Constructing Tree-based Index for Efficient and Effective Dense Retrieval

Recent studies have shown that Dense Retrieval (DR) techniques can significantly improve the performance of first-stage retrieval in IR systems. Despite its empirical effectiveness, the application of DR is still limited. In contrast to statistic retrieval models that rely on highly efficient inverted index solutions, DR models build dense embeddings that are difficult to be pre-processed with most existing search indexing systems. To avoid the expensive cost of brute-force search, the Approximate Nearest Neighbor (ANN) algorithm and corresponding indexes are widely applied to speed up the inference process of DR models. Unfortunately, while ANN can improve the efficiency of DR models, it usually comes with a significant price on retrieval performance. To solve this issue, we propose JTR, which stands for Joint optimization of TRee-based index and query encoding. Specifically, we design a new unified contrastive learning loss to train tree-based index and query encoder in an end-to-end manner. The tree-based negative sampling strategy is applied to make the tree have the maximum heap property, which supports the effectiveness of beam search well. Moreover, we treat the cluster assignment as an optimization problem to update the tree-based index that allows overlapped clustering. We evaluate JTR on numerous popular retrieval benchmarks. Experimental results show that JTR achieves better retrieval performance while retaining high system efficiency compared with widely-adopted baselines. It provides a potential solution to balance efficiency and effectiveness in neural retrieval system designs.Comment: 10 pages, accepted at SIGIR 202

Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models

A retrieval model should not only interpolate the training data but also extrapolate well to the queries that are different from the training data. While neural retrieval models have demonstrated impressive performance on ad-hoc search benchmarks, we still know little about how they perform in terms of interpolation and extrapolation. In this paper, we demonstrate the importance of separately evaluating the two capabilities of neural retrieval models. Firstly, we examine existing ad-hoc search benchmarks from the two perspectives. We investigate the distribution of training and test data and find a considerable overlap in query entities, query intent, and relevance labels. This finding implies that the evaluation on these test sets is biased toward interpolation and cannot accurately reflect the extrapolation capacity. Secondly, we propose a novel evaluation protocol to separately evaluate the interpolation and extrapolation performance on existing benchmark datasets. It resamples the training and test data based on query similarity and utilizes the resampled dataset for training and evaluation. Finally, we leverage the proposed evaluation protocol to comprehensively revisit a number of widely-adopted neural retrieval models. Results show models perform differently when moving from interpolation to extrapolation. For example, representation-based retrieval models perform almost as well as interaction-based retrieval models in terms of interpolation but not extrapolation. Therefore, it is necessary to separately evaluate both interpolation and extrapolation performance and the proposed resampling method serves as a simple yet effective evaluation tool for future IR studies.Comment: CIKM 2022 Full Pape

Aggregation challenges in the formulation development of multi-dose peptide products

The formulation development of parenteral peptide therapeutics frequently encounters aggregation challenges. In-depth biophysical understanding of the molecule and formulation are required to achieve formulation robustness. Further, unique considerations need to be given for peptide products that require multi-dose as the use of preservatives can promote aggregation while preservative effectiveness can also be impacted by its interaction with the peptide. This presentation will focus on the reversible and irreversible fibril aggregates in peptide formulations. Biophysical characterization of aggregation and formulation will be discussed in detail. Formation of reversible aggregates and the impact of excipients especially preservatives will be discussed. For the development of fibril-prone peptides, analytical challenges, formulation strategies, as well as predictive test for kinetics will also be discussed. In particular, studies on the temperature-dependent fibril nucleation kinetics and its impact on formulation development will be presented. Please click Additional Files below to see the full abstract

Oridonin induces growth inhibition and apoptosis in human gastric carcinoma cells by enhancement of p53 expression and function

The tumor suppressive role of oridonin, an active compound extracted from Rabdosia rubescens, has been proven in several gastric cancer (GC) cell lines. The present study aimed to evaluate the effect of oridonin on another GC cell line, SNU-216, and explore the potential mechanisms. The viable cell numbers, cell migration, survival fraction, and cell viability were, respectively, evaluated by trypan blue exclusion assay, wound healing assay, clonogenic assay, and CCK-8 assay. Cell apoptosis was determined by flow cytometry assay and western blot. The expression of p53 was inhibited by transient transfection, and the efficiency was verified by western blot. qRT-PCR was performed to measure the mRNA expression of p53. Western blot was used to evaluate the protein expression of apoptosis, DNA damage and p53 function related factors. We found that oridonin significantly inhibited cell proliferation, migration, and survivability, and enhanced cell apoptosis in SNU-216 cells. However, it had no influence on HEK293 cell viability. Oridonin also remarkably enhanced the anti-tumor effect of cisplatin on SNU-216 cells, as it significantly increased apoptotic cells and decreased cell viability. Moreover, the mRNA and protein expression of p53 was significantly up-regulated in oridonin-treated cells, while Mdm2 expression was down-regulated. Furthermore, oridonin enhanced p53 function and induced DNA damage. Knockdown of p53 or employing the caspase inhibitor, Boc-D-FMK, reversed the effect of oridonin on cell viability and apoptosis-related protein expression. The present study demonstrated that oridonin exhibited an anti-tumor effect on GC SNU-216 cells through regulating p53 expression and function

Transplantation of oral mucosal epithelial cells seeded on decellularized and lyophilized amniotic membrane for the regeneration of injured endometrium

Abstract Background Intrauterine adhesion (IUA) is characterized by progressive intrauterine fibrosis as a consequence of trauma to the basal layer of the endometrium. In an attempt to relieve IUA, many approaches have been applied in the clinic but show limited effects. In this study, we investigated the effect of autologous oral mucosal epithelial cells (OMECs) seeded on decellularized and lyophilized amniotic membrane (DL-AM) on preventing the development of IUA in a rat model. Methods IUA model was established by surgical scraping of the endometrium in the left uteri (the right uteri were kept as control) of SD rats. Wounds were randomly treated as unrepaired (IUA group), repaired with DL-AM alone (DL-AM group), and DL-AM seeded with autologous OMECs (DL-AM+OMECs group), respectively, in a total of 54 rats (n = 18 each). Uterus samples were harvested for histological and immunohistochemical evaluation after 3, 7, 14, and 28 days (n = 3 in each time point) of operations. Results After surgery, the uterine cavity was observed to be filled with extensive fibrosis in the IUA and DL-AM groups, respectively, while a lower ratio of the fibrotic area was identified in the DL-AM transplantation group. Transplantation of OMECs seeded on DL-AM significantly reduced fibrosis of IUA with recovered uterine cavity and regenerated epithelium and endometrial glands as determined by CK-18 immunostaining. OMECs transplantation resulted in extensive cellular proliferation as revealed by the Ki-67 immunofluorescent staining exhibited. Meanwhile, microvessel density was significantly increased in uteri that received OMECs transplantation, which was concomitant with elevated expression of vascular endothelial growth factor. The pregnancy test (n = 6 in each group) showed successful conception in the OMEC-transplanted uteri, but not in the IUA and DL-AM groups. Conclusions Engineered epithelium developed from DL-AM seeded with OMECs showed great potential in preventing progression of intrauterine adhesion by improved endometrial epithelium regeneration

Unsteady conjugate mass transfer of a 2D deformable droplet in a modest extensional flow in across-slot

This work aims to investigate the unsteady conjugate interphase mass transfer between a stationary deformed drop and the modest extensional flow in a cross-intersected 2D channel. It is very difficult to accurately quantify the transient mass transfer rate of solute in such a geometry. Therefore, we established a mathematical model on the basic of the Stokes equation and solved it by the boundary element method, which could deal precisely with a two-phase flow system with a deformable interface; meanwhile, the convection-diffusion equation was solved by the finite difference method to calculate the unsteady conjugate interphase mass transfer. The simulation results showed that the mass transfer rate, analyzed and characterized in terms of mean concentration variation and Sherwood number Sh, was affected by capillary number Ca, Peclet number Pe, viscosity ratio lambda, interior-to-exterior diffusivity ratio K, distribution coefficient m, and wall effect factor W

Nontrivial thermoelectric behavior in cubic SnSe driven by spin-orbit coupling

Recently, tin selenide SnSe has attracted extensive attention for the reported excellent thermoelectric performance. By alloying with AgSbSe2, we observed that SnSe undergoes a phase transition from the orthorhombic structure to a cubic phase. The cubic SnSe exhibits some anomalous thermoelectric properties compared with common IV-VI cubic semiconductors, such as PbTe and SnTe. It is proven that cubic SnSe is not a trivial band semiconductor, whereas its band gap originates in the spin-orbit coupling effects. In this nontrivial semiconductor, the competing factors, Seebeck coefficient and electrical conductivity, can be simultaneously optimized. The peak ZT reaches 0.82 at 842 K in Sn-0.4(AgSb)(0.3)Se. This study reveals that such spin-orbit semiconductors are a new class of promising thermoelectric materials, in which the thermoelectric performance strongly depends on the local spin-orbit coupling, besides the overall chemical bonding

Tuning the K⁺ Concentration in the Tunnel of OMS‑2 Nanorods Leads to a Significant Enhancement of the Catalytic Activity for Benzene Oxidation

OMS-2 nanorods with tunable K⁺ concentration were prepared by a facile hydrothermal redox reaction of MnSO₄, (NH₄)₂S₂O₈, and (NH₄)₂SO₄ at 120 °C by adding KNO₃ at different KNO₃/MnSO₄ molar ratios. The OMS-2 nanorod catalysts are characterized by X-ray diffraction, transmission electron microscopy, N₂ adsorption and desorption, inductively coupled plasma, and X-ray photoelectron spectrometry. The effect of K⁺ concentration on the lattice oxygen activity of OMS-2 is theoretically and experimentally studied by density functional theory calculations and CO temperature-programmed reduction. The results show that increasing the K⁺ concentration leads to a considerable enhancement of the lattice oxygen activity in OMS-2 nanorods. An enormous decrease (Δ<i><i>T</i></i>₅₀ = 89 °C; Δ<i>T</i>₉₀ > 160 °C) in reaction temperatures <i>T</i>₅₀ and <i>T</i>₉₀ (corresponding to 50 and 90% benzene conversion, respectively) for benzene oxidation has been achieved by increasing the K⁺ concentration in the K⁺-doped OMS-2 nanorods due to the considerable enhancement of the lattice oxygen activity