The MOBIOS+: A FAIR (Findable, Accessible, Interoperable and Reusable) database for Mindanao's terrestrial biodiversity

Due to its complex geological history and the emergence of various biogeographic regions, the Philippines boasts an extraordinary array of flora and fauna. This unique combination has contributed to the country’s exceptional density of terrestrial species, making it amongst the highest in the world. Mindanao, in the southern part of the Philippines, is the second largest group of islands and supports high levels of endemism and proportion of threatened species. However, consolidated biodiversity records and information remain unavailable for the region. The primary goal of the Mindanao Open Biodiversity Information (MOBIOS+) database is to address these substantial data deficiencies by compiling contemporary biodiversity information from the 21st century. This initiative seeks to enhance our comprehension of biodiversity trends in Mindanao over temporal and spatial dimensions, while also creating an openly-accessible database. The database we present here is the first of its kind and currently the most comprehensive attempt to establish the largest consolidated database for Mindanao biodiversity, based on publicly available literature. With its vast collection of biodiversity data, this database will prove to be a valuable resource for advancing biodiversity research and analysis. It will further facilitate the identification of species and areas that require immediate conservation prioritisation and action, addressing the urgent challenges posed by our rapidly changing planet.The MOBIOS+ database is the first attempt to create a massive FAIR database aiming to collate biodiversity records from published literature in the Mindanao faunal region, south of the Philippines. The database currently includes 12,813 georeferenced specimen occurrences representing 1,907 unique taxa across 10 animal classes inhabiting the terrestrial and freshwater environments of Mindanao faunal region. We made all georeferenced specimen occurrences available in the Global Biodiversity Information Facility (GBIF) platform

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Search for strongly interacting massive particles generating trackless jets in proton–proton collisions ats=13 TeV\sqrt{s} = 13\,\text {TeV}

A search for dark matter in the form of strongly interacting massive particles (SIMPs) using the CMS detector at the LHC is presented. The SIMPs would be produced in pairs that manifest themselves as pairs of jets without tracks. The energy fraction of jets carried by charged particles is used as a key discriminator to suppress efficiently the large multijet background, and the remaining background is estimated directly from data. The search is performed using proton–proton collision data corresponding to an integrated luminosity of 16.1fb$^{-1}$, collected with the CMS detector in 2016. No significant excess of events is observed above the expected background. For the simplified dark matter model under consideration, SIMPs with masses up to 100GeV are excluded and further sensitivity is explored towards higher masses

Measurement of single-diffractive dijet production in proton–proton collisions at s=8 TeV\sqrt{s} = 8\,\text {Te}\text {V} with the CMS and TOTEM experiments

Measurements are presented of the single-diffractive dijet cross section and the diffractive cross section as a function of the proton fractional momentum loss ξ ξ and the four-momentum transfer squared t. Both processes p p → p X p p → p X and p p → X p p p → X p , i.e. with the proton scattering to either side of the interaction point, are measured, where X X includes at least two jets; the results of the two processes are averaged. The analyses are based on data collected simultaneously with the CMS and TOTEM detectors at the LHC in proton–proton collisions at s √ =8TeV s=8TeV during a dedicated run with β ∗ =90m β∗=90m at low instantaneous luminosity and correspond to an integrated luminosity of 37.5nb −1 37.5nb−1 . The single-diffractive dijet cross section σ p X jj σjj p X , in the kinematic region ξ<0.1 ξ<0.1 , 0.03<|t|<1GeV 2 0.03<|t|<1GeV2 , with at least two jets with transverse momentum p T >40GeV pT>40GeV , and pseudorapidity |η|<4.4 |η|<4.4 , is 21.7±0.9(stat) +3.0 −3.3 (syst)±0.9(lumi)nb 21.7±0.9(stat)−3.3+3.0(syst)±0.9(lumi)nb . The ratio of the single-diffractive to inclusive dijet yields, normalised per unit of ξ ξ , is presented as a function of x, the longitudinal momentum fraction of the proton carried by the struck parton. The ratio in the kinematic region defined above, for x values in the range −2.9≤log 10 x≤−1.6 −2.9≤log10⁡x≤−1.6 , is R=(σ p X jj /Δξ)/σ jj =0.025±0.001(stat)±0.003(syst) R=(σjj p X /Δξ)/σjj=0.025±0.001(stat)±0.003(syst) , where σ p X jj σjj p X and σ jj σjj are the single-diffractive and inclusive dijet cross sections, respectively. The results are compared with predictions from models of diffractive and nondiffractive interactions. Monte Carlo predictions based on the HERA diffractive parton distribution functions agree well with the data when corrected for the effect of soft rescattering between the spectator partons

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯

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

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