Miracle-dz/UniFAR-FTUs huggingface dataset:
Persona-Aware Tips Generation?

Tips, as a compacted and concise form of reviews, were paid less attention by researchers. In this paper, we investigate the task of tips generation by considering the “persona” information which captures the intrinsic language style of the users or the different characteristics of the product items. In order to exploit the persona information, we propose a framework based on adversarial variational auto-encoders (aVAE) for persona modeling from the historical tips and reviews of users and items. The latent variables from aVAE are regarded as persona embeddings. Besides representing persona using the latent embeddings, we design a persona memory for storing the persona related words for users and items. Pointer Network is used to retrieve persona wordings from the memory when generating tips. Moreover, the persona embeddings are used as latent factors by a rating prediction component to predict the sentiment of a user over an item. Finally, the persona embeddings and the sentiment information are incorporated into a recurrent neural networks based tips generation component. Extensive experimental results are reported and discussed to elaborate the peculiarities of our framework.
Implicit Regularization in Over-parameterized Neural Networks

Over-parameterized neural networks generalize well in practice without any explicit regularization. Although it has not been proven yet, empirical evidence suggests that implicit regularization plays a crucial role in deep learning and prevents the network from overfitting. In this work, we introduce the gradient gap deviation and the gradient deflection as statistical measures corresponding to the network curvature and the Hessian matrix to analyze variations of network derivatives with respect to input parameters, and investigate how implicit regularization works in ReLU neural networks from both theoretical and empirical perspectives. Our result reveals that the network output between each pair of input samples is properly controlled by random initialization and stochastic gradient descent to keep interpolating between samples almost straight, which results in low complexity of over-parameterized neural networks.
Genetic Evidence for the Association between Schizophrenia and Breast Cancer

Objective: To estimate the potential effect of schizophrenia on breast cancer risk in women, we performed a two-sample Mendelian randomization (MR) study. Methods: The instrumental variables comprised 170 uncorrelated and non-pleiotropic single nucleotide polymorphisms (SNPs) that are significantly associated with schizophrenia risk in genome-wide association studies in 105,000 European descent individuals of the Psychiatric Genomics Consortium (http://www.med.unc.edu/pgc/) and the United Kingdom Clozapine Clinic. The association between these SNPs determined schizophrenia and breast cancer risk was estimated in approximately 229,000 European descent females from the Breast Cancer Association Consortium using the inverse-variance weighted and the weighted median MR methods. Results: We found that the genetically-predicted risk of schizophrenia was associated with increased breast cancer risk (under a random-effects model: odds ratio per 1 unit increase in log odds of schizophrenia = 1.04, 95% confidence interval: 1.02–1.06, p = 5.6 × 10−5). Similar significant associations were observed in analyses using a weighted median model and sensitivity analysis excluding six SNPs with genotype imputation score of less than 0.8, as well as analyses stratified by estrogen receptor status of breast cancer. Conclusion: Our findings implicate a modest increased risk for breast cancer in genetically determined schizophrenic females.
Effects of Thioflavin T and GSK-3 Inhibition on Lifespan and Motility in a Caenorhabditis elegans Model of Tauopathy

The nematode Caenorhabditis elegans (C. elegans) is a powerful model organism to study lifespan and aging, protein aggregation, and neurodegeneration, as well as to carry out drug screenings. The C. elegans strain aex-3/T337 expresses human pathogenic V337M mutant tau under a pan-neuronal promoter and presents uncoordinated locomotion, accumulation of phosphorylated insoluble tau, and shortened lifespan. Herein we have used this strain to assay two compounds that could affect tau aggregation and/or phosphorylation, and looked for phenotypic changes in their lifespan and motility. The first compound is Thioflavin T (ThT), a member of the tetracycline family with protein antiaggregant properties, yet to be tested in a tauopathy model. The second is a novel small molecule, NP103, a highly selective inhibitor of glycogen synthase kinase-3 (GSK-3), the main kinase contributing to pathogenic tau hyperphosphorylation. Importantly, we find that ThT extends lifespan of aex-3/T337 worms as it does with control N2 animals, showing both strains similar locomotion features under this treatment. By contrast, NP103 improves the paralysis phenotype of aex-3/T337 mutants but not their lifespan. Our results show that both treatments present beneficial effects for this model of tauopathy and encourage pursuing further investigations on their therapeutic potential for AD and other tauopathies.
Machine-learning approach to the design of OSDAs for zeolite beta

Significance Zeolite beta is one of the top-six zeolites of commercial interest. It has been synthesized through the use of a number of organic structure directing agents (OSDAs). Pure zeolite beta A has not yet been synthesized, nor has chiral zeolite beta A. We here report a machine-learning strategy to aid the computational design of chemically synthesizable OSDAs for zeolite beta A. The use of machine learning speeds up the computation by a factor of 350. Through de novo materials design runs, a total of 3,062 promising OSDAs were identified, and 469 OSDAs were computed to stabilize the structure of zeolite beta A better than known compounds. We report a machine-learning strategy for design of organic structure directing agents (OSDAs) for zeolite beta. We use machine learning to replace a computationally expensive molecular dynamics evaluation of the stabilization energy of the OSDA inside zeolite beta with a neural network prediction. We train the neural network on 4,781 candidate OSDAs, spanning a range of stabilization energies. We find that the stabilization energies predicted by the neural network are highly correlated with the molecular dynamics computations. We further find that the evolutionary design algorithm samples the space of chemically feasible OSDAs thoroughly. In total, we find 469 OSDAs with verified stabilization energies below −17 kJ/(mol Si), comparable to or better than known OSDAs for zeolite beta, and greatly expanding our previous list of 152 such predicted OSDAs. We expect that these OSDAs will lead to syntheses of zeolite beta.
TarSynFlow, a workflow for bacterial genome comparisons that revealed genes putatively involved in the probiotic character of Shewanella putrefaciens strain Pdp11

Probiotic microorganisms are of great interest in clinical, livestock and aquaculture. Knowledge of the genomic basis of probiotic characteristics can be a useful tool to understand why some strains can be pathogenic while others are probiotic in the same species. An automatized workflow called TarSynFlow (Targeted Synteny Workflow) has been then developed to compare finished or draft bacterial genomes based on a set of proteins. When used to analyze the finished genome of the probiotic strain Pdp11 of Shewanella putrefaciens and genome drafts from seven known non-probiotic strains of the same species obtained in this work, 15 genes were found exclusive of Pdp11. Their presence was confirmed by PCR using Pdp11-specific primers. Functional inspection of the 15 genes allowed us to hypothesize that Pdp11 underwent genome rearrangements spurred by plasmids and mobile elements. As a result, Pdp11 presents specific proteins for gut colonization, bile salt resistance and gut pathogen adhesion inhibition, which can explain some probiotic features of Pdp11.
Engineered resistance to Zika virus in transgenic Aedes aegypti expressing a polycistronic cluster of synthetic small RNAs

Significance Here, we describe the generation of Aedes aegypti mosquitoes that are engineered to be resistant to Zika virus (ZIKV) transmission. Our results demonstrate that engineered mosquitoes express a polycistronic cluster of synthetic small RNAs designed to target the ZIKV genome. As a result, homozygous mosquitoes were refractory to ZIKV infection, and therefore could not transmit the virus. Additionally, mosquitoes heterozygous for the transgene showed significantly lower levels of viral infection, dissemination, and transmission compared with wild-type mosquitoes; importantly, these levels were low enough to make such mosquitoes unlikely to transmit ZIKV to a susceptible host. Finally, we discuss how such an engineering approach can be used to combat the major health burden of ZIKV, and potentially other arboviruses, in the future. Recent Zika virus (ZIKV) outbreaks have highlighted the necessity for development of novel vector control strategies to combat arboviral transmission, including genetic versions of the sterile insect technique, artificial infection with Wolbachia to reduce population size and/or vectoring competency, and gene drive-based methods. Here, we describe the development of mosquitoes synthetically engineered to impede vector competence to ZIKV. We demonstrate that a polycistronic cluster of engineered synthetic small RNAs targeting ZIKV is expressed and fully processed in Aedes aegypti, ensuring the formation of mature synthetic small RNAs in the midgut where ZIKV resides in the early stages of infection. Critically, we demonstrate that engineered Ae. aegypti mosquitoes harboring the anti-ZIKV transgene have significantly reduced viral infection, dissemination, and transmission rates of ZIKV. Taken together, these compelling results provide a promising path forward for development of effective genetic-based ZIKV control strategies, which could potentially be extended to curtail other arboviruses.
Quantitative heterodonty in Crocodylia: assessing size and shape across modern and extinct taxa

Heterodonty in Crocodylia and closely related taxa has not been defined quantitatively, as the teeth rarely have been measured. This has resulted in a range of qualitative descriptors, with little consensus on the condition of dental morphology in the clade. The purpose of this study is to present a method for the quantification of both size- and shape-heterodonty in members of Crocodylia. Data were collected from dry skeletal and fossil specimens of 34 crown crocodylians and one crocodyliform, resulting in 21 species total. Digital photographs were taken of each tooth and the skull, and the margins of both were converted into landmarks and semilandmarks. We expressed heterodonty through Foote’s morphological disparity, and a principal components analysis quantified shape variance. All specimens sampled were heterodont to varying degrees, with the majority of the shape variance represented by a ‘caniniform’ to ‘molariform’ transition. Heterodonty varied significantly between positions; size undulated whereas shape was significantly linear from mesial to distal. Size and shape appeared to be primarily decoupled. Skull shape correlated significantly with tooth shape. High size-heterodonty often correlated with relatively large caniniform teeth, reflecting a prioritization of securing prey. Large, highly molariform, distal teeth may be a consequence of high-frequency durophagy combined with prey size. The slender-snouted skull shape correlated with a caniniform arcade with low heterodonty. This was reminiscent of other underwater-feeding tetrapods, as they often focus on small prey that requires minimal processing. Several extinct taxa were very molariform, which was associated with low heterodonty. The terrestrial peirosaurid shared similarities with large modern crocodylian taxa, but may have processed prey differently. Disparity measures can be inflated or deflated if certain teeth are absent from the tooth row, and regression analysis may not best apply to strongly slender-snouted taxa. Nevertheless, when these methods are used in tandem they can give a complete picture of crocodylian heterodonty. Future researchers may apply our proposed method to most crocodylian specimens with an intact enough tooth row regardless of age, species, or rearing conditions, as this will add rigor to many life history studies of the clade.
STAT1-mediated inhibition of FOXM1 enhances gemcitabine sensitivity in pancreatic cancer

Forkhead box protein M1 (FOXM1) was identified as an oncogenic transcription factor and master regulator of tumor progression and metastasis. FOXM1 expression often correlates with poor prognosis and chemotherapy resistance. In the present study, we investigated the association of FOXM1 expression and chemoresistance in pancreatic cancer. Elevated FOXM1 protein levels were associated with gemcitabine chemoresistance in patients with pancreatic cancer. In gemcitabine resistance cell line models of pancreatic cancer, FOXM1 expression increased, which induced gemcitabine chemoresistance in vitro. In pancreatic cancer cells treated with gemcitabine, FOXM1 affected nuclear factor κB (NF-κB) signaling activity. Immunohistochemical analysis demonstrated a negative association of FOXM1 expression and the level of phosphorylated signal transducer and activator of transcription 1 (pSTAT1) in human pancreatic cancer tissues. Dual-luciferase reporter assays and chromatin-immunoprecipitation assays demonstrated that pSTAT1 directly binds to the FOXM1 promoter to down-regulate its transcription. Interferon γ (IFNγ) promoted gemcitabine-induced cell apoptosis and inhibited cell proliferation in vitro and in vivo by FOXM1 inhibition. These data suggested that FOXM1 enhances chemoresistance to gemcitabine in pancreatic cancer. IFNγ could be used to down-regulate the expression of FOXM1 through STAT1 phosphorylation, thereby increasing the sensitivity of pancreatic cancer cells to gemcitabine. These studies suggested the sensitization by IFNγ in pancreatic ductal adenocarcinoma (PDAC) chemotherapy, which requires further clinical studies.
Conservation Conundrum: At-risk Bumble Bees (Bombus spp.) Show Preference for Invasive Tufted Vetch (Vicia cracca) While Foraging in Protected Areas

Abstract In recent decades, some bumble bee species have declined, including in North America. Declines have been reported in species of bumble bees historically present in Ontario, including: yellow bumble bee (Bombus fervidus) (Fabricus, 1798), American bumble bee (Bombus pensylvanicus) (DeGeer, 1773), and yellow-banded bumble bee (Bombus terricola) (Kirby, 1837). Threats contributing to bumble bee population declines include: land-use changes, habitat loss, climate change, pathogen spillover, and pesticide use. A response to the need for action on pollinator preservation in North America has been to encourage ‘bee-friendly’ plantings. Previous studies show differences in common and at-risk bumble bee foraging; however, similar data are unavailable for Ontario. Our research question is whether there is a difference in co-occurring at-risk and common bumble bee (Bombus spp.) floral use (including nectar and pollen collection) in protected areas in southern Ontario. We hypothesize that common and at-risk species forage differently, predicting that at-risk species forage on a limited selection of host plants. We conducted a field survey of sites in southern Ontario, using observational methods to determine bumble bee foraging by species. The results of a redundancy analysis show a difference in foraging between common and at-risk bumblebee species. At-risk bumble bee species show a preference for foraging on invasive, naturalized Vicia cracca (tufted vetch). This finding raises the question of how to preserve or provide forage for at-risk bumble bees, when they show an association with an invasive species often subject to control in protected areas.
Human complement factor H Y402H polymorphism causes an age-related macular degeneration phenotype and lipoprotein dysregulation in mice

Significance The complement factor H (CFH) Y402H polymorphism (rs1061170) imparts the strongest risk for age-related macular degeneration (AMD), the leading cause of blindness in the elderly. Popular thinking holds that the CFH H402 variant increases complement activation in the eye, predisposing susceptibility to disease. However, clinical trials of complement inhibitors in AMD patients have failed. Here we provide an explanation, showing CFH variant-specific differences in the presentation of AMD-like pathologies. We show that aged mice expressing the human H402, but not Y402 variant, (i) develop AMD-like symptoms and (ii) display differences in their systemic and ocular lipoprotein levels, but not in their complement activation, after diet. These findings support targeting lipoproteins for the treatment of AMD. One of the strongest susceptibility genes for age-related macular degeneration (AMD) is complement factor H (CFH); however, its impact on AMD pathobiology remains unresolved. Here, the effect of the principal AMD-risk–associated CFH variant (Y402H) on the development and progression of age-dependent AMD-like pathologies was determined in vivo. Transgenic mice expressing equal amounts of the full-length normal human CFH Y402 (CFH-Y/0) or the AMD-risk associated CFH H402 (CFH-H/H) variant on a Cfh−/− background were aged to 90 weeks and switched from normal diet (ND) to a high fat, cholesterol-enriched (HFC) diet for 8 weeks. The resulting phenotype was compared with age-matched controls maintained on ND. Remarkably, an AMD-like phenotype consisting of vision loss, increased retinal pigmented epithelium (RPE) stress, and increased basal laminar deposits was detected only in aged CFH-H/H mice following the HFC diet. These changes were not observed in aged CFH-Y/0 mice or in younger (36- to 40-week-old) CFH mice of both genotypes fed either diet. Biochemical analyses of aged CFH mice after HFC diet revealed genotype-dependent changes in plasma and eyecup lipoproteins, but not complement activation, which correlated with the AMD-like phenotype in old CFH-H/H mice. Specifically, apolipoproteins B48 and A1 are elevated in the RPE/choroid of the aged CFH-H/H mice compared with age-matched control CFH-Y/0 fed a HFC diet. Hence, we demonstrate a functional consequence of the Y402H polymorphism in vivo, which promotes AMD-like pathology development and affects lipoprotein levels in aged mice. These findings support targeting lipoproteins as a viable therapeutic strategy for treating AMD.
Pilot Study on the Effect of Orally Administered Bisphenol A on Glucose and Insulin Response in Nonobese Adults

Abstract Objective To determine the effects of varying doses of orally administered BPA on indices of glucose metabolism. Methods Eleven college students (21.0 ± 0.8 years; 24.2 ± 3.9 kg/m2) were randomized in a double-blinded, crossover fashion separated by >1 week to placebo (PL), deuterated BPA at 4 µg/kg body weight (BPA-4), and deuterated BPA at 50 µg/kg body weight (BPA-50). Total BPA, glucose, insulin, and C-peptide were assessed at baseline, minutes 15, 30, 45, 60, and every 30 minutes for 2 hours in response to a glucose tolerance test. Results There was a significant condition × time interaction for total BPA (P < 0.001) such that BPA increased more rapidly in BPA-50 than BPA-4 and PL (P = 0.003) and increased more rapidly in BPA-4 than PL (P < 0.001). There were no significant condition × time interactions on glucose, insulin, and C-peptide. Significant condition main effects were observed for glucose such that BPA-50 was significantly lower than PL (P = 0.036) and nearly lower for BPA-4 vs PL (P = 0.056). Significant condition main effects were observed such that insulin in BPA-50 was lower than BPA-4 (P = 0.021), and C-peptide in BPA-50 was lower than BPA-4 (t18 = 3.95; Tukey-adjusted P = 0.003). Glucose, insulin, and C-peptide areas under the curve for the 3-hour profile were significantly lower in BPA-50 vs PL (P < 0.05). Conclusion Orally administered BPA protocol appeared feasible and has immediate effects on glucose, insulin, and C-peptide concentrations.
Cold sensing by NaV1.8-positive and NaV1.8-negative sensory neurons

Significance The cellular correlate for cold sensing has been ascribed to either Trpm8-expressing or NaV1.8-expressing neurons. Importantly, transcriptomic analysis shows that these neuronal populations are nonoverlapping. Using in vivo GCaMP imaging in live mice we show that the vast majority of acute cold-sensing neurons activated at ≥1 °C do not express NaV1.8, and that the loss of NaV1.8 does not affect acute cold-sensing behavior in mice. Instead, we show that cold-responding neurons are enriched with Trpm8 as well as numerous potassium channels, including Kcnk9. By contrast, NaV1.8-positive neurons signal prolonged extreme cold. These observations highlight the complexity of cold sensing in DRG neurons, and the role of NaV1.8-negative neurons in cold sensing down to 1 °C. The ability to detect environmental cold serves as an important survival tool. The sodium channels NaV1.8 and NaV1.9, as well as the TRP channel Trpm8, have been shown to contribute to cold sensation in mice. Surprisingly, transcriptional profiling shows that NaV1.8/NaV1.9 and Trpm8 are expressed in nonoverlapping neuronal populations. Here we have used in vivo GCaMP3 imaging to identify cold-sensing populations of sensory neurons in live mice. We find that ∼80% of neurons responsive to cold down to 1 °C do not express NaV1.8, and that the genetic deletion of NaV1.8 does not affect the relative number, distribution, or maximal response of cold-sensitive neurons. Furthermore, the deletion of NaV1.8 had no observable effect on transient cold-induced (≥5 °C) behaviors in mice, as measured by the cold-plantar, cold-plate (5 and 10 °C), or acetone tests. In contrast, nocifensive-like behavior to extreme cold-plate stimulation (−5 °C) was completely absent in mice lacking NaV1.8. Fluorescence-activated cell sorting (FACS) and subsequent microarray analysis of sensory neurons activated at 4 °C identified an enriched repertoire of ion channels, which include the Trp channel Trpm8 and potassium channel Kcnk9, that are potentially required for cold sensing above freezing temperatures in mouse DRG neurons. These data demonstrate the complexity of cold-sensing mechanisms in mouse sensory neurons, revealing a principal role for NaV1.8-negative neurons in sensing both innocuous and acute noxious cooling down to 1 °C, while NaV1.8-positive neurons are likely responsible for the transduction of prolonged extreme cold temperatures, where tissue damage causes pan-nociceptor activation.
Programmed conversion of hypertrophic chondrocytes into osteoblasts and marrow adipocytes within zebrafish bones

Much of the vertebrate skeleton develops from cartilage templates that are progressively remodeled into bone. Lineage tracing studies in mouse suggest that chondrocytes within these templates persist and become osteoblasts, yet the underlying mechanisms of this process and whether chondrocytes can generate other derivatives remain unclear. We find that zebrafish cartilages undergo extensive remodeling and vascularization during juvenile stages to generate fat-filled bones. Growth plate chondrocytes marked by sox10 and col2a1a contribute to osteoblasts, marrow adipocytes, and mesenchymal cells within adult bones. At the edge of the hypertrophic zone, chondrocytes re-enter the cell cycle and express leptin receptor (lepr), suggesting conversion into progenitors. Further, mutation of matrix metalloproteinase 9 (mmp9) results in delayed growth plate remodeling and fewer marrow adipocytes. Our data support Mmp9-dependent growth plate remodeling and conversion of chondrocytes into osteoblasts and marrow adipocytes as conserved features of bony vertebrates.