three years and includes laboratory work with collections and field studies of the Tula Oblast flora. The first year of the project (from May of 2019 to May of 2020) was devoted to the accumulation and structuring of electronic data on the regional diversity of vascular plants. We performed processing  and digitisation of plant collections from Tula Oblast, preserved in Tula State Lev Tolstoy Pedagogical University (TUL) and Lomonosov Moscow State University (MW). As a result, 13,931 images made at 300 dpi were published via the Moscow Digital Herbarium ; habitat; collection date; collector's name; identifier's name; re-identification date; re-identifier's name; notes). The main Table also includes some technical fields for the data processing — sign ; number of the record ; the herbarium number (unique number assigned to a specimen); date of recording; recording person.Quality control. Сlarification and correction of the entered information with the help of specific queries selecting data on a certain collector, date, location etc. Some important information has been found in literature and some unpublished sources of botanists who worked in Tula Oblast. This allowed us to restore some information gaps in the available data and include them in the database.Labelling. Each specimen has two labels, i.e. printed label retrieved from the database and the original one. New labels with the unique specimen number and TUL acronym have been obtained from the database by programming external links between MS Access and MS Word. In addition to the new ones, the original labels made by collectors have been placed on the Herbarium sheets to clarify the historical component of the Herbarium.TUL006192). The barcodes were pre-ordered and printed typographically.Barcoding. A barcode contains the name of the TUL Herbarium in Latin , TUL acronym and a six-digit number (like Creation a library of images (scanning and processing)https://elar.ru/) on planetary scanners of A2 format with a resolution of 300 dpi in two steps in December 2019 and January 2020. The contribution from the commercial partner included:Imaging was carried out by the commercial partner  with a scale bar;converting TIFF files to JPEG copies;renaming of the files against barcodes;structuring of graphic images in accordance with their physical storage within the herbarium ;manual quality control of the final images;recording of images on storage media (HDD).Electronic data captureEach image was supplied with minimum metadata, for example, ID against barcode, species name from the folder and area code (Tula Oblast). The records from the MS Access database with full label transcriptions were cross-linked using barcode IDs and integrated into the dataset.Georeferencing specimen dataYandex.Maps, Google Maps etc.). We used the old scanned maps (of the early 20th century) for georeferencing of some historical collections, since the names of some geographic locations have been changed or disappeared over time.Manual georeferencing is carried out using standard e-cartographic libraries , with several lines of the code being written in JAVA . This coPublication of digitised collectionsDigitised collections of the TUL Herbarium were published in the Moscow Digital Herbarium. This means that images and metadata are available on three platforms .https://plant.depo.msu.ru/) is actually an operational version with a number of search tools like label search, geosearch, search on the taxonomic tree, search by Latin and vernacular names etc. Data administrators of Lomonosov Moscow State University are managing the content and editing the data. IT staff are incorporating new large datasets like labels, georeferences, taxonomic treatments etc. The content of the portal is hidden from search robots, but users can download XLSX-files with general metadata. One can see basic statistics of the Moscow Digital Herbarium right on the homepage.Moscow Digital Herbarium (https://plant.depo.msu.ru/open/). – This portal is optimised for computers, tablets and mobile platforms. The content is updated once a day. The open version allows search robots to access the text and JPG images, as well as quick simple searches through all fields of the database. The content is accessible 24/7 even if we are updating the system or content. One can see search results in the form of small icons and search criteria could be saved as a unique URL.Open version (https://www.gbif.org/). – Our data are fully available in GBIF without any limitations ;intensive studies of some areas during summer field practices of students.As a result, some districts of Tula Oblast are well-studied and represented by numerous specimens, whereas other districts are poorly sampled. In Table The most sampled area is Shchekinsky District , where Leo Tolstoy Museum-Estate "Yasnaya Polyana" is situated. This institution is involved with nature conservation and biodiversity research and periodically supports studies of various groups of organisms. For example, some student master's theses  were performed due to the on-purpose contracts between the Museum-Estate and TSPI. From the other side, the Museum-Estate is situated not far from the University and is a convenenient place for field practices and botanical excursions.The City of Tula  and adjacent Leninsky District (715) are holding the second and the third positions in the ranking. These administrative units are the places of regular excursions and individual assignments, as well as scientific research of the alien flora.They are superseded by Suvorovsky, Yasnogorsky, Efremovsky, Odoevsky, Kimovsky, and Aleksinsky districts, where local biodiversity hotspots , as well as some protected areas, are situated. Other districts are either situated on the fringes of the Tula Oblast or have vegetation greatly affected by human activity.52.9 and 54.9 Latitude; 35.9 and 39 Longitude.Most of the TUL Herbarium collections are represented by vascular plants from Tula Oblast, of which 95% are currently digitised. The focus of the Herbarium is on native and alien flora, whereas cultivated plants of Tula Oblast are almost missing. The brief taxonomic outline of the collections is based on GBIF dataset with 9,000 specimens.https://www.catalogueoflife.org/).For many years, we followed the standard "Flora of the middle zone of the European part of Russia" by P.F. Mayevsky  for taxoGBIF webpage of our dataset. There are no type materials in the TUL Herbarium.The digitised TUL collections of vascular plants contain 9,000 specimens which belong to 1,131 species and nothospecies (hybrids), 514 genera, 98 families, 40 orders and five classes. The correlation of represented orders is shown in Fig. The most sampled families, genera and species of the TUL Herbarium are given in Table TUL Herbarium documents hundreds of localities of rare and protected species of the region. Its collections were intensively used during the preparation of the "Red Data Book of Tula Oblast". In the current first edition of the Book , there aAt present, 29 of 158 legally-protected species of Tula Oblast are not represented in the TUL Herbarium. Most of them are kept in the Moscow University Herbarium , as wellPLEASE FILL IN TRAIT INFORMATION HEREFrom 20 June 1919 to 26 October 2019.Gentianellaamarella (L.) Börner collected by K.S. Dubensky on 20 June 1919 and the latter is a specimen of Solidagocanadensis L. collected by I.S. Sheremetyeva on 26 October 2019 in line with the digitisation project.A hundred years is the time interval between the oldest and the freshest specimens of the TUL Herbarium. The first one is a specimen of The temporal distribution of collected specimens over decades is given in Fig. A brief description of peaks and other significant dates is given below. Total figures are pointed as estimates because some specimens do not have an exact date, but very likely belong to this period.1919–1928: Four specimens collected by K.S. Dubensky in 1919.1929–1938: 13 specimens collected by V.A. Arsenyev in 1931.1939–1948: Three specimens collected by A.I. Alyushin in 1939 (his first collections).1949–1958: no collections.1959–1968: 197 specimens, i.e. the first collections made in Tula State Lev Tolstoy Pedagogical Institute; also, five specimens collected by A.I. Alyushin.1969–1978: 1,728 specimens collected by A.I. Alyushin and three by I.S. Sheremetyeva. Other specimens (ca. 300) are ordinary collections of students made during their summer field practices.1979–1988: 2,816 specimens, incl. 710 collected by I.S. Sheremetyeva, 365 by A.I. Alyushin, 178 by E.G. Balashova and T.Yu. Svetasheva, 167 by L.V. Khoroon, 99 by E. Zenina, 80 by M. Andreeva, 71 by A.V. Shcherbakov and I.S. Sheremetyeva, 50 by E. Azarova and 43 by I. Blokhin. An interesting collection with 15 specimens was made by the famous Moscow Botanist V.E. Skvortsov together with I.S. Sheremetyeva in the Efremovsky District in 1988.1989–1998: 2,775 specimens, incl. 777 collected by I.S. Sheremetyeva, 733 by L.V. Khoroon, 452 by E.G. Balashova and T.Yu. Svetasheva, 215 by A.V. Shcherbakov, I.S. Sheremetyeva and P.B. Sheremetyev, 130 by I. Dorokhina and 112 by E. Zenina. A small interesting collection with 32 specimens was made by I.S. Sheremetyeva together with the Moscow Botanists V.S. Novikov, N.B. Oktyabreva and K.V. Kiseleva in botanically well-known area of "Lupishki bogs" in 1990–1992. Other specimens are ordinary collections of students made during their summer field practices.1999–2008: 546 specimens, incl. 271 collected by I.S. Sheremetyeva, L.V. Khoroon, T.Yu. Svetasheva and P.B. Sheremetyev made during research of protected areas in Tula Oblast. The results were published in the special edition of the "Red Data Book" devoted to the protected nature areas of Tula Oblast  4.0 License.https://doi.org/10.15468/ca08cm)TUL Herbarium: Tula Oblast collections of vascular plants . The imaging was supported by the research project 19-44-710002 funded by RFBR and Tula Oblast Government. Databasing and georeferencing of the specimens from the TUL Herbarium were performed by staff members of the Tula State Lev Tolstoy Pedagogical University and Tula Local History Museum. The labels of all digitised specimens were fully databased and ca. 80% of specimens were georeferenced by May 2020. All data were published in the Moscow Digital Herbarium in 2019–2020 (https://plant.depo.msu.ru/) and are fully available in GBIF  imaged in December 2019 – January 2020 by the commercial partner : TUL Herbarium: Tula Oblast collections of vascular plants. v 1.31. Tula State Lev Tolstoy Pedagogical University. Dataset/Occurrence. https://doi.org/10.15468/ca08cm accessed via GBIF.org on 2020-09-28.Svetasheva T, Seregin A (2020). TUL Herbarium: Tula Oblast collections of vascular plants. Version 1.34. Tula State Lev Tolstoy Pedagogical University. Occurrence dataset


Anti-tumor necrosis factor-alpha (anti-TNF-α) agents have been suggested as being favorable  and a poThe experience of IBD patients infected with COVID-19 has been reported through the SECURE-IBD database. As of July 13, 2020, 15% of the patients on anti-TNF therapy required hospitalization, with 2% requiring intensive care and 1% succumbing to the disease . PatientFurthermore, important differences exist between the study populations of IBD trials and COVID-19 patients. IBD trials typically exclude patients with severe uncontrolled infections and those with heart failure . Severe The cumulative evidence in the literature has also been inconsistent regarding the safety profile for infectious adverse events with anti-TNF-α therapies in IBD. When compared to placebo, meta-analysis has found that UC patients treated with anti-TNF agents had increased long-term risks of opportunistic and of serious infections requiring intravenous antibiotics or hospitalization, or causing death . A higheThe indication of anti-TNF-α treatment in the present pandemic would target pulmonary inflammation and mortality. The previous literature concerning both acute lung injury and acute respiratory distress syndrome feature higher local and systemic levels of TNF-α and have been associated with worse outcomes . SimilarIt is nonetheless worth noting that emerging data on the use of anti-TNF agents in patients with COVID-19 included the description of a case where infliximab was initiated in a 54-year-old female patient for a severe episode of ulcerative colitis [With no experience with this novel virus, TNF blockade, although mechanistically promising, may harbor serious risks in fragile older patients. We endorse the hypothesis stipulating that this therapy might prevent severe complications of systemic inflammation in COVID-19 infections, but further investigation into the evolution of COVID-19 infections in IBD patients already treated with anti-TNF agents could provide valuable insight into the benefits of suppressing the TNF-α cascade. Caution should, however, be used in projecting any outcomes observed in patients on maintenance therapy to initiating antibody treatment in a naïve but COVID-19 afflicted patients.


We produced chimeric murine polyomavirus VLPs and capsomeres each incorporating defined CD8+ T cell, CD4+ T cell or B cell repeat epitopes derived from Plasmodium yoelii CSP. VLPs and capsomeres were evaluated using both homologous or heterologous DNA prime/boost immunization regimens for T cell and antibody immunogenicity. Chimeric VLP and capsomere vaccine platforms induced robust CD8+ T cell responses at similar levels which was enhanced by a heterologous DNA prime. The capsomere platform was, however, more efficient at inducing CD4+ T cell responses and less efficient at inducing antigen-specific antibody responses. Our data suggest that capsomeres, which have significant manufacturing advantages over VLPs, should be considered for diseases where a T cell response is the desired outcome.Despite extensive research, the development of an effective malaria vaccine remains elusive. The induction of robust and sustained T cell and antibody response by vaccination is an urgent unmet need. Chimeric virus-like particles (VLPs) are a promising vaccine platform. VLPs are composed of multiple subunit capsomeres which can be rapidly produced in a cost-effective manner, but the ability of capsomeres to induce antigen-specific cellular immune responses has not been thoroughly investigated. Accordingly, we have compared chimeric VLPs and their sub-unit capsomeres for capacity to induce CD8 Plasmodium spp. parasite will likely require an effective vaccine  B cell repeats and some CD4+ and CD8+ T cell epitopes fused with recombinant hepatitis B surface antigen (RTS) and co-expressed with free hepatitis B surface antigen (S) , is a virus-like particle (VLP) comprising multiple copies of the igen (S) , co-admiigen (S) , 6. SignIn vitro studies have shown that chimeric hamster polyomavirus and SV40 VLPs incorporating T cell epitopes from mucin 1 and influenza, respectively, can induce activation of epitope-specific CD8+ T cells  induced robust CD8+ T cell responses as well as high antibody titres, but poor CD4+ T cell responses  adjuvant with VLPs, and of including a heterologous DNA prime-boost regimen.Herein, we extended those studies to comprehensively compare chimeric murine polyomavirus VLP and capsomere constructs incorporating defined 80-288)+  and CD4((59-79)+  from PyCPyCSP E. coli expression then synthesized by GeneWorks .For genomic insertion of epitopes into VLPs and capsomeres, complementary oligonucleotides for the PyCSP CD8280−288 (SYVPSAEQI), CD459−79 (YNRNIVNRLLGDALNGKPEEK) and B cell (QGPGAPQGPGAP) peptides were purchased from Mimotopes Pty Ltd .For peptide stimulation in T cell assays- PyCSP (pVR2516) or empty vector without insert  were commercially purchased from PureSyn Inc. .For plasmid DNA immunizations, plasmid DNA encoding full-length M34958) was obtained from the Protein Expression Facility . For the VLP platform, the VP1 sequence was modified by PEF by inserting an AfeI restriction enzyme site flanked with Glycine4-Serine linker sequences at position 293; this was designated pGEX-VP1-S4-G4S  with the murine polyomavirus VP1 sequence . The GST-tagged VP1 proteins were expressed by bacteria culture in Terrific Broth and expression induced using 0.2 mM IPTG and purified as previously described  aged 6–7 weeks  were immunized three times at 3-week intervals by (i) subcutaneous injection (s.c.) of pooled VLPs or pooled capsomeres  on the lower back near the base of the tail; (ii) intramuscular injection (i.m.) of plasmid DNA (100 μg) into the anterior tibialis; or (iii) s.c. injection of pooled peptides  on the lower back near the base of the tail. Capsomeres and peptides were co-administered with 50 μg of high molecular weight poly(I:C) adjuvant ; and VLPs were administered with or without this adjuvant, in parallel groups. Mice were immunized in both homologous and heterologous prime/boost regimens involving two priming doses of PyCSP plasmid DNA followed by a booster dose of capsomere, VLP or peptide. Negative control groups included PBS, wild-type capsomere with poly(I:C), or wild-type VLP with poly(I:C). The positive control group received three doses of PyCSP plasmid DNA. All murine experiments were approved by the QIMR Berghofer MRI Animal Ethics Committee and were conducted in accordance with the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes (2004).Female BALB/c mice  mouse B cell lymphoma A20 cells (ATCC TIB-208) which had been either DNA-transfected, peptide-stimulated, or untreated. Transfections with plasmid DNA encoding PyCSP (pVR2516) or empty vector (pVR1020) was achieved using the AMAXA Nucleofector system  using Kit V and program C-25 with 5 × 106 A20 cells per cuvette, following the manufacturer's protocol. Peptide stimulation with PyCSP CD8+(280−288) and CD4+(59−79) T cell epitopes, or these peptides combined with the B cell repeat epitope peptide. Cells were incubated in KD-MEM media comprised of Dulbecco's Modified Eagle's Medium  supplemented with folic acid (136 nM), L-asparagine (32 mM), L-arginine (67 mM), sodium bicarbonate (24 mM), HEPES (10 mM), β-2-mercaptoethanol (5 nM), L-glutamine (1.5 mM), penicillin (100 Units/L), streptomycin (100 mg/L), and 10% fetal calf serum.Ten days after the final immunization, spleens were harvested and single cell suspensions generated by mechanical disruption and red blood cell lysis. For ELISpot, cytometric bead array (CBA) and intracellular cytokine staining (ICS) assays, 5 × 102 for 40 h. Wells were washed and stained with 2 μg/ml biotinylated anti-mouse IFN-γ antibodies , followed by 1 μg/ml streptavidin-HRP . The assay was developed using AEC substrate . Spots were counted using the AID ELISpot reader system .IFN-γ ELISpot assays were conducted as previously described , 32. Bri2 for 72 h. Culture supernatant was collected and stored at −80°C prior to assay. Secreted IFN-γ, TNF, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12p70, and IL-13 cytokines were analyzed using the mouse cytometric bead array flex kit  following the manufacturer's protocol. Samples were acquired using a FACSArray instrument  and data analyzed using the CBA array software .Splenocyte/A20 cultures were incubated at in 96-well U-bottom plates in 200 μl of complete media at 37°C and 5% CO2. Cells were stained with PE-Cy7 labeled anti-CD8+ (53-6.7) and BV510 labeled anti-CD4+ (RM4.5) antibodies before being fixed with 4% paraformaldehyde at room temperature (RT) for 15 min. Cells were then washed with permwash and stained with APC-labeled anti-IFN-γ (XMG1.2), PE-labeled anti-IL-2 (JES6-5H4) and FITC-labeled anti-TNF-α (MP6-XT22) antibodies diluted in Cytofix/Cytoperm . All antibodies were purchased from Biolegend with the exception of anti-TNF-α which was purchased from eBioscience. Flow cytometric analysis was performed on a Fortessa 4 . Post-acquisition data analysis was performed using FlowJo software version 10 .Splenocyte/A20 cultures in 200 μl of complete media supplemented with 0.1% Golgi Plug  in 96-well U-bottom plates were incubated for 6 h at 37°C and 5% COPyCSP B cell repeat peptide linked to a polystyrene binding tag (4 spacer (PyCSP recombinant protein (1 μg/ml) diluted in carbonate buffer. Wells were subsequently blocked with PBS containing 2% BSA. Triplicate wells of 2-fold serially diluted sera in PBS-BSA 0.1% were used for endpoint titrations, and sera diluted 1:400 for isotype screening. For IgG responses, wells were incubated with biotinylated donkey α-mouse IgG antibodies  diluted 1:20,000 in PBS-BSA 0.1%, followed by incubation with streptavidin-HRP  diluted 1:1,000 in PBS-BSA 0.1 and 0.2% Tween20. For IgG isotype responses, wells were incubated with HRP-conjugated goat anti-mouse IgG1, rabbit anti-mouse IgG2a, goat anti-mouse IgG2b, or goat anti-mouse IgG3 antibodies  all diluted 1:3,000 in PBS-BSA 0.1 and 0.2% Tween20. Wells were developed with tetramethylbenzidine (TMB) and stopped using TMB stop reagent . Absorbance was measured at 450 nm using a VersaMax microplate reader . Positivity was defined as OD450 value >3× standard deviations above the mean blank (no serum) values.Sera was collected from mice 14 days after immunizations 1 and 2, and 5 days after the final immunization. Nunc Maxisorp plates  were coated overnight with either ding tag  with a g4 spacer   were centrifuged at 10,000 × g for 5 min then resuspended to 105 sporozoites per ml of Medium 199 . Then, 10 μl was added to wells drawn on a microscope slide using a Barrier Pap pen and air dried at RT before long-term storage at −80°C. Prior to use, slides were thawed to RT in a desiccator cabinet. Pooled sera from each immunization group collected 5 days after the final immunization was diluted 1:400 in PBS with 2% BSA, then 10 μl was added to each well and incubated at 37°C in a humid box. Wells were gently washed with PBS then stained with 10 μl of FITC conjugated anti-mouse IgG antibodies , diluted 1:30 in filtered PBS containing 0.005% Evans blue. Slides were incubated for 30 min in a humid chamber and then washed gently with PBS. A cover slide was mounted over PBS with 10% glycerol and slides viewed on an EVOS fluorescence microscope  at x400 magnification.Sporozoite-specific antibodies were assayed by Indirect fluorescence antibody test (IFAT) using a protocol modified slightly from that previously described . Briefly*p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.Statistical analysis was performed using GraphPad Prism version 6.0 . Logarithmic transformed data of groups were compared by one-way analysis of variance (ANOVA) and Bonferroni's multiple comparison test. Statistical significance is reported as PyCSP peptide epitopes into the murine polyomavirus VP1 protein for generation of VLPs ] with minimal amounts of aggregation . The peptide immunizations also induced a robust IFN-γ responses which was dominated by the CD4 peptide stimulation.Significant antigen-specific IFN-γ responses were induced by homologous immunization with both capsomeres and VLP, when compared to their respective negative control, as detected after peptides . The amop < 0.001), VLPs and VLPs with poly(I:C) (p < 0.0001) when stimulated with the whole PyCSP antigen transfected into A20 cells, and capsomeres (p < 0.01), VLPs and VLPs with poly(I:C) (p < 0.0001) when stimulated in vitro with pooled peptides. This increase in IFN-γ responses was driven by the DNA prime as evidenced by comparison of the responses to those of DNA only immunized mice. Consistent with results from the homologous immunization regimens, IFN-γ responses induced by capsomeres and VLPs in the heterologous DNA prime/boost regimen were not significantly different.Heterologous prime/boost immunization resulted in an ~5-fold increase in IFN-γ responses over the homologous regimens for both capsomeres and VLPs . When coin vitro, we also stimulated with either PyCSP CD8+ or CD4+ T cell peptides separately. That study showed that both the capsomere and VLP induced IFN-γ responses were predominantly associated with the CD8+ T cell peptide, with no significant difference between the capsomere and VLP immunized groups  (p < 0.0001) when stimulated with the CD4+ T cell peptide  showing beneficial effects of the repeat peptide doses.Although capsomere and VLP platforms induced a very similar profile of CD8 peptide . This tr peptide  and in td by ICS , althoug epitope , 2. Within vitro immune assays using cytometric bead array (CBA)  . The IFNay (CBA) . IFN-γ r+ or CD4+ peptide, but significant TNF responses were induced by VLP immunization and this was further increased by poly(I:C) adjuvant; these responses were preferentially directed against the CD8+ T cell peptide but were also significant for the CD4+ T cell peptide epitopes  as assessed by ICS (data not shown) and CBA . The IL-PyCSP B cell repeat peptide and PyCSP recombinant protein were performed using individual and pooled mouse sera collected 14 days after doses 1 and 2; and 5 days after final immunization (PyCSP B cell repeat IgG titres which were increased with the co-administration of poly(I:C) adjuvant . There was a trend to increased antibody response with VLP administered with adjuvant compared to the non-adjuvanted VLPs but this was not statistically significant. However, the adjuvant effect was significant when VLPs were administered with a DNA prime (p < 0.05) indicating that with only a single VLP dose, the inclusion of adjuvant is beneficial and this benefit becomes less important after multiple doses (p < 0.01).ELISA assays against the PST-nization . Consistadjuvant . Capsomele doses . A primiPyCSP B cell peptide total IgG responses using pooled sera collected after each immunization to determine the effect of the number of immunizations within each regimen . VLP immunizations induced an IgG3 response which was absent in the capsomere-immunized mice. Compared to other immunization regimens, the homologous VLP immunization groups had higher levels of IgG3 but similar levels of IgG1 indicating that the second and third doses caused a shift in isotype responses toward an IgG3 bias. IgG2a responses were increased with the inclusion of poly(I:C) with the VLP but this was not present in the capsomere with poly(I:C) immunized mice, indicating the difference was platform specific. Moderate IgG2a responses were also present in the DNA group and the heterologous DNA prime groups.Antibody isotypes contributing to the total IgG response reported above were also delineated, using pooled sera collected after the final immunization . ImmunizPyCSP protein, pooled sera collected after the final immunization was assayed using ELISA against recombinant protein  collected after the final immunization (3 which was absent in chimeric capsomeres. The inclusion of poly(I:C) resulted in increased levels of IgG3 responses, and the homologous three-dose regimen significantly increased levels as compared to the heterologous prime/boost regimen (p < 0.001).To confirm that the IgGnization . Each VLP. yoelii 17XNL sporozoites, as evidenced by surface staining in the homologous and heterologous immunization regimens  adjuvant were able to recognize regimens .Plasmodium sp. CSP is the leading antigen target for sub-unit vaccines against malaria, and is the antigenic component of the virus-like particle RTS,S which is the most advanced human vaccine candidate against Plasmodium falciparum malaria. It was, therefore, a logical choice for evaluation of novel vaccine delivery platforms. We know that liver-stage protection from sporozoite challenge can be achieved by either CD8+ T cells  was selected for study because of its the ability to induce functional CD4+ T cell populations of either TH1 or TH2 subsets associated with T cell proliferation responses or help for antibody responses (+ T cell helper effect on antibody titres by co-administering a chimeric CD4 VLP (in a VLP pool) with B cell VLPs (+ T cell helper responses as both capsomeres and VLPs were only administered in pools. We found that immunization with pooled peptides adjuvanted with poly(I:C) induced the most robust responses, however this is likely related to the dose of the target peptide epitope, as the positive control peptide pools incorporated 30 μg of the CD4 peptide whereas the amount of epitope presented in the chimeric capsomeres and VLPs was ~1.77 and 0.52 μg, respectively, per dose. This may also explain why the capsomeres were more effective than VLPs at inducing responses against this peptide epitope as one of the benefits of capsomeres over VLPs as a vaccine platform is the ability to present a higher antigen load, and in our study capsomeres achieved a 3-fold higher antigen dose than VLPs. It should be noted that the antigen dose difference was the same for the CD8+ T cell peptide epitope and we did not see similar increased immune responses against that antigen target. The ability of capsomeres to induce CD4+ T cell responses is an important advantage for vaccinology since vaccine platforms that preferentially induce CD8+ T cell responses rather than antibody responses are often poor inducers of CD4+ T cell responses , establishing that the CD8+ or CD4+ T cell chimeric VLPs were not responsible for the subclass, as seen in other platforms  protected BALB/c mice from a P. yoelii 17XNL sporozoite challenge (An interesting observation from our study is that the IgGdetected . It appelatforms . It is cathogens , 54 inclarasites , 40, andhallenge .+ T cell response and its poor ability to prime an antibody response (There are many examples of enhanced immunogenicity and protection with DNA prime-boost regimens using various antigen delivery systems encoding the same antigen or epitope , 55–58 iresponse .+ T cell responses but the capsomeres were significantly better at inducing epitope-specific CD4+ T cell responses than VLPs. This enhanced CD4+ T cell response may be of particular importance in the control of chronic viral infections (+ T cells during prolonged viral infections (+ T cell help may be required for optimal CD8+ T cell activity (+ T cell memory (+ T cell vaccine induced response is required. On the other hand, since capsomeres have a limited capacity to induce antibody responses, VLPs would be the preferred platform for antibody mediated immunity. Given that most licensed vaccines target the induction of antibody response and the increasing interest at identifying vaccine platforms capable of inducing robust T cell responses, our data have important implications for the development of vaccines against those pathogens that have thus far proved challenging.Chimeric capsomeres are a promising vaccine platform which build on the established vaccine potential of VLPs, but are easier and cheaper to produce than VLPs , and canfections , the maifections  where CDactivity  or for Cl memory , or indeThe datasets generated for this study can be obtained from the corresponding author upon reasonable request.The animal study was reviewed and approved by QIMR Berghofer Medical Research Institute Animal Ethics Committee.DP, SA, DD, and AM contributed conception and design of the study. DP, NW, TR-H, and AM contributed to construction of virus-like particles and capsomeres. DP, SA, and PG conducted the mouse experiments. DP performed the statistical analysis. DP and DD wrote the manuscript. All authors contributed to manuscript revision, have read, and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This study aimed to assess plasma fibroblast growth factor 23 (FGF23) in patients with heart failure with preserved ejection fraction (HFpEF) and its relation to inflammation, renal function, clinical and imaging characteristics, exercise capacity, and prognosis.n = 130; controls n = 42, age 73 ± 9, female 50%) who underwent plasma biomarker sampling, echocardiography, cardiac magnetic resonance imaging, and 6 min walk testing (6MWT). The primary endpoint was the composite of all‐cause death or HF hospitalization. FGF23 was higher in HFpEF compared with controls . In HFpEF, FGF23 correlated with greater symptom burden (New York Heart Association class: r = 0.308), poorer exercise capacity (6MWT distance: r = −0.345), and plasma biomarkers reflecting inflammation , bone metabolism (osteoprotegerin: r = 0.446), renal dysfunction , and echocardiographic E/e′ (r = 0.298); P < 0.05. Following multivariable linear regression modelling, FGF23 remained independently associated with shorter 6MWT distance (P = 0.012) in addition to age, body mass index, and lower haemoglobin. During follow‐up (median 1428 days), there were 61 composite events  in patients with HFpEF. In multivariable Cox regression analysis, FGF23 , B‐type natriuretic peptide , and prior HF hospitalization  were independent predictors of the composite endpoint.We performed a prospective, observational study of 172 age‐matched and sex‐matched subjects (HFpEF Plasma FGF23 is higher in HFpEF compared with age‐matched and sex‐matched controls and is strongly associated with exercise incapacity and prognosis. FGF23 correlates with plasma markers of inflammation and renal impairment. Heart failure (HF) is an increasingly prevalent and important health care issue. Of incident cases of HF, approximately half are HF with preserved ejection fraction (EF) (HFpEF), a proportion which has increased over recent years and which is likely to be the predominant phenotype in the near future.HFpEF includes a heterogeneous patient population, which have in common a typical phenotype, encompassing preserved left ventricular (LV) function and abnormal cardiac structure in the form of LV hypertrophy (LVH) and atrial dilatation, with elevated circulating natriuretic peptides. It is increasingly recognized that a multitude of co‐morbidities, singly or more often in combination, may contribute to the development of the HFpEF syndromeCirculating FGF23 levels have been associated with risk of incident cases of HFpEF in community‐based populationsThe aims of our study were to identify whether FGF23 was associated with plasma markers of inflammation, renal dysfunction, clinical metrics of disease severity including exercise capacity, imaging characteristics, and prognosis in patients with HFpEF undergoing extensive tissue characterization with cardiac magnetic resonance (CMR).2, and standard contraindications to CMR imaging.As reported previously,HFpEF patients were compared with asymptomatic age‐matched and sex‐matched controls without known cardiac disease. The control population did include individuals with a history of hypertension (50%), because this is highly prevalent in the general population as well as in HFpEF, and the aim for our study was to identify factors differentiating between patients with and without HFpEF.Declaration of Helsinki. The research protocol was approved by the UK National Research Ethics Service (reference: 12/EM/0222). Written informed consent was obtained from all subjects prior to participation. The study was registered on Clinicaltrials.gov (NCT03050593).During a single study visit, all subjects underwent clinical assessment of New York Heart Association (NYHA) status, blood sampling, TTE, CMR, standardized 6 min walking test (6MWT),At recruitment, blood sampling was undertaken for B‐type natriuretic peptide , haematocrit, haemoglobin, and renal function and assayed in our hospital laboratory.Blinded single batch testing of FGF23, osteoprotegerin (OPG), highly sensitive C‐reactive protein (hs‐CRP), and myeloperoxidase (MPO) was undertaken from residual supernatant plasma stored at −80°C in cryotubes using a Luminex® bead‐based multiplex assay,Echocardiography  was performed as previously detailed.The CMR protocol used has previously been detailed.CVI42 software . LV volumes, EF, and mass (excluding papillary muscles) were calculated from the short‐axis cine stack.All CMR analyses were performed by a single observer (P. K.) blinded to clinical data, using The primary endpoint was a composite of all‐cause mortality or hospitalization for HF . Only first events were included in the outcome analysis. All subjects underwent a minimum of 1 year follow‐up, post‐study entry. Outcome data were sourced from hospital records.t‐test, Mann–Whitney U‐test, and the χ2 test, as appropriate. BNP, creatinine, eGFR, and all plasma biomarkers were log10 transformed before analysis. 6MWT distance was square root transformed.SPSS V25  was used for statistical testing. Summary data are presented as mean ± standard deviation or median [25–75% inter‐quartile range (IQR) or range]. Between group differences were compared using the P < 0.05 was considered significant.Spearman's correlations were performed to check for potential associations of FGF23 with continuous variables in HFpEF patients. Multivariable linear regression modelling was undertaken to determine variables independently associated with 6MWT distance. P < 0.1 were then entered into multivariable analysis to identify independent predictors using both backwards and forwards stepwise elimination methods. Four separate, clinically relevant multivariable models were generated including a final model incorporating the strongest predictors. Generally, multivariable models were limited to no more than six parameters, allowing for approximately one parameter/10 composite events. The final model however was also adjusted for additional, well‐recognized prognosticators [e.g. blood pressure (BP) and NYHA class] and potential confounders , independent of their P values. Continuous variables were Z‐standardized to enable comparison of hazard ratios (HRs) based upon one standard deviation increase in the predictor variable. Receiver operator characteristic (ROC) analysis was undertaken to gauge the accuracy of the final independent Cox model to predict adverse events.Event rates were calculated from Kaplan–Meier analysis. Differences in survival curves were tested using the log‐rank test. To account for missing data . The final cohort with complete plasma biomarker profiles comprised 130 HFpEF patients and 42 controls. As reported previously, ECV and iECV could not be calculated in a small subset of consecutive HFpEF  and controls  owing to unavailability of the T1 mapping sequence at the time of the CMR scan.The overall study recruitment is shown in TablesBaseline clinical and imaging characteristics are shown in P < 0.0001)], lower haemoglobin, worse renal function, increased LV mass, and more concentric LV remodelling (mass/volume). Surrogate markers of diastolic dysfunction, that is, echocardiographic E/e′, BNP, maximal left atrial volume index [LAVImax], and LAEF were worse in HFpEF. Focal (MI and non‐MI) and diffuse (ECV and iECV) fibrosis were greater in HFpEF. Plasma biomarkers associated with inflammation  and OPG were also higher in HFpEF . FGF23 levels did not differ significantly between hypertensive and non‐hypertensive controls (P = 0.920).FGF23 levels were significantly higher in HFpEF compared with controls  remained an independent predictor along with Lg BNP  and prior HF hospitalization . Plots of the scaled Schoenfeld residuals against time were centred around zero with no time‐dependent trend, suggesting that the proportional hazards assumption was upheld using the functional forms supplied to the Cox models. The final independent Cox model to predict outcomes yielded and area under the ROC curve of 0.786 (P < 0.0001).Sixteen variables showed univariate association with adverse outcomes Table5. ClinFigureP < 0.0001).Kaplan–Meier survival curves stratified according to median FGF23 are shown in In this extensively phenotyped cohort of patients with HFpEF, higher FGF23 was associated with more severe HF, as evidenced by higher NYHA class and BNP, lower systolic and diastolic BP, and higher LV filling pressure (E/e′). Furthermore, higher FGF23 was associated with evidence of more advanced anaemia and renal dysfunction, as well as with evidence of systemic inflammation. Importantly, we observed independent associations between higher circulating FGF23 concentrations and exercise capacity (6MWT), and the risk of death or hospitalization with HF in patients with HFpEF.FGF23 is a regulator of bone mineral, vitamin D, and iron homeostasis; in turn, FGF23 production is regulated by various factors including iron deficiency and inflammation.The rationale for the link between FGF23 and adverse outcomes in HFpEF is not clear. It is known that FGF23 is associated with prognosis in, and progression of, chronic jkidney diseaseOur observation of association between circulating FGF23 and adverse outcome in HFpEF is in keeping with that from a recent studyImportantly, to the association with adverse prognosis, we report an additional association for FGF23 with reduced exercise capacity in HFpEF. HFpEF is a syndrome characterized by limitation of exercise capacity, in the presence of preserved LVEF, LVH, and elevated plasma natriuretic peptides. Our cohort of 130 patients demonstrated the archetypal HFpEF phenotype, with LVEF comparable with the matched control cohort (56 vs. 58%), moderate elevation of BNP, and clearly elevated LV mass and filling pressures. Exercise capacity in patients with HFpEF was reduced markedly, with median 6MWT distance (180 m) less than half of that compared with age‐matched and sex‐matched controls (vs. 380 m).Table, lower haemoglobin, higher BMI, and higher FGF23, but not of eGFR or creatinine, is of note. As with the association with prognosis, we cannot ascribe a causal relationship between elevated FGF23 and reduced 6MWT distance. However, potential contributors to this apparent effect include the potential for FGF23 to induce LVH, and its association with progressive renal impairment, as already noted. However, using gold standard CMR imaging, we failed to observe any correlation between indices of FGF23 with LV mass indices. Alternatively, FGF23 may promote myocardial fibrosis and remodelling via activation of the renin–angiotensin–aldosterone systemA number of clinical variables demonstrated univariate association with 6MWT distance, including parameters of renal impairment (eGFR and creatinine) and plasma FGF23  and measures of LV remodelling (LVEDVI and LVESVI) showed univariate associations, these were not retained after adjustment for covariates. As well as higher age and BMI and lower haemoglobin, higher FGF23 was the only laboratory parameter to retain a multivariate association with poorer exercise capacity. We suggest that this observation supports a possible direct link between FGF23 and exercise capacity in this patient group.r = 0.446, P < 0.0001). Clustering of these peptides as markers of outcome in HFpEF has been reported in one previous study,FGF23 plays a pivotal role in bone mineral homeostasis, and levels increase in response to increasing phosphate levels and increase as renal impairment progresses. In this context, we noted elevated circulating levels of a second biomarker related to mineral metabolism and OPG in our patients with HFpEF, with a relatively strong correlation between FGF23 and OPG levels  and the John and Lucille Van Geest Foundation. GPM was supported by a National Institute for Health Research Career Development Fellowship (2014‐07‐045) and Research Professorship (RP‐2017‐08‐ST2‐007).PK recruited the patients, supervised the study visits and CMR scans (with AS and JNK), analysed the data including qualitative analysis for the presence of MI, performed the statistical analysis, and drafted the initial manuscript along with IBS and JRA. GGS undertook follow‐up outcome data collection. BNP and other serum sampling were undertaken in the hospital pathology laboratory under the supervision of PG. PK, IBS, LLN, and GPM conceived the study. All authors critically revised the manuscript for important intellectual content, approved the final version for submission, and agreed to be accountable for all aspects of the work in ensuring that questions relating to the accuracy or integrity of any part of the work are appropriately investigated and resolved.The study complied with the Declaration of Helsinki and the National Research Ethics Service approved the study. Written informed consent was obtained from all subjects prior to participation.Figure S1. Association of fibroblast growth factor 23 with six minute walk test distance.Caption: Scatter plot illustrating the relationship between Log fibroblast growth factor 23 with square root transformed six minute walk test distance.Click here for additional data file.Figure S2. Kaplan–Meier survival analysis.Caption: Survival curves stratified according to median fibroblast growth factor 23.Click here for additional data file.Table S1. Multivariable predictor models inclusive of FGF23 for the composite endpoint of death and/or hospitalization with heart failure.Click here for additional data file.


The 501Y.V2 variants of SARS-CoV-2 containing multiple mutations in spike are now dominant in South Africa and are rapidly spreading to other countries. Here, experiments with 18 pseudotyped viruses showed that the 501Y.V2 variants do not confer increased infectivity in multiple cell types except for murine ACE2-overexpressing cells, where a substantial increase in infectivity was observed. Notably, the susceptibility of the 501Y.V2 variants to 12 of 17 neutralizing monoclonal antibodies was substantially diminished, and the neutralization ability of the sera from convalescent patients and immunized mice was also reduced for these variants. The neutralization resistance was mainly caused by E484K and N501Y mutations in the receptor-binding domain of spike. The enhanced infectivity in murine ACE2-overexpressing cells suggests the possibility of spillover of the 501Y.V2 variants to mice. Moreover, the neutralization resistance we detected for the 501Y.V2 variants suggests the potential for compromised efficacy of monoclonal antibodies and vaccines.  •501Y.V2 showed no higher infectivity in cells with hACE2 comparing to 614G variant•501Y.V2 showed increased infectivity in cells with mACE2 compared to 614G variant•501Y.V2 escaped neutralization by most of neutralizing monoclonal antibodies•501Y.V2 significantly compromised the inhibitory effects of polyclonal antibodies Experiments with pseudotyped viruses show that the 501Y.V2 variant of SARS-CoV-2 exhibits resistance to neutralization from monoclonal antibodies and sera from convalescent as well as immunized individuals, predominantly due to the E484K and N501Y mutations in the receptor-binding domain of the viral spike protein. SARS-CoV-2 is a member of the coronavirus family, which carries the largest genome among single-stranded RNA viruses. Although the replication-dependent RNA polymerase in most RNA viruses has no proofreading activity, the coronavirus genome encodes a 3′–5′ exonuclease  with proofreading activity that can partially correct mutations introduced during virus replication  protein of SARS-CoV-2 can increase the infectivity of the virus. For example, the D614G mutation in the S protein increases viral infectivity in susceptible cells by 8- to 10-fold , and botFortunately, this 614G mutation did not cause a significant change in viral antigenicity that would allow its escape from immune responses resulting from infection with the original virus or from a vaccine . HoweverThe Republic of South Africa currently has the highest numbers of SARS-CoV-2-infected cases and COVID-19-related deaths in Africa. The initial SARS-CoV-2 epidemic in South Africa primarily involved the B.1 lineage identified in Italy . The preSouth Africa experienced a brief plateau following the first wave of the epidemic. However, the number of SARS-CoV-2 infections in South Africa has increased exponentially since mid-October of 2020. In this outbreak, a new 501Y.V2 lineage  was identified; variants of this lineage are genetically distinct from those of the first wave. By early November, the number of new cases infected with the 501Y.V2 variants exceeded the total infections by all of the variants from the first wave of the epidemic. It has therefore been assumed that 501Y.V2 variants have become the predominant epidemic variants in South Africa .In the present study, we refer to the three most prevalent variants of the 501Y.V2 lineages as 501Y.V2-1, 501Y.V2-2, and 501Y.V2-3. In the early stages of the second wave, 501Y.V2-1 was prevalent; it is identifiable by five amino acid mutations in the S protein (in addition to D614G), including D80A, D215G, E484K, N501Y, and A701V. Subsequently, two further mutations arose in the S protein, L18F, and K417N, resulting in the emergence of variant 501Y.V2-2. The third variant (501Y.V2-3) appeared based on deletion of S protein residues (Del242-244) from 501Y.V2-2. Compared against the S protein of the 614G virus shows that 501Y.V2-3’s S protein contains 8 mutations: four are located at the NTD , three are in the viral RBD , and one is in the S2 region (A701V) .In this communication, we investigated the biological significance—using assays of infectivity and of antigenicity—of a set of 18 501Y.V2 lineage-related mutants. Our approach was based on construction of 18 pseudotyped viruses using the vesicular stomatitis virus (VSV)-pseudovirus system, and we generated a pseudotyped reference 614G variant as a control for the assays. We analyzed the infectivity of the pseudotyped viruses for multiple SARS-CoV-2-susceptible cell lines and for a panel of HEK293T cells expressing the ACE2 ortholog proteins from a total of 14 mammal species. We also profiled the antigenicity of the pseudotyped viruses to monoclonal antibodies, to SARS-CoV-2 convalescent sera, and to RBD immunize animal sera. We found that the 501Y.V2 variants showed no increased infectivity for SARS-CoV-2-susceptible human cell lines; however, the 501Y.V2 variants were less susceptible to the neutralizing activity of antibodies compared to the 614G variant. Similar results have also been reported by Daming Zhou's group when tested 501Y.V2 against vaccine-induced and SARS-CoV-2-infected sera .To study the effects of 501Y.V2-related mutations, we generated a total of 18 pseudotyped viruses. The 501Y.V2 variants, derived from B.1 , have thWe first investigated the potential infection-related effects of these mutations in assays with three cell lines known to be susceptible to SARS-CoV-2 pseudotyped virus infection : Huh-7, We then challenged these ACE2 receptor expressing cells with our 18 pseudotyped viruses. The infectivity of individual variant in each ACE2 expressing cells was assessed relative to the reference 614G variant’s infectivity. For 13 of the 14 tested ACE2-expressing cells, no significant enhancement in infectivity were detected for any of the pseudotyped viruses with 501Y.V2-related mutations B. The exTo study the effects of 501Y.V2-related mutations on viral antigenicity we tested our 18 pseudotyped viruses against a set of 17 neutralizing monoclonal antibodies targeting the RBD. Strikingly, most of monoclonal antibodies used in this study showed decreased neutralizing activity to the pseudotyped viruses carrying mutations in the RBD compared to the reference 614G variant , and S3.We found that an increasing number of mutation sites in the RBD was correlated with immune escape from a steadily increasing number of monoclonal antibodies , clearlyWe also obtained convalescent sera from 15 SARS-CoV-2-infected patients with high neutralizing antibody titers and obtained three pooled sera samples from a total of nine mice immunized with the RBD to further investigate how these mutations affect antigenicity A. NeutraTo determine how the mutations in the 501Y.V2 variants may affect neutralization activity in the sera with differing levels of neutralizing antibodies, we obtained longitudinal sera from ten SARS-CoV-2-infected patients at 2, 5, and 8 months after onset A. The ps50 for 614G <100) were not able to neutralize 501Y.V2-3 (ED50 <30).Taking the reference 614G pseudotyped virus as an example: compared to assays for the sera collected at 2 months, neutralization titers for sera collected at 5- and 8-months post-onset decreased by 2.2- and 2.5-fold, respectively C. We notMutation is a common phenomenon in the natural evolution of viruses, and SARS-CoV-2 is no exception. The emergence of a variety of SARS-CoV-2 mutants has become a major concern during the ongoing pandemic. Mutants may be more transmittable, or may be able to evade neutralizing monoclonal antibodies, or even polyclonal antibodies induced by either infection or vaccination. That is, a shift in the predominant variant(s) in various epidemics could cause potentially declines in the protective effects of vaccines or neutralizing monoclonal antibodies that were developed based on the original variant. Here, we constructed 18 501Y.V2-related pseudoviruses using a VSV-based system and systematically studied the effects of mutations on virus infectivity and antigenicity. We found that, compared with the reference 614G variant, the infectivity of the 501Y.V2 variants in human receptor cells did not change significantly, but did alter antigenicity. The neutralizing activity of multiple RBD-targeting monoclonal antibodies decreased significantly, and polyclonal antibodies  also had decreased neutralizing activity against 501Y.V2 variants to certain degrees.Previous reports have shown that passage of SARS-CoV-2 in mice can result in an increase in infectivity toward mice and can cause symptoms similar to human COVID-19, including interstitial pneumonia and inflammatory responses . This enMonoclonal antibodies P2C-1F11 and H014 showed no reduction in their neutralizing capacity against all three 501Y.V2 pseudotyped viruses. The common feature of these two antibodies is that they both have a relatively high number of binding sites within the RBD. The binding interface between P2C-1F11 and RBD involves 22 amino acid residues . The RBDAlthough H014 and P2C-1F11 neutralized all of the 501Y.V2 variants we tested in the present study, we previously showed that some other mutations in the RBD region lead to decreased neutralizing capability for P2C-1F11 (A475V) and H014 (A435S and Y508H) . Thus, gInterestingly, our data from assays with convalescent sera indicate that the K417N mutation actually increases viral sensitivity to neutralization. Consider that in the closed conformation of the S protein, K417 forms hydrogen bonds with the main chain of N370 in the neighboring S protomer D, resultIt is notable that residue 484 has mutated into a variety of different amino acids under pressure of SARS-CoV-2 convalescent sera  e.g., E. This vaThe 501Y.V2 variants showed no obvious changes in infectivity SARS-CoV-2-susceptible cell lines. However, RBD mutations led to significantly higher viral infection in HEK293T cells expressing the murine ortholog of ACE2. Simultaneous mutation of three amino acids in the RBD of the 501Y.V2 variants decreased sensitivity to neutralization by SARS-CoV-2 convalescent sera and RBD-immunized sera, while mutations outside of the RBD had minimal effects on viral infectivity and antigenicity. Moreover, our data support that the predominant 501Y.V2 variants may compromise the therapeutic efficacy of existing monoclonal antibodies or convalescence sera, or even cause a decrease in the protective efficacy of existing vaccines. Therefore, studies on SARS-CoV-2 reinfection should also be conducted to evaluate whether the immune response established by an early viral infection can prevent reinfection by the newer mutant variants. It also remains unclear whether the variants induce strong immune responses. Close monitoring and functional genetic analysis of these prevalent variants could be informative for guiding prevention and control measures for the SARS-CoV-2 pandemic.The application of pseudotyped virus to study the infectivity and antigenicity of the virus has been widely used in the field of virus research , especiawangyc@nifdc.org.cn).Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Youchun Wang  was used to detach cells for subculturing every 2–3 days.Huh-7 , Vero , LLC-MK2  and HEK293T  cells were cultured in Dulbecco’s modified Eagle medium . All the cells were cultured in media supplemented with 100 U/mL of Penicillin-Streptomycin solution , 20 mM N-2-hydroxyethyl piperazine-N-2-ethane sulfonic acid , and 10% fetal bovine serum  in a 5% COSera from 15 convalescent patients were collected from the Chinese CDC of Heilongjiang  and Liaoning (CSC15) provinces. A series of 30 convalescence serum samples  were provided by the University of South China. Written informed consent was obtained from each individual for serum collection.The sera were obtained by immunizing nine SPF BALB/c mice with the SARS-CoV-2 RBD protein. RBD protein (20 μg) was mixed with an equal amount of aluminum adjuvant and injected subcutaneously through the head and neck. Immunization was performed once every other week . Blood samples were collected 14 days after the third immunization. Sera of three mice were pooled and labeled as RBD1, RBD2, and RBD3. The protocol of the animal study was approved by the Ethical Review Committee for Animal Welfare of The National Institutes for Food and Drug Control.XhoI sites to obtain the plasmid pcDNA3.1-SARS-CoV-2-spike (pcDNA3.1.S2).The SARS-CoV-2 spike (GenBank: MN908947) expression plasmid was optimized for mammalian codon usage and was inserted into the eukaryotic expression vector pcDNA3.1 using the BamHI and XhoI sites to get ACE2 expression plasmids from the different species.A total of 14 ACE2 expressing plasmids were constructed, including human (BAB40370.1), mink (QNC68911.1), dog (MT663955), cat (MT663959), pangolin (XP_017505746.1), pig (NP_001116542.1), mouse (ABN80106.1), bat (KC881004.1), cow (NP_001019673.2), rabbit (MT663961), ferret (MT663957), sheep (XP_011961657.1), civet (AY881174.1), and monkey (MT663960). Each gene of the 14 species was mammalian codon-optimized. The codon-optimized ACE2 fused with a FLAG tag (GACTACAAGGACGATGACGATAAG) at the 3′-terminal end was synthesized by General Biol. Inc, . Each synthesized sequence was inserted into the eukaryotic expression vector pRP[Exp]-EGFP-CMV using the BamHI and DpnI (NEB) overnight and used to transform E. coli. DH5α competent cells. The bacteria seeded on the corresponding resistance plates were incubated at 37°C overnight. Single colonies were selected and then sequenced to confirm the integrity of the expected mutation. Specific mutation sites and corresponding primers (Sangon Biotech) are shown in the Based on pcDNA3.1.S2, 18 mutant plasmids were constructed. The point mutation method was conducted as described in our previous study , 2020b. 2 environment at 37°C, the cell surface expression of the FLAG-tagged ACE2 orthologs was assessed by flow cytometry: 1x106cells/tube were stained with 1 μg/ml PE labeled anti-Flag antibody (Biolegend). The fluorescent signal was examined using a BD FACS CantoTM II Flow Cytometer.ACE2 expressing cells from different species were prepared as follows: taking the T75 flask as an example, HEK293T cells were transfected with 30 μg of ACE2 plasmid using Lipofectamine 2000 (Invitrogen) transfection reagent to obtain ACE2 overexpressing cells. The culture medium was the same as that used for the HEK293T cells. After 24 h culture in a 5% CO5 cells/mL in a 15ml culture medium and incubated overnight in an incubator at 37°C with 5% CO2. When cells reached 70%–90% confluence, the culture medium was discarded and 15 mL G∗ΔG-VSV virus  with a concentration of 7.0 × 104 TCID50/mL was used for infection. At the same time, 30 μg of the S protein expression plasmid was transfected according to the instructions of Lipofectamine 3000 (Invitrogen), and then the cells were cultured in an incubator at 37°C and 5% CO2. After 4-6 hours, the cell medium was discarded, and the cells were gently washed two times with PBS+1% FBS. Next, 15 mL fresh complete DMEM was added to the T75 cell culture flask, which was placed in an incubator at 37°C with 5% CO2 for 24 h. After that, the SARS-CoV-2 pseudotyped virus containing the culture supernatant was harvested, filtered, aliquoted, and frozen at −70°C for further use.The pseudotyped viruses of the SARS-CoV-2 variants and the point mutation pseudotyped viruses were constructed using the methods reported in our previous study , 2020b. RNA of SARS-CoV-2 pseudotyped virus and point mutation pseudotyped virus was extracted using the QIAamp Viral RNA Mini Kit . The virus DNA was obtained by reverse transcription using the SuperScript III First-Strand Synthesis System for RT-PCR kit reagent (Invitrogen). RT-PCR was performed using TB Green Premix Ex TaqII (Takara). The plasmid containing the P protein gene of the VSV virus was used as the standard to calculate the viral copy number. See the primers in the 4/100 μl. Chemiluminescence monitoring was carried out after a 24 h incubation with 5% CO2 at 37°C. The supernatant was adjusted to 100 μL for each sample. Luciferase substrate was mixed with cell lysis buffer  and was added to the plate (100 μl/well). Two minutes later, 150 μL of lysate was transferred to opaque 96-well plates. The luminescence signal was detected using a PerkinElmer Ensight luminometer, with data collected in terms of relative luminescence unit (RLU) values. Each group contained two replicates, and these experiments were repeated three times.After quantification by RT-PCR, the pseudotyped virus was diluted to the same particle number, and 100 μL aliquots were added into 96-well cell culture plates. Cells of the assayed cell lines were then digested with trypsin and added into each well at 2 × 104/100 μl). After incubation with 5% CO2 at 37°C for 24 hours, luminescence was measured as described above. The sample EC50 (median effect concentration) was calculated using the Reed-Muench method (The effects of the monoclonal antibodies and sera on the entry inhibition of the pseudotyped viruses was evaluated by detecting the decrease of luciferase gene expression . The samh method .We modeled the spike protein based on the Protein Data Bank coordinate set 6VXX, showing the first step of the S protein trimer activation with one RBD domain in the up position, bound to the hACE2 receptor . We used∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.005, ∗∗∗∗ p < 0.001.GraphPad Prism 8 was used for plotting and statistical analysis; the values were expressed as means ± SEM. One-way ANOVA and Holm-Sidak’s multiple comparison tests were used to analyze differences between groups. A p value of less than 0.05 was considered to be significant.


The aim was to explore the association between the TNF-α promoter -1031T/C single nucleotide polymorphism (SNP) and the serum TNF-α level in addition to nephropathy among type 2 diabetic patients. The study included 38 T2DM subjects without nephropathy (DM group), 40 subjects with DN, and 20 controls. Identification of TNF-α promoter gene polymorphism -1031T/C was done by PCR-RFLP, and genotyping was confirmed by direct sequencing. The serum TNF-α level was assessed by ELISA. Correlations were tested by Pearson's correlation analysis. Logistic regression was used to detect the most independent factor for development of DN. The serum level of TNF-α in the DM group was significantly higher than controls (p < 0.001); also, the DN group was considerably higher than controls and DM without nephropathy (p < 0.001). Also, there was a significant positive correlation between serum levels of TNF-α with FBG (fasting blood glucose), creatinine, total cholesterol, LDL-C, HbA1c, and microalbumin/creatinine ratio (ACR) among the DN group . Mutant homozygous CC and heterozygous TC genotypes were higher in DN than in DM and controls. C allele was more represented in DN than in DM and controls (p = 0.003) while T allele was higher in controls than in DM and DN patients. The levels of TNF-α were higher in subjects who had mutant CC than the wild TT genotype among DN (p < 0.001). C allele was more risky for DN than T allele between DN and controls by 5.4-fold (CI: 1.75-16.68) as well as between DN and DM by 2.25-fold (CI: 1.1-4.59). Conclusion. Serum levels of TNF-α were higher in individuals with mutant CC genotype of -1031T/C TNF-α gene, and C allele could be associated with increased risk for nephropathy among patients with T2DM.Type 2 Diabetes Mellitus (T2DM) is well known to include an inflammatory component that has been considered to be related to diabetic complications. Diabetic nephropathy (DN) is one of the significant complications as it constitutes the most frequent cause of end-stage renal disease. Tumor Necrosis Factor- Type 2 DM is one of the most widespread metabolic disorders. Sustained hyperglycemia in patients with T2DM is the major cause of micro- and macrovascular complications including DN, which could develop at a later stage of the disease . DN is cα is a cell signaling protein interrelated to systemic inflammation; in addition, it is a member of cytokines tangled in acute phase reaction [α is produced mainly by monocytes/macrophages, even though intrinsic renal cells can also synthesize this cytokine. TNF-α actions are assisted by specific cell surface receptors. Binding of TNF-α to its receptors results in the expression of a variety of growth factors, transcription factors, cytokines, receptors, mediators of inflammatory processes, and acute phase proteins; in addition, it could mediate both apoptosis and necrosis. Consequently, TNF-α accelerates the release and synthesis of inflammatory mediators and could participate in the progress of DN [Cytokines are significant mediators in the immune system, and their response due to an inappropriate balance may largely regulate disease predisposition. TNF-reaction . TNF-α iss of DN , 5.α gene is located within the Class III region of the human major histocompatibility complex (MHC) on chromosome 6 (6p21.31) traversing about 3 kb containing 4 exons. Control of TNF-α production takes place at both the transcriptional and posttranscriptional levels, with regulatory sequences within the 5′ end of the gene regulating the rate of transcription [The locus of TNF-α gene, having the ability to cause structural alterations inside regulatory sites that could disturb the function and regulation of TNF-α production. The location of the gene inside the MHC region has augmented the possibility that SNPs within this locus may contribute to the development of many diseases, such as T2DM and DN [Many SNPs have been recognized in the promoter region of human TNF-M and DN .α gene at location -1031T/C have been associated with different inflammatory and autoimmune diseases [1031T/C SNP of TNF-α and the susceptibility to develop nephropathy in patients with T2DM.Polymorphisms located in the 5′ regulatory area of TNF-diseases , 9. TherThis present case-control study involved 98 subjects who attended Internal Medicine Outpatient Clinics & Inpatient Department, Menoufia University Hospitals, Egypt, between September 2016 and December 2018. They were divided into 3 groups: group I: 20 apparently healthy controls; group II (DM): 38 T2DM without nephropathy, their albumin/creatinine ratio (ACR) < 30 mg/g; and group III (DN): 40 T2DM with nephropathy, their ACR < 30 mg/g.Exclusion criteria were patients with history of hypoglycemic coma or diabetic ketoacidosis in the last 3 months before the study, urinary tract infection or other renal disease, hypertension, congestive heart failure, fever, inflammatory diseases like asthma and rheumatoid arthritis, pregnancy, infections, autoimmunity, neoplasm, or other endocrine diseases. This study was approved by the Research Ethics Committee, and written informed consent was obtained from all participants (written in Arabic).For all subjects, the following were done: history taking, clinical examination, and assessment of anthropometric measurements.μl of whole blood on EDTA was stored at 4–8°C, and estimation was carried out within 1 week of collection by ion-exchange resin chromatography using commercially available kits.A fasting blood sample was withdrawn under aseptic protections and collected into plain and EDTA vacutainers. For glycated hemoglobin, 400 α level by ELISA. Another venous sample was taken after 2 hours of eating to measure the 2 h postprandial (2 h pp) glucose level. Urine samples were collected to estimate microalbumin and creatinine in urine, and then, ACR was calculated.Another blood sample on EDTA was stored in aliquots at −80°C till further DNA extraction. Serum was separated for biochemical investigations such as fasting blood glucose (FBG), blood urea nitrogen (BUN), creatinine, and lipid profile, which were carried out using Beckman Coulter (Au 680) chemistry auto analyzer using a kit supplied by Beckman, USA, while low-density lipoprotein (LDL-C) was calculated by Friedewald's and Fredrickson's formula. An aliquot of serum was kept at −20°C till further use for estimation of the TNF-1031T/C polymorphism of TNF-α gene, polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was done.Genomic DNA was extracted from whole blood using a commercially available DNA extraction kit . DNA was stored at −20°C until additional analysis. To genotype the -μl which included 5 μl (100 ng) of genomic DNA, 4.5 μl of nuclease-free water, 1.5 μl forward and reverse primers, and 12.5 μl of DreamTaq PCR Master Mix . Amplification was done using a Prime Thermal Cycler  with the following protocol: initial incubation at 95°C for 5 min, followed by 35 cycles of denaturation at 95°C for 30 s, annealing at 54°C for 30 sec, and extension at 72°C for 45 sec, followed by a final incubation at 72°C lasting 5 min. Amplicons with 264 bp in length were digested by BpiI fast digest restriction enzyme  incubated at 37°C for 15 min as a reaction mixture of 10 μl of PCR product, 2 μl of enzyme buffer, 1 μl of the enzyme (BpiI) (1 U), and 7 μl nuclease-free water. The digested products were separated by 2.5% agarose gel electrophoresis and identified by ethidium bromide staining. Stained fragments were visualized under UV  was performed to get the best cutoff for TNF-α. The Spearman coefficient was used for correlation. For genotype distribution, the chi-squared test and Monte Carlo test were used. Odds ratio (OR) and confidence interval (CI) were calculated by logistic regression analysis. The level of significance was set at 0.05 or less.Data were collected, tabulated, and analyzed by SPSS software package version 20.0. For comparisons of demographic data and biochemical investigations between the studied groups, the following were used: chi-squared test, ANOVA test followed by post hoc Tukey's test, Kruskal-Wallis test followed by post hoc Dunn's test, Student's p < 0.001) in DM and DN patients than controls. The duration of diabetes was longer in DN than DM. FBG, 2 h pp, and HbA1c were significantly higher (p < 0.001) in both patient groups compared to controls, where HbA1c was also higher in DN than DM (p = 0.013) (p < 0.001) in DN patients as compared to DM, whereas the high-density lipoprotein (HDL-C) level is significantly lower (p < 0.001) in DN as compared to DM. Serum creatinine and BUN levels were significantly higher (p < 0.001) in DN compared to both DM and controls. As regards the serum TNF-α level, patient groups were significantly higher than controls; in addition, DN were significantly higher than DM (p < 0.001). The ROC curve  . Total cOC curve  revealedDN group .α gene promoter -1031T/C (p = 0.003), while T allele was more represented in controls than in DM and DN patients. The results also revealed that the TNF-α level in DM was significantly higher (p < 0.001) in TC and CC genotypes than TT genotype. Moreover, the TNF-α level among DN was significantly higher in CC genotype than TC and TT genotypes . Also, TC genotype was significantly higher than TT genotype (p = 0.039). In addition, the C allele group among both DM and DN was significantly higher in the TNF-α level than the T allele group (p < 0.001).The genotypic and allelic frequencies of TNF--1031T/C  were fouα carry the risk for DN; however, there was no independent risk factor as the disease is multifactorial.The evaluation of the risk for DN at the genotype level is shown in α is a significant feature of T2DM. These remarks suggest that TNF-α could participate in the pathogenicity of T2DM and DN. The TNF-α level varies among individuals; in addition, it is genetically determined [Diabetes is a promptly rising health problem in Egypt where the prevalence of T2DM was tripled in the previous 2 decades to reach around 15.6% of all adults 20–79 years . Diabetitermined .Both patient groups were significantly higher in BMI than controls without significant difference between DM and DN. These results agreed with Doghish et al.  who repoMaric-Bilkan  stated tThe results revealed that the duration of diabetes was longer in DN than DM. This agreed with Mahfouz et al. ; meanwhiIn the present study, FBG, 2 h pp, and HbA1c were significantly higher in patients compared to controls, while there was no significant difference between the DM and DN groups. This agreed with Motawi et al. ; meanwhiThis study had found that lipid profile obtained results agreed with Mahfouz et al. . Meanwhiα were significantly elevated in both patient groups than controls; in addition, DN were higher than DM. The TNF-α level showed a significant positive correlation with FBG, creatinine, total cholesterol, LDL-C, HbA1c, and ACR in the DN group. These results are consistent with those observed by Navarro and Mora-Fernandez [α levels in DN patients suggesting an elevated inflammatory milieu in DN. In addition, patients with T2DM had been reported to have 3–4 times greater TNF-α circulatory levels compared to controls, and these levels are more elevated in diabetic patients with microalbuminuria with respect to normoalbuminuria. Centered on the above, the results support the cytotoxic role of TNF-α in the glomerular damage mediated by hyperglycemia, which in turn leads to progressive albuminuria [Our results revealed that the serum levels of TNF-ernandez  and Chenernandez  who alsouminuria .α level showed a positive correlation with age and urea and a negative correlation with HDL-C and LDL-C. However, Gupta et al. [α level in both patients and controls did not reach statistical significance. This could be due to the discrepancies in their study designs and variations in the genetic background and may also be due to environmental exposures of the T2DM patients enrolled in these studies.Moreover, Umapathy et al.  found tha et al.  reportedα—mainly produced by monocytes and macrophages—plays a vital function in the course of DN. Also, it had effects on insulin resistance and insulin secretion. In addition, TNF-α has been cytotoxic to the epithelial, mesangial, and glomerular cells that could lead to direct kidney injury. Also, it was stated that TNF-α had a critical role in mediating inflammatory processes, which was involved in glomerular and tubulointerstitial damage [The TNF-l damage .α gene have a direct functional importance in terms of regulating TNF-α production. Particularly, there is a concern in these polymorphic sites in the regulatory regions of the TNF-α gene that relate with the DNA motifs in which the transcription factors bind. The -1031T/C polymorphisms in the 5′ regulatory region of TNF gene have been associated with many inflammatory and autoimmune diseases. To clarify the TNF gene polymorphism role in the pathogenesis of DN, the -1031T/C SNP was studied in DM and DN then interrelated to TNF-α level.SNPs in the TNF-α among DN patients than the subjects with wild TT genotype; in addition, the serum TNF-α level was found to be higher in both DM and DN individuals of C allele compared to T allele.The results revealed that homozygous mutant CC genotype had an elevated level of serum TNF-α gene promoter -1031T/C polymorphism was associated with elevated plasma TNF-α levels; however, this was not statistically significant. They also found that T2DM patients having T/C and C/C SNPs had 3-fold increased risk of evolving nephropathy. This discrepancy in the results could be the variation in the ethnicity of the study groups.A previous study conducted by Gupta et al.  revealedα is a vital marker in few inflammatory diseases being a high producer of TNF-α and disease susceptibility. The C variant stimulates the binding of nuclear factors except NF-κB to the TNF-α gene promoter, which may lead to a rise in TNF-α expression [α and its receptors are expressed and stimulate the production of other cytokines such as IL-8, acute phase proteins, chemokine, and growth factors by adjacent cells. Further, TNF-α has been reported to participate in the development of DN through several mechanisms, including the decreased glomerular filtration rate and the glomerular blood flow and disturbance of the glomerular filtration barrier. Increased production of TNF-α can stimulate oxidative stress and have a direct cytotoxic and apoptotic effect on glomerular cells [It has been well documented that the homozygous CC genotype of TNF-pression . This inar cells .1031T/C SNP of TNF-α is concomitant with a significant risk for development of diabetic nephropathy. Also, the circulatory levels of TNF-α were higher in individuals with mutant genotype. The strength of the present study is that all patients and controls are of the same ethnic origin. We conclude -1031T/C SNP of TNF-α to be a genetic vulnerability factor for DN, which would attribute to the anticipation and early diagnosis of DN. However, further studies among different ethnic populations and with large sample size are necessary to attain more evidence.In summary, this study exposed that the C allele of -


The present study showed that SWJB may be beneficial in preventing oxaliplatin-induced peripheral neuropathy.Chemotherapy-induced peripheral neuropathy (CIPN) is a dose-limiting side effect caused by chemotherapy drugs, and its existence seriously affects the quality of life of patients. We first established an oxaliplatin-induced peripheral neuropathy (OIPN) model and then measured and evaluated mechanical hyperalgesia, thermal nociception, cold allodynia, and intraepidermal nerve fiber (IENF) density to determine Siwei Jianbu Decoction's role in preventing OIPN. Then, we conducted a systematic pharmacological study that revealed important roles for the MAPK signaling pathway and proinflammatory immune pathway and confirmed these roles by western blot, immunofluorescence, and qPCR. The data show that Siwei Jianbu Decoction can effectively prevent oxaliplatin-induced neuroinflammation by inhibiting an increase in NF- Similarly, studies have found that celecoxib reduces oxaliplatin-induced hyperalgesia by inhibiting ERK1/2 signaling in the spinal cord  (http://www.organchem.csdb.cn) for further screening [The compounds of four herbs in J12 were gathered from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform  (HL), drug-likeness (DL), oral bioavailability (OB), and blood–brain barrier (BBB) screening with Caco-2 permeability (Caco-2) evaluation to identify the active compounds in J12 .Ultimately, we screened the active compounds by setting the following parameters: HL ≥ 4, DL ≥ 0.18, OB ≥ 30%, BBB ≥ −0.3, and Caco-2 ≥ −0.4 .http://sea.bkslab.org/), and TCMSP database (http://lsp.nwu.edu.cn/tcmsp.php) and finally obtained the potential of the J12 target.To predict the potential targets of the active compounds in J12 screened above, we employed a systematic drug targeting method developed by Yu and others : that ishttps://cytoscape.org/) software to build a composite target network.To gain a deeper understanding of the relationship between compounds and targets, we used Cytoscape (http://www.drugbank.ca/), OMIM (http://www.omim.org/), GAD (http://geneticassociationdb.nih.gov/), PharmGKB (https://www.pharmgkb.org/index.jsp), and TTD (http://database.idrb.cqu.edu.cn/TTD/) [To further analyze known targets associated with oxaliplatin-induced peripheral neuropathy, we searched five databases: DrugBank (cn/TTD/) . We searAn interactive network for potential J12 targets was constructed using the Cytoscape built-in plugin, Bisogenet, and Cytoscape software was used for visualization (version 3.7.1) . In the http://david.ncifcrf.gov) and the Metascape database (https://metascape.org/) for KEGG annotation of nodes in J12 and Omicshare Tools to construct visual enrichment results to analyze potential targets, signaling pathways, and related biological processes in the gene network that may be involved in the regulation of active components in J12.We then applied the DAVID database (μL RIPA strong lysate and 5 μL protease were added to the tissue of each mouse at a ratio of 100 : 1 inhibitor (PMSF) mixture. After grinding the homogenate, centrifugation was performed in a low temperature centrifuge at 12000 rpm and 4°C for 15 min, the supernatant was slowly removed, and the protein concentration was measured using a BCA kit  on a microplate reader . The proteins were analyzed by 8-12% SDS-PAGE gels and transferred to polyvinylidene fluoride membranes . Nonspecific binding sites were blocked with 5% (w/v) BSA , and the membranes were incubated with the primary antibodies NF-κB, ERK1/2 (Abcam), phospho-p38, phospho-SAPK/JNK, phospho-ERK1/2, p38, SAPK/JNK, and GAPDH . The membranes were washed 4 times in TBST and then incubated with the secondary antibodies for 1 h at room temperature on a shaker. Protein expression was measured by using an ECL system .Extraction of total tissue protein: all operations were performed on ice. Mouse DRG tissue and sciatic nerve tissue were removed from the -80°C ultralow temperature refrigerator, and 500 μm and mounted on a glass slide. Briefly, sections were blocked for 1 hour at room temperature in 5% normal goat serum and 0.5% Tween-20 in PBS and incubated overnight at 4°C with a primary antibody containing NF-κB . The sections remained overnight at 4°C. After being washed three times with PBS, sections were incubated with FITC-conjugated secondary antibodies (1 : 100) in the dark at room temperature for 1 hour. After extensive washing, the sections were stained with DAPI. The immunostained DRGs were then observed under an inverted fluorescence microscope.At the end of week 6, L4 and L5 DRGs were taken from mice for immunohistochemical analysis. The sample tissue was placed in a paraformaldehyde fixative solution and placed at a temperature of 4°C. The tissue was then transferred to 20% sucrose for dehydration for 24 h, and then, the DRG was cut to a thickness of 10 Total RNA was extracted from DRG tissue using a TRIzol extraction kit . CDNA was synthesized using the reverse transcription kit TransStart Top Green qPCR SuperMix . Real-time PCR was performed using an Applied Biosystems 7500 RealTime PCR System . Due to different species, qPCR-related primers were provided by Shanghai Shenggong Co., Ltd. The sequences are as follows:GAPDH .α .IL-6 (forward: 5′-AGACTTCCATCCAGTTGCC TTCTTG-3′reverse: 5′-CATGTGTAATTAAGCCTCCGACTTGTG-3′).β .κB .μL of blood sample was collected from the eye socket of the mouse, and the supernatant of the blood sample was gathered after centrifugation at 3,000 × g for 15 minutes. According to the manufacturer's instructions, ELISA analysis kits  were used to measure the concentration of IL-1β, NF-κB, TNF-α, and IL-6 in the supernatant of the blood.Approximately 200 p values were tested by one-way analysis of variance (ANOVA) with the Tukey post hoc test for multiple comparisons. Data comparisons were considered to be significant if p < 0.05.All the experimental data are presented as the mean ± standard deviation (SD) and were analyzed with GraphPad Prism 8. The To verify whether J12 prevented oxaliplatin-induced peripheral neuropathy, we followed the behavioral experiment plan, as shown in The data on heat hyperalgesia of mice in each group showed significant differences in the sixth week. The OXA group mice were more sensitive than the control. Moreover, the difference between the OXA group and O+J12(L) group demonstrated that the prophylactic administration of J12 could attenuate oxaliplatin-induced heat hyperalgesia .The line chart shows subtle differences between the groups from the fourth week to the sixth week. The O+J12(L) group showed better preventive effects than the O+J12(H) group . In summThe immunofluorescence detection of PGP9.5 (a marker of IENFs) showed that compared with the control group , the IENJ12 contains four herbs, but the mechanism of J12 treatment of OIPN remains unclear because of the multicomponent, multitarget nature of the herbal component. Therefore, we conducted a systematic approach to investigate the possible pharmacological mechanisms of J12.A total of 471 compounds were collected from J12 to screen for active compounds by indicator, including drug half-life (HL), drug similarity (DL), oral bioavailability (OB), blood-brain barrier (BBB), and Coco-2 permeability (Coco-2) with the following criteria: HL ≥ 4, DL ≥ 0.18, OB% ≥ 30%, BBB ≥ -0.3, and Caco-2 ≥ -0.4 . FinallyThen, we erected a compound-target network from the selected active compounds and their potential targets to identify the complex interactions between them . ThroughWe used the screened active compounds and potential targets to construct a compound-target network to elucidate the complex interactions between them. Eighty-seven genes were gathered from five databases  and recognized as CIPN-related targets. Genes and proteins do not act by acting independently of each other but through interconnected molecular networks and pathways acting at multiple levels . TherefoThrough the DAVID and Metascape databases, further research on potential pathways involving candidate targets, the results were divided into two categories, namely, molecular functions/biological processes and signaling pathways. As shown in The results of KEGG annotation analysis showed that J12 participates in signaling pathways, including the MAPK signaling pathway, ubiquitin-mediated proteolysis, and neurotrophin signaling pathway . Based oκB are involved in oxaliplatin-induced neuroinflammation, western blot analysis was performed to detect the protein expression levels of MAPK and NF-κB in the DRG. Compared to control mice, p-p38, p-ERK1/2, and NF-κB were activated in the OXA group. Compared to the OXA group, most of the same proteins were reduced in the treatment group  prophylaxis group was significantly better than that of the high-dose (10 g/kg) group . After that, the target of J12 is predicted, and a composite target network is constructed to further understand the interaction of composite targets, to further identify the key regulatory factors that these targets play as an important role in CIPN therapy. We combined two PPI networks to generate a CPPI network, one for J12 targets and the other for CIPN-related targets. By screening the topological characteristics of the CPPI network, we obtained key proteins that may contribute to CIPN therapy. Using the DAVID database and Omicshare software, the MAPK signaling pathway was identified as the main pathway.κB) is a ubiquitous transcription factor well known for its role in the innate immune response. As such, NF-κB is a transcriptional activator of inflammatory mediators, such as cytokines. It has been reported that downregulating NF-κB can reduce inflammation [α (TNF-α) is a master cytokine that mediates inflammatory responses and innate immunity. Guadalupe Sabio [α. It was stated that the activation of MAP kinases and TNF-α is synchronized. Interestingly, p38 MAP kinases can also inhibit NF-κB activity following exposure to TNF-α [β expression can reduce inflammation [Nuclear factor kappa light chain enhancer of activated B cells (NF-ammation . Tumor npe Sabio  has revito TNF-α , 30. It ammation , 32, simammation , 34 and ammation , 36.κB and/or ERK/NF-κB induced by oxaliplatin. J12 could reduce the oxaliplatin-induced production of TNF-α, IL-6, and IL-1β in the dorsal root ganglion. Overall, these data suggested that J12 may be effective in attenuating neuroinflammation in mice. These findings may aid in further exploration of the mechanism of J12 prevention of oxaliplatin-induced inflammation.In our study, we investigated the effect of J12 on oxaliplatin-induced inflammatory pain and the potential underlying mechanisms. The results suggested that J12 had an anti-inflammatory effect in mice, inhibited by the activation of p38/NF-