Dataset vs Reality: Understanding Model Performance from the Perspective of Information Need

Deep learning technologies have brought us many models that outperform human beings on a few benchmarks. An interesting question is: can these models well solve real-world problems with similar settings (e.g., identical input/output) to the benchmark datasets? We argue that a model is trained to answer the same information need for which the training dataset is created. Although some datasets may share high structural similarities, e.g., question-answer pairs for the question answering (QA) task and image-caption pairs for the image captioning (IC) task, they may represent different research tasks aiming for answering different information needs. To support our argument, we use the QA task and IC task as two case studies and compare their widely used benchmark datasets. From the perspective of information need in the context of information retrieval, we show the differences in the dataset creation processes, and the differences in morphosyntactic properties between datasets. The differences in these datasets can be attributed to the different information needs of the specific research tasks. We encourage all researchers to consider the information need the perspective of a research task before utilizing a dataset to train a model. Likewise, while creating a dataset, researchers may also incorporate the information need perspective as a factor to determine the degree to which the dataset accurately reflects the research task they intend to tackle.Comment: 19 pages, 5 figure

Essential role for interleukin-2 for CD4+CD25+ T regulatory cell development during the neonatal period

Although many aspects of CD4+CD25+ T regulatory (Treg) cell development remain largely unknown, signaling through the IL-2R represents one feature for the production of Treg cells. Therefore, the present study was undertaken to further define early developmental steps in the production of Treg cells, including a more precise view on the role of interleukin (IL)-2 in this process. After adoptive transfer of wild-type Treg cells into neonatal IL-2Rβ−/− mice, only a small fraction of donor Treg cells selectively seeded the lymph node (LN). These donor Treg cells underwent rapid and extensive IL-2–dependent proliferation, followed by subsequent trafficking to the spleen. Thus, IL-2 is essential for Treg cell proliferation in neonatal LN. The number and distribution of Treg cells in the periphery of normal neonatal mice closely paralleled that seen for IL-2Rβ−/− mice that received Treg cells. However, for normal neonates, blockade of IL-2 decreased Treg cells in both the thymus and LN. Therefore, two steps of Treg cell development depend upon IL-2 in neonatal mice, thymus production, and subsequent expansion in the LN

An Image Dataset for Benchmarking Recommender Systems with Raw Pixels

Recommender systems (RS) have achieved significant success by leveraging explicit identification (ID) features. However, the full potential of content features, especially the pure image pixel features, remains relatively unexplored. The limited availability of large, diverse, and content-driven image recommendation datasets has hindered the use of raw images as item representations. In this regard, we present PixelRec, a massive image-centric recommendation dataset that includes approximately 200 million user-image interactions, 30 million users, and 400,000 high-quality cover images. By providing direct access to raw image pixels, PixelRec enables recommendation models to learn item representation directly from them. To demonstrate its utility, we begin by presenting the results of several classical pure ID-based baseline models, termed IDNet, trained on PixelRec. Then, to show the effectiveness of the dataset's image features, we substitute the itemID embeddings (from IDNet) with a powerful vision encoder that represents items using their raw image pixels. This new model is dubbed PixelNet.Our findings indicate that even in standard, non-cold start recommendation settings where IDNet is recognized as highly effective, PixelNet can already perform equally well or even better than IDNet. Moreover, PixelNet has several other notable advantages over IDNet, such as being more effective in cold-start and cross-domain recommendation scenarios. These results underscore the importance of visual features in PixelRec. We believe that PixelRec can serve as a critical resource and testing ground for research on recommendation models that emphasize image pixel content. The dataset, code, and leaderboard will be available at https://github.com/westlake-repl/PixelRec

Mechanistic evaluation of the inhibitory effect of four SGLT-2 inhibitors on SGLT 1 and SGLT 2 using physiologically based pharmacokinetic (PBPK) modeling approaches

Sodium-glucose co-transporter type 2 (SGLT 2, gliflozins) inhibitors are potent orally active drugs approved for managing type 2 diabetes. SGLT 2 inhibitors exert a glucose-lowering effect by suppressing sodium-glucose co-transporters 1 and 2 in the intestinal and kidney proximal tubules. In this study, we developed a physiologically based pharmacokinetic (PBPK) model and simulated the concentrations of ertugliflozin, empagliflozin, henagliflozin, and sotagliflozin in target tissues. We used the perfusion-limited model to illustrate the disposition of SGLT 2 inhibitors in vivo. The modeling parameters were obtained from the references. Simulated steady-state plasma concentration-time curves of the ertugliflozin, empagliflozin, henagliflozin, and sotagliflozin are similar to the clinically observed curves. The 90% prediction interval of simulated excretion of drugs in urine captured the observed data well. Furthermore, all corresponding model-predicted pharmacokinetic parameters fell within a 2-fold prediction error. At the approved doses, we estimated the effective concentrations in intestinal and kidney proximal tubules and calculated the inhibition ratio of SGLT transporters to differentiate the relative inhibition capacities of SGLT1 and 2 in each gliflozin. According to simulation results, four SGLT 2 inhibitors can nearly completely inhibit SGLT 2 transporter at the approved dosages. Sotagliflozin exhibited the highest inhibition activity on SGLT1, followed by ertugliflozin, empagliflozin, and henagliflozin, which showed a lower SGLT 1 inhibitory effect. The PBPK model successfully simulates the specific target tissue concentration that cannot be measured directly and quantifies the relative contribution toward SGLT 1 and 2 for each gliflozin

Bacterial and fungal inhibitor interacted impacting growth of invasive Triadica sebifera and soil N2O emissions

Plant invasions affect biodiversity and seriously endanger the stability of ecosystems. Invasive plants show strong adaptability and growth advantages but are influenced by various factors. Soil bacteria and fungi are critical to plant growth and are important factors affecting plant invasions. Plant invasions also affect soil N2O emissions, but the effects of invasive plants from different population origins on N2O emissions and their microbial mechanisms are not clear. In this experiment, we grew Triadica sebifera from native (China) and invasive (USA) populations with or without bacterial (streptomycin) and/or fungal (iprodione) inhibitors in a factorial experiment in which we measured plant growth and soil N2O emissions of T. sebifera. Plants from invasive populations had higher leaf masses than those from native populations when soil bacteria were not inhibited (with or without fungal inhibition) which might reflect that they are more dependent on soil bacteria. Cumulative N2O emissions were higher for soils with invasive T. sebifera than those with a plant from a native population. Bacterial inhibitor application reduced cumulative N2O emissions but reductions were larger with application of the fungal inhibitor either alone or in combination with the bacterial inhibitor. This suggests that fungi play a strong role in plant performance and soil N2O emissions. Therefore, it is important to further understand the effects of soil microorganisms on the growth of T. sebifera and soil N2O emissions to provide a more comprehensive scientific basis for understanding the causes and consequences of plant invasions

The ecological adaptability of Phragmites australis to interactive effects of water level and salt stress in the Yellow River Delta

Soil salinity and waterlogging are two major environmental problems in estuarine wetlands. To prevent the typical wetland plants from degradation by soil salinization and salt waterlogging and more effectively use the plants to provide wetland ecosystem services, we examined the ecological adaptability of Phragmites australis, a characteristic plant species in the Yellow River Delta, to the interactive effects of water level and salt stress. The results showed that P. australis adapts to salt and water table stressed environments through slowing down the growth rate, maintaining the tiller number, and adjusting the biomass allocation of different organs. The highest plant height and the largest leaf area were at 0 cm water table treatment; the 0.5 % NaCl treatment increased the aboveground biomass; higher water table increased the fibrous root biomass allocation, but largely decreased the leaf biomass. The exclusion of toxic inorganic ions such as Na+ and Cl- and the accumulation of organic solutes are also important mechanisms to aid survival in saline wetlands. On average 35.1 % of Cl- and 53.9 % of Na+ accumulated in belowground organs. The study could provide fundamental guidance for wetland restoration projects and wetland sustainable use in coastal zones such as the Yellow River Delta

Selective Availability of IL-2 Is a Major Determinant Controlling the Production of CD4 +

The development and maintenance of T regulatory (Treg) cells critically depend on IL-2. This requirement for IL-2 might be due to specificity associated with IL-2R signal transduction or because IL-2 was uniquely present in the niche in which Treg cells reside. To address this issue, we examined the capacity of IL-7R-dependent signaling to support Treg cell production and prevent autoimmunity in IL-2Rbeta(-/-) mice. Expression of transgenic wild-type IL-7R or a chimeric receptor that consisted of the extracytoplasmic domain of the IL-7R alpha-chain and the cytoplasmic domain of IL-2R beta-chain in IL-2Rbeta(-/-) mice did not prevent autoimmunity. Importantly, expression of a chimeric receptor that consisted of the extracytoplasmic domain of the IL-2R beta-chain and the cytoplasmic domain of IL-7R alpha-chain in IL-2Rbeta(-/-) mice led to Treg cells production in the thymus and periphery and prevented autoimmunity. Signaling through the IL-2R or chimeric IL-2Rbeta/IL-7Ralpha in vivo or the culture of thymocytes from IL-2Rbeta(-/-) mice with IL-7 led to up-regulation of Foxp3 and CD25 on Treg cells. These findings indicate that IL-7R signal transduction is competent to promote Treg cell production, but this signaling requires triggering through IL-2 by binding to the extracytoplasmic portion of the IL-2R via this chimeric receptor. Thus, a major factor controlling the nonredundant activity of the IL-2R is selective compartmentalization of IL-2-producing cells with Treg cells in vivo