86 research outputs found
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
Generative flows and diffusion models have been predominantly trained on
ordinal data, for example natural images. This paper introduces two extensions
of flows and diffusion for categorical data such as language or image
segmentation: Argmax Flows and Multinomial Diffusion. Argmax Flows are defined
by a composition of a continuous distribution (such as a normalizing flow), and
an argmax function. To optimize this model, we learn a probabilistic inverse
for the argmax that lifts the categorical data to a continuous space.
Multinomial Diffusion gradually adds categorical noise in a diffusion process,
for which the generative denoising process is learned. We demonstrate that our
method outperforms existing dequantization approaches on text modelling and
modelling on image segmentation maps in log-likelihood.Comment: Accepted at Neural Information Processing Systems (NeurIPS 2021
Livelihood system assessment and planning for poverty alleviation: a case of rainfed agriculture in Jharkhand
Agriculture is the major livelihood source of 75% of
the population residing in the rural areas of Jharkhand.
Agricultural production is not able to meet the
demand, leading to food and nutritional security as a
major challenge in the state. A majority of Jharkhand
population is below poverty line. This calls for an
urgent attention of the policy makers to undertake
productivity enhancement initiatives considering the
land, water and human resources. The potential of
agriculture needs to be harnessed through science-led
development using systematic planning and promoting
holistic solutions. A new paradigm of science-led participatory
research for development and holistic approach
along with enabling policies and intuitions are
needed to address the food and nutritional security
along with improved livelihoods of the rural people.
The present paper assesses the current resource base
in Jharkhand, the potential of which could be harnessed.
An effort is also made to analyse future scenarios
based on the trends of population growth in the
state. Business as usual approach would not be effective
to meet the demand and to reduce the poverty
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
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