Sequential Recommendation with Diffusion Models

Generative models, such as Variational Auto-Encoder (VAE) and Generative Adversarial Network (GAN), have been successfully applied in sequential recommendation. These methods require sampling from probability distributions and adopt auxiliary loss functions to optimize the model, which can capture the uncertainty of user behaviors and alleviate exposure bias. However, existing generative models still suffer from the posterior collapse problem or the model collapse problem, thus limiting their applications in sequential recommendation. To tackle the challenges mentioned above, we leverage a new paradigm of the generative models, i.e., diffusion models, and present sequential recommendation with diffusion models (DiffRec), which can avoid the issues of VAE- and GAN-based models and show better performance. While diffusion models are originally proposed to process continuous image data, we design an additional transition in the forward process together with a transition in the reverse process to enable the processing of the discrete recommendation data. We also design a different noising strategy that only noises the target item instead of the whole sequence, which is more suitable for sequential recommendation. Based on the modified diffusion process, we derive the objective function of our framework using a simplification technique and design a denoise sequential recommender to fulfill the objective function. As the lengthened diffusion steps substantially increase the time complexity, we propose an efficient training strategy and an efficient inference strategy to reduce training and inference cost and improve recommendation diversity. Extensive experiment results on three public benchmark datasets verify the effectiveness of our approach and show that DiffRec outperforms the state-of-the-art sequential recommendation models

Frequency Enhanced Hybrid Attention Network for Sequential Recommendation

The self-attention mechanism, which equips with a strong capability of modeling long-range dependencies, is one of the extensively used techniques in the sequential recommendation field. However, many recent studies represent that current self-attention based models are low-pass filters and are inadequate to capture high-frequency information. Furthermore, since the items in the user behaviors are intertwined with each other, these models are incomplete to distinguish the inherent periodicity obscured in the time domain. In this work, we shift the perspective to the frequency domain, and propose a novel Frequency Enhanced Hybrid Attention Network for Sequential Recommendation, namely FEARec. In this model, we firstly improve the original time domain self-attention in the frequency domain with a ramp structure to make both low-frequency and high-frequency information could be explicitly learned in our approach. Moreover, we additionally design a similar attention mechanism via auto-correlation in the frequency domain to capture the periodic characteristics and fuse the time and frequency level attention in a union model. Finally, both contrastive learning and frequency regularization are utilized to ensure that multiple views are aligned in both the time domain and frequency domain. Extensive experiments conducted on four widely used benchmark datasets demonstrate that the proposed model performs significantly better than the state-of-the-art approaches.Comment: 11 pages, 7 figures, The 46th International ACM SIGIR Conference on Research and Development in Information Retrieva

Metagenomic next-generation sequencing shotgun for the diagnosis of infection in connective tissue diseases: A retrospective study

ObjectivePatients with connective tissue diseases (CTDs) are at high risk of infection due to various reasons. The purpose of the study was to investigate the infection diagnosis value of metagenomic next-generation sequencing (mNGS) shotgun in CTDs to guide the use of anti-infective therapy more quickly and accurately.MethodsIn this retrospective study, a total of 103 patients with CTDs admitted with suspected infection between December 2018 and September 2021 were assessed using mNGS as well as conventional microbiological tests (CMT).ResultsAmong these 103 patients, 65 were confirmed to have an infection (Group I) and 38 had no infection (Group II). mNGS reached a sensitivity of 92.31% in diagnosing pathogens in Group I. Moreover, mNGS showed good performance in identifying mixed infection. In all infection types, lung infection was the most common. mNGS also played an important role in detecting Pneumocystis jirovecii, which was associated with low CD4+ T-cell counts inextricably.ConclusionmNGS is a useful tool with outstanding diagnostic potential in identifying pathogens in patients with CTDs and conduce to provide guidance in clinical practice

Diversity patterns and conservation gaps of Magnoliaceae species in China

Postponed access: the file will be available after 2023-12-27Magnoliaceae, a primitive group of angiosperms and distinguished ornamental plants with more than 100 species in China, is one of the most threatened plant family in the wild due to logging, habitat loss, over-collection and climate change. To provide a scientific guide of its conservation for policymakers, we explore the diversity patterns of 114 Magnoliaceae species in China using three diversity indices (species richness, weighted endemism, β-diversity) with a spatial resolution of 10 km by 10 km. Two methods, the top 5% richness algorithm and complementary algorithm, are used to identify diversity hotspots. Conservation gaps are recognized by overlapping the diversity hotspots with Chinese nature reserves. Our results indicate that Magnoliaceae species richness and weighted endemism are high in tropical to subtropical low montane forests in southern China, exceptionally high in southernmost Yunnan and boundary of Guizhou, Guangxi and Hunan. The β-diversity are scattered in southern China, suggesting a different species composition among grid cells. We identify 2524 grids as diversity hotspots for Magnoliaceae species in China, with 24 grids covered by three diversity indices (first-level diversity hotspots), 561 grids covered by two indices (second-level diversity hotspots) simultaneously and 1939 grids (76.8%) covered by only one index (third-level diversity hotspots). The first-level diversity hotspots include over 70% of the critically endangered Magnoliaceae species and are the priority areas for Magnoliaceae conservation. However, only 24% of the diversity hotspots fall in nature reserves and only ten grids are from the first-level diversity hotspots. Zhejiang, Guizhou and Fujian have less than 20% of diversity hotspots covered by nature reserves and need attention in future Magnoliaceae conservation. Using multiple diversity indices and algorithms, our study identifies diversity hotspots and conservation gaps and provides scientific basis for Magnoliaceae conservation in future.acceptedVersio

Boosting the Electron Beam Transmittance of Field Emission Cathode Using a Self-Charging Gate

The gate-type carbon nanotubes cathodes exhibit advantages in long-term stable emission owing to the uniformity of electrical field on the carbon nanotubes, but the gate inevitably reduces the transmittance of electron beam, posing challenges for system stabilities. In this work, we introduce electron beam focusing technique using the self-charging SiNx/Au/Si gate. The potential of SiNx is measured to be approximately −60 V quickly after the cathode turning on, the negative potential can be maintained as the emission goes on. The charged surface generates rebounding electrostatic forces on the following electrons, significantly focusing the electron beam on the center of gate hole and allowing them to pass through gate with minimal interceptions. An average transmittance of 96.17% is observed during 550 hours prototype test, the transmittance above 95% is recorded for the cathode current from 2.14 μA to 3.25 mA with the current density up to 17.54 mA cm−2

Effect of ghrelin gene knockout on the postsynaptic potential of dopaminergic neurons in the substantia nigra of mice

Objective To study the effect of ghrelin gene knockout on the postsynaptic potential of dopaminergic neurons in the substantia nigra of mice. Methods Substantia nigra tissue was taken from 10-week-old ghrelin-/- male mice (ghrelin-/- group) and their male wild-type (WT) littermates (WT group). RNA-seq technique was used to screen differently expressed genes (DEGs). KEGG pathway enrichment analysis was performed for the neuronal synaptic activity-associated signaling pathways which DEGs might be involved in. Quantitative real-time PCR (RT-qPCR) was used for validation of the identified DEGs, and western blotting was used for protein expression of neuronal synaptic activity-related genes. Results Compared with the WT group, the ghrelin-/- group had significant changes in the expression levels of 23 genes in the synaptic signaling pathway of dopaminergic neurons. Specifically, Ionotropic glutamate receptors α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid type subunit 3 (GluA3) and glycogen synthase kinase3-β (GSK-3β) regulated α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor and N-methyl-D-aspartic acid receptor on the postsynaptic membrane of neurons, respectively. GluA3 and GSK-3β genes were significantly downregulated in the substantia nigra tissue of mice in the ghrelin-/- group. RT-qPCR results showed that compared to the WT group, the ghrelin-/- group had significant downregulation of the mRNA expression levels of GluA3 and GSK-3β in the substantia nigra tissue of mice (t =2.408,2.740,P<0.05). Western blotting results showed that compared with the WT group, the ghrelin-/- group had a significantly upregulated expression level of GluA3 protein (t=2.530,P<0.05) and a significantly downregulated expression level of GSK-3β protein (t=3.469,P<0.05) in the substantia nigra tissue of mice. Conclusion Ghrelin gene knockout may enhance the excitatory synaptic transmission activity by enhancing the postsynaptic potential of substantia nigra dopaminergic neurons in mice for a long time, thus regulating movement

Original Article Sunitinib for patients with locally advanced or distantly metastatic dermatofibrosarcoma protuberans but resistant to imatinib

Abstract: Purpose: This study evaluated the efficacy and adverse effects of Imatinib therapy to advanced Dermatofibrosarcoma protuberan (DFSP) and Sunitinib therapy to advanced Dermatofibrosarcoma protuberan (DFSP) after Imatinib resistance. Methods: We analyzed the efficacy, adverse effects and survival of 95 patients with locally advanced or metastatic DFS

A Wall-Associated Kinase Gene CaWAKL20 From Pepper Negatively Modulates Plant Thermotolerance by Reducing the Expression of ABA-Responsive Genes

Heat stress has become a major threat to crop production due to global warming; however, the mechanisms underlying plant high-temperature sensing are not well known. In plants, the membrane-anchored receptor-like kinases (RLKs) relay environmental signals into the cytoplasm. In a previous study, we isolated a wall-associated RLK-like (WAKL) gene CaWAKL20 from pepper (Capsicum annuum L.). Here, the amino acid sequence of CaWAKL20 was characterized and found to consist of conserved domains of WAK/WAKL family, including an extracellular region containing a GUB-WAK binding domain and a degenerated EGF2-like domain; a transmembrane region; and an intercellular region with an STKc catalytic domain. Moreover, CaWAKL20 transcription was inhibited by heat stress, whereas it was induced by both ABA and H2O2 treatments. Silencing of CaWAKL20 enhanced pepper thermotolerance, while overexpression decreased Arabidopsis thermotolerance. Additionally, Arabidopsis lines overexpressing CaWAKL20 showed less sensitivity to ABA during seed germination and root growth. Finally, the survival rate of Arabidopsis seedlings under heat stress treatment was enhanced by ABA pre-treatment, while it was compromised by the overexpression of CaWAKL20. Furthermore, the heat-induced expression of several ABA-responsive genes and some key regulator genes for thermotolerance was decreased in Arabidopsis CaWAKL20-overexpression lines. These results suggest that CaWAKL20 negatively modulates plant thermotolerance by reducing the expression of ABA-responsive genes, laying a foundation for further investigation into the functional mechanisms of WAKs/WAKLs in plants undergoing environmental stresses

Efficacy and acceptability of anti-inflammatory agents in major depressive disorder: a systematic review and meta-analysis

BackgroundAnti-inflammatory agents have emerged as a potential new therapy for major depressive disorder (MDD). In this meta-analysis, our aim was to evaluate the antidepressant effect of anti-inflammatory agents and compare their efficacy.MethodsWe conducted a comprehensive search across multiple databases, including PubMed, Embase, Web of Science, Cochrane Review, Cochrane Trial, and ClinicalTrials.gov, to identify eligible randomized clinical trials. The primary outcome measures of our meta-analysis were efficacy and acceptability, while the secondary outcome measures focused on remission rate and dropout rate due to adverse events. We used odds ratio (OR) and 95% confidence interval (95% CI) to present our results.ResultsA total of 48 studies were included in our analysis. In terms of efficacy, anti-inflammatory agents demonstrated a significant antidepressant effect compared to placebo (OR = 2.04, 95% CI: 1.41–2.97, p = 0.0002). Subgroup analyses revealed that anti-inflammatory agents also exhibited significant antidepressant effects in the adjunctive therapy subgroup (OR = 2.17, 95% CI: 1.39–3.37, p = 0.0006) and in MDD patients without treatment-resistant depression subgroup (OR = 2.33, 95% CI: 1.53–3.54, p < 0.0001). Based on the surface under the cumulative ranking curve (SUCRA) value of network meta-analysis, nonsteroidal anti-inflammatory drugs (NSAIDs) (SUCRA value = 81.6) demonstrated the highest acceptability among the included anti-inflammatory agents.ConclusionIn summary, our meta-analysis demonstrates that anti-inflammatory agents have significant antidepressant effects and are well-accepted. Furthermore, adjunctive therapy with anti-inflammatory agents proved effective in treating MDD. Among the evaluated anti-inflammatory agents, NSAIDs exhibited the highest acceptability, although its efficacy is comparable to placebo.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=422004), identifier CRD42023422004