Explainable Recommender with Geometric Information Bottleneck

Explainable recommender systems can explain their recommendation decisions, enhancing user trust in the systems. Most explainable recommender systems either rely on human-annotated rationales to train models for explanation generation or leverage the attention mechanism to extract important text spans from reviews as explanations. The extracted rationales are often confined to an individual review and may fail to identify the implicit features beyond the review text. To avoid the expensive human annotation process and to generate explanations beyond individual reviews, we propose to incorporate a geometric prior learnt from user-item interactions into a variational network which infers latent factors from user-item reviews. The latent factors from an individual user-item pair can be used for both recommendation and explanation generation, which naturally inherit the global characteristics encoded in the prior knowledge. Experimental results on three e-commerce datasets show that our model significantly improves the interpretability of a variational recommender using the Wasserstein distance while achieving performance comparable to existing content-based recommender systems in terms of recommendation behaviours

XRCC3 Thr241Met polymorphism and ovarian cancer risk: a meta-analysis

Genetic polymorphism of X-ray repair crosscomplementing group 3 (XRCC3) Thr241Met has been implicated to alter the risk of ovarian cancer, but the results are controversial. In order to get a more precise result, a meta-analysis was performed. All eligible studies were identified through an extensive search in PubMed, Excerpta Medica Database (Embase), Chinese National Knowledge Infrastructure database, and Chinese Biomedical Literature Database before August 2013. The association between the XRCC3 Thr241Met polymorphism and ovarian cancer risk was conducted by odds ratios (ORs) and 95 % confidence intervals (95 % CIs). Finally, a total of four publications including seven studies with 3,635 cases and 5,473 controls were included in our meta-analysis. Overall, there was no association between XRCC3 Thr241Met polymorphism and risk of ovarian cancer under all five genetic models in overall population (T vs. C: OR = 0.99, 95 % CI = 0.960–1.03, P = 0.752; TT vs. CC: OR = 1.00, 95 % CI = 0.91–1.10, P = 0.943; TC vs. TT: OR = 0.97, 95 % CI = 0.92–1.04, P = 0.396, Fig. 1; TT vs. TC/CC: OR = 1.00, 95 % CI = 0.91–1.12, P = 0.874; TT/TC vs. CC: OR = 0.98, 95 % CI = 0.94–1.03, P = 0.486). In the subgroup analysis according to ethnicity, the results suggested that XRCC3 Thr241Met polymorphism was not associated with the risk of ovarian cancer in Caucasians population. No significant association was found between the XRCC3 Thr241 Met polymorphism and the risk of ovarian cancer. Given the limited sample size and ethnicities included in the meta-analysis, further large scaled and well-designed studies are needed to confirm our results

Current status and progress in research on dressing management for diabetic foot ulcer

Diabetic foot ulcer (DFU) is a major complication of diabetes and is associated with a high risk of lower limb amputation and mortality. During their lifetime, 19%–34% of patients with diabetes can develop DFU. It is estimated that 61% of DFU become infected and 15% of those with DFU require amputation. Furthermore, developing a DFU increases the risk of mortality by 50%–68% at 5 years, higher than some cancers. Current standard management of DFU includes surgical debridement, the use of topical dressings and wound decompression, vascular assessment, and glycemic control. Among these methods, local treatment with dressings builds a protective physical barrier, maintains a moist environment, and drains the exudate from DFU wounds. This review summarizes the development, pathophysiology, and healing mechanisms of DFU. The latest research progress and the main application of dressings in laboratory and clinical stage are also summarized. The dressings discussed in this review include traditional dressings (gauze, oil yarn, traditional Chinese medicine, and others), basic dressings (hydrogel, hydrocolloid, sponge, foam, film agents, and others), bacteriostatic dressings, composite dressings (collagen, nanomaterials, chitosan dressings, and others), bioactive dressings (scaffold dressings with stem cells, decellularized wound matrix, autologous platelet enrichment plasma, and others), and dressings that use modern technology (3D bioprinting, photothermal effects, bioelectric dressings, microneedle dressings, smart bandages, orthopedic prosthetics and regenerative medicine). The dressing management challenges and limitations are also summarized. The purpose of this review is to help readers understand the pathogenesis and healing mechanism of DFU, help physicians select dressings correctly, provide an updated overview of the potential of biomaterials and devices and their application in DFU management, and provide ideas for further exploration and development of dressings. Proper use of dressings can promote DFU healing, reduce the cost of treating DFU, and reduce patient pain

Functional metagenomic and metabolomics analysis of gut dysbiosis induced by hyperoxia

BackgroundInhaled oxygen is the first-line therapeutic approach for maintaining tissue oxygenation in critically ill patients, but usually exposes patients to damaging hyperoxia. Hyperoxia adversely increases the oxygen tension in the gut lumen which harbors the trillions of microorganisms playing an important role in host metabolism and immunity. Nevertheless, the effects of hyperoxia on gut microbiome and metabolome remain unclear, and metagenomic and metabolomics analysis were performed in this mouse study.MethodsC57BL/6 mice were randomly divided into a control (CON) group exposed to room air with fractional inspired oxygen (FiO2) of 21% and a hyperoxia (OXY) group exposed to FiO2 of 80% for 7 days, respectively. Fecal pellets were collected on day 7 and subjected to metagenomic sequencing. Another experiment with the same design was performed to explore the impact of hyperoxia on gut and serum metabolome. Fecal pellets and blood were collected and high-performance liquid chromatography with mass spectrometric analysis was carried out.ResultsAt the phylum level, hyperoxia increased the ratio of Firmicutes/Bacteroidetes (p = 0.049). At the species level, hyperoxia reduced the abundance of Muribaculaceae bacterium Isolate-037 (p = 0.007), Isolate-114 (p = 0.010), and Isolate-043 (p = 0.011) etc. Linear discriminant analysis effect size (LEfSe) revealed that Muribaculaceae and Muribaculaceae bacterium Isolate-037, both belonging to Bacteroidetes, were the marker microbes of the CON group, while Firmicutes was the marker microbes of the OXY group. Metagenomic analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Carbohydrate-Active enZYmes (CAZy) revealed that hyperoxia provoked disturbances in carbohydrate and lipid metabolism. Fecal metabolomics analysis showed hyperoxia reduced 11-dehydro Thromboxane B2-d4 biosynthesis (p = 1.10 × 10−11). Hyperoxia blunted fecal linoleic acid metabolism (p = 0.008) and alpha-linolenic acid metabolism (p = 0.014). We showed that 1-docosanoyl-glycer-3-phosphate (p = 1.58 × 10−10) was the most significant differential serum metabolite inhibited by hyperoxia. In addition, hyperoxia suppressed serum hypoxia-inducible factor-1 (HIF-1, p = 0.007) and glucagon signaling pathways (p = 0.007).ConclusionHyperoxia leads to gut dysbiosis by eliminating beneficial and oxygen strictly intolerant Muribaculaceae with genomic dysfunction of carbohydrate and lipid metabolism. In addition, hyperoxia suppresses unsaturated fatty acid metabolism in the gut and inhibits the HIF-1 and glucagon signaling pathways in the serum

MMR Deficiency Does Not Sensitize or Compromise the Function of Hematopoietic Stem Cells to Low and High LET Radiation

One of the major health concerns on long‐duration space missions will be radiation exposure to the astronauts. Outside the earth’s magnetosphere, astronauts will be exposed to galactic cosmic rays (GCR) and solar particle events that are principally composed of protons and He, Ca, O, Ne, Si, Ca, and Fe nuclei. Protons are by far the most common species, but the higher atomic number particles are thought to be more damaging to biological systems. Evaluation and amelioration of risks from GCR exposure will be important for deep space travel. The hematopoietic system is one of the most radiation‐sensitive organ systems, and is highly dependent on functional DNA repair pathways for survival. Recent results from our group have demonstrated an acquired deficiency in mismatch repair (MMR) in human hematopoietic stem cells (HSCs) with age due to functional loss of the MLH1 protein, suggesting an additional risk to astronauts who may have significant numbers of MMR deficient HSCs at the time of space travel. In the present study, we investigated the effects gamma radiation, proton radiation, and 56Fe radiation on HSC function in Mlh1+/+ and Mlh1‐/‐ marrow from mice in a variety of assays and have determined that while cosmic radiation is a major risk to the hematopoietic system, there is no dependence on MMR capacity. Stem Cells Translational Medicine 2018;7:513–520The hematopoietic system is essential for life, and normally has the capacity to sustain function for the duration of our lifetimes in spite of natural declination, which is associated with loss of DNA repair (including as DNA mismatch repair). Astronauts are exposed to ionizing radiation sources that are not commonly found on earth (such as HZE ions) and thus may display unforseen risks that need accounting in NASA risk models.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145333/1/sct312310.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145333/2/sct312310_am.pd

Position bias mitigation : a knowledge-aware graph model for emotion cause extraction

The Emotion Cause Extraction (ECE)} task aims to identify clauses which contain emotion-evoking information for a particular emotion expressed in text. We observe that a widely-used ECE dataset exhibits a bias that the majority of annotated cause clauses are either directly before their associated emotion clauses or are the emotion clauses themselves. Existing models for ECE tend to explore such relative position information and suffer from the dataset bias. To investigate the degree of reliance of existing ECE models on clause relative positions, we propose a novel strategy to generate adversarial examples in which the relative position information is no longer the indicative feature of cause clauses. We test the performance of existing models on such adversarial examples and observe a significant performance drop. To address the dataset bias, we propose a novel graph-based method to explicitly model the emotion triggering paths by leveraging the commonsense knowledge to enhance the semantic dependencies between a candidate clause and an emotion clause. Experimental results show that our proposed approach performs on par with the existing state-of-the-art methods on the original ECE dataset, and is more robust against adversarial attacks compared to existing models.Comment: ACL2021 Main Conference Long pape

Addressing token uniformity in transformers via singular value transformation

Token uniformity is commonly observed in transformer-based models, in which different tokens share a large proportion of similar information after going through stacked multiple self-attention layers in a transformer. In this paper, we propose to use the distribution of singular values of outputs of each transformer layer to characterise the phenomenon of token uniformity and empirically illustrate that a less skewed singular value distribution can alleviate the token uniformity problem. Base on our observations, we define several desirable properties of singular value distributions and propose a novel transformation function for updating the singular values. We show that apart from alleviating token uniformity, the transformation function should preserve the local neighbourhood structure in the original embedding space. Our proposed singular value transformation function is applied to a range of transformer-based language models such as BERT, ALBERT, RoBERTa and DistilBERT, and improved performance is observed in semantic textual similarity evaluation and a range of GLUE tasks

Association of MDR1 G2677T polymorphism and leukemia risk: evidence from a meta-analysis

In the light of the relationship between the MDR1 G2677T polymorphism and the risk of leukemia remains inclusive or controversial. For better understanding of the effect of MDR1 G2677T polymorphism on leukemia risk, we performed a meta-analysis. Eligible studies were identified through a search of electronic databases such as PubMed, Excerpta Medica Database (Embase), Cochrane Library, and Chinese Biomedical Literature Database (CBM). The association between the MDR1 G2677T polymorphism and leukemia risk was conducted by odds ratios (ORs) and 95 % confidence intervals (95 % CI). A total of seven publications including eight studies with 1,229 cases and 1,097 controls were included in the meta-analysis. There was no association between MDR1 G2677T polymorphism and leukemia risk in all of five models in overall populations (T vs. G: OR = 1.00, 95 % CI = 0.88–1.12, P = 0.914; TT vs. GG: OR = 0.97, 95 % CI = 0.75–1.26, P = 0.812; TG vs. GG: OR = 1.00, 95 % CI = 0.92–1.08, P = 0.939; TT vs. TG/GG: OR = 0.98, 95 % CI = 0.67–1.43, P = 0.906; TT/TG vs. GG: OR = 1.00, 95 % CI = 0.95–1.06, P = 0.994). However, the significant association was found in others (Table 2) under the homozygote model (TT vs. GG: OR = 0.68, 95 % CI = 0.48–0.94, P = 0.020) and recessive model (TT vs. TG/GG: OR = 0.63, 95 % CI = 0.43–0.92, P = 0.016). In the subgroup analysis, according to the type of leukemia, significant association was found between MDR1 G2677T polymorphism and myeloid leukemia but not lymphoblastic leukemia (TT vs. GG: OR = 0.66, 95 % CI = 0.46–0.95, P = 0.026; TT vs. TG/GG: OR = 0.56, 95 % CI = 0.38–0.84, P = 0.005). The results suggested that there was no association between MDR1 G2677T polymorphism and leukemia risk in overall populations, but significant association was found in others populations (Asians and Africans), and myeloid leukemia indicated that G2677T polymorphism might be a protective factor in the susceptibility of myeloid leukemia and in Asians and Africans