ConvFormer: Revisiting Transformer for Sequential User Modeling

Sequential user modeling, a critical task in personalized recommender systems, focuses on predicting the next item a user would prefer, requiring a deep understanding of user behavior sequences. Despite the remarkable success of Transformer-based models across various domains, their full potential in comprehending user behavior remains untapped. In this paper, we re-examine Transformer-like architectures aiming to advance state-of-the-art performance. We start by revisiting the core building blocks of Transformer-based methods, analyzing the effectiveness of the item-to-item mechanism within the context of sequential user modeling. After conducting a thorough experimental analysis, we identify three essential criteria for devising efficient sequential user models, which we hope will serve as practical guidelines to inspire and shape future designs. Following this, we introduce ConvFormer, a simple but powerful modification to the Transformer architecture that meets these criteria, yielding state-of-the-art results. Additionally, we present an acceleration technique to minimize the complexity associated with processing extremely long sequences. Experiments on four public datasets showcase ConvFormer's superiority and confirm the validity of our proposed criteria

Transcriptome profiling of A549 non-small cell lung cancer cells in response to Trichinella spiralis muscle larvae excretory/secretory products

Trichinella spiralis (T. spiralis) muscle-larva excretory/secretory products (ML-ESPs) is a complex array of proteins with antitumor activity. We previously demonstrated that ML-ESPs inhibit the proliferation of A549 non-small cell lung cancer (NSCLC) cell line. However, the mechanism of ML-ESPs against A549 cells, especially on the transcriptional level, remains unknow. In this study, we systematically investigated a global profile bioinformatics analysis of transcriptional response of A549 cells treated with ML-ESPs. And then, we further explored the transcriptional regulation of genes related to glucose metabolism in A549 cells by ML-ESPs. The results showed that ML-ESPs altered the expression of 2,860 genes (1,634 upregulated and 1,226 downregulated). GO and KEGG analysis demonstrated that differentially expressed genes (DEGs) were mainly associated with pathway in cancer and metabolic process. The downregulated genes interaction network of metabolic process is mainly associated with glucose metabolism. Furthermore, the expression of phosphofructokinase muscle (PFKM), phosphofructokinase liver (PFKL), enolase 2 (ENO2), lactate dehydrogenase B (LDHB), 6-phosphogluconolactonase (6PGL), ribulose-phosphate-3-epimerase (PRE), transketolase (TKT), transaldolase 1 (TALDO1), which genes mainly regulate glycolysis and pentose phosphate pathway (PPP), were suppressed by ML-ESPs. Interestingly, tricarboxylic acid cycle (TCA)-related genes, such as pyruvate dehydrogenase phosphatase 1 (PDP1), PDP2, aconitate hydratase 1 (ACO1) and oxoglutarate dehydrogenase (OGDH) were upregulated by ML-ESPs. In summary, the transcriptome profiling of A549 cells were significantly altered by ML-ESPs. And we also provide new insight into how ML-ESPs induced a transcriptional reprogramming of glucose metabolism-related genes in A549 cells

Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease

Abstract Background The absence of distinct symptoms in the majority of individuals with metabolic dysfunction-associated fatty liver disease (MAFLD) poses challenges in identifying those at high risk, so we need simple, efficient and cost-effective noninvasive scores to aid healthcare professionals in patient identification. While most noninvasive scores were developed for the diagnosis of nonalcoholic fatty liver disease (NAFLD), consequently, the objective of this study was to systematically assess the diagnostic ability of 12 noninvasive scores (METS-IR/TyG/TyG-WC/TyG-BMI/TyG-WtHR/VAI/HSI/FLI/ZJU/FSI/K-NAFLD) for MAFLD. Methods The study recruited eligible participants from two sources: the National Health and Nutrition Examination Survey (NHANES) 2017-2020.3 cycle and the database of the West China Hospital Health Management Center. The performance of the model was assessed using various metrics, including area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), decision curve analysis (DCA), and subgroup analysis. Results A total of 7398 participants from the NHANES cohort and 4880 patients from the Western China cohort were included. TyG-WC had the best predictive power for MAFLD risk in the NHANES cohort (AUC 0.863, 95% CI 0.855–0.871), while TyG-BMI had the best predictive ability in the Western China cohort (AUC 0.903, 95% CI 0.895–0.911), outperforming other models, and in terms of IDI, NRI, DCA, and subgroup analysis combined, TyG-WC remained superior in the NAHANES cohort and TyG-BMI in the Western China cohort. Conclusions TyG-BMI demonstrated satisfactory diagnostic efficacy in identifying individuals at a heightened risk of MAFLD in Western China. Conversely, TyG-WC exhibited the best diagnostic performance for MAFLD risk recognition in the United States population. These findings suggest the necessity of selecting the most suitable predictive models based on regional and ethnic variations

Experimental Study of Water Vapor Adsorption on Bare Soil and Gravel Surfaces in an Arid Region of Ningxia, China

Water vapor adsorption on soil, a crucial non-rainfall water resource in arid regions, warrants further experimental investigation, particularly on two typical land surfaces: bare soil and gravel. This study examined the formation characteristics and influencing factors of vapor adsorption in an arid region of Northwestern China. Observations and analyses were conducted on adsorption and evaporation measurements taken by two small weighing lysimeters (SLSs); soil temperature at a depth of 5 cm; surface temperature; relative humidity; and air temperature at a height of 30 cm above the ground from 2019 to 2020. The adsorbed water in this area was more abundant at night and less abundant during the day, with a stable nightly adsorption rate of 0.013 mm/h. Adsorption was more frequent in spring and winter (from January to June and November to December), accounting for about 90% of the total annual adsorption. In 2019 and 2020, the ratio values of adsorption to evaporation were 0.16 and 0.10 for bare soil, and 0.10 and 0.12 for gravel, respectively. Adsorption was more likely to occur when the soil moisture content was less than 13%; the highest adsorption frequency was close to 20% when the RH was between 75 and 95%; low soil temperatures were more conducive to the occurrence of adsorption. The effect of temperature differences (Ta−Ts) on adsorption was stronger than that of relative humidity. The adsorption frequency generally showed a bimodal change with increasing temperature difference, but the effect of temperature differences was less effective for gravel than bare soil. When the relative humidity was high and the temperature difference was weakly positive, the maximum adsorption intensity could reach 0.18 mm/h

Chiral Quasi-Bound States in the Continuum of a Dielectric Metasurface for Optical Monitoring and Temperature Sensing

Chiral BIC can reach ultrahigh quality factors (Q-factor) based on its asymmetry, with broken mirror symmetries and in-plane inversion. Only by in-plane structural perturbation can chiral quasi-BIC (q-BIC) appear, so it is much more realizable and reasonable for the manufacturers in practical productions and fabrications considering the technology and means that are available. In this paper, we design a new dielectric metasurface employing H-shaped silica meta-atoms in the lattice, which is symmetrical in structure, obtaining chiral BIC with ultrahigh Q-factor (exceeding 105). In this process, we change the length of the limbs of the structure to observe the specific BICs. Previous scholars have focused on near-infrared-wavelength bands, while we concentrate on the terahertz wavelength band (0.8–1 THz). We found that there is more than one BIC, thus realizing multiple BICs in the same structure; all of them exhibit excellent circular dichroism (CD) (the maximum value of CD is up to 0.8127) for reflectance and transmittance, which provides significant and unique guidance for the design of multi-sensors. Meanwhile, we performed temperature sensing with chiral BIC; the sensitivity for temperature sensing can reach 13.5 nm/°C, which exhibits high accuracy in measuring temperature. As a consequence, the result proposed in this study will make some contributions to advanced optical imaging, chiral sensors with high frequency and spectral resolution, optical monitoring of environmental water quality, multiple sensors, temperature sensing, biosensing, substance inspection and ambient monitoring and other relevant optical applications

Responses of soil nitrogen cycling to changes in aboveground plant litter inputs: A meta-analysis

Alterations in aboveground plant litter inputs due to global climate change can strongly change soil nitrogen (N) cycling, which will influence soil processes and functions. However, a comprehensive evaluation for the effects of altered litter inputs on soil N cycling is not available. We evaluated these effects using a global meta-analysis based on 1829 observations from 119 studies across different ecosystems including forests, shrublands and grasslands. Results showed that litter addition significantly increased soil N pools including total N (TN), dissolved organic N (DON), ammonium (NH4+), nitrate (NO3–) and microbial biomass N (MBN) by 4–––24 %, while litter removal decreased them by 10–––42 %. High initial soil TN pool weakened the positive effect of litter addition on soil TN. Moreover, litter addition significantly increased soil net N mineralization (+19 %), DON leaching (+56 %) and nitrous oxide (N2O) emission (+27 %), whereas litter removal reduced net N mineralization (-10 %) and increased NO3– leaching (+51 %). The response of soil net N mineralization to litter addition was stronger in broadleaved forests than that in coniferous forests, and negatively correlated with mean annual temperature and precipitation. The responses of soil TN, NH4+, NO3–, MBN and N2O emission to litter manipulation increased with increasing litter input rates. Therefore, altered litter inputs had strong effects on soil N cycling and these effects were regulated by soil N status, ecosystems, climates and experimental conditions. Our results provide insights into understanding how altered plant litter input affects soil N cycling and help better assess the soil processes under global climate change

Integrated profiling identifies ferredoxin 1 as an immune-related biomarker of malignant phenotype in glioma

Background: Glioma, a highly resistant and recurrent type of central nervous system tumor, poses a significant challenge in terms of effective drug treatments and its associated mortality rates. Despite the discovery of Ferredoxin 1 (FDX1) as a crucial participant in cuproptosis, an innovative mechanism of cellular demise, its precise implications for glioma prognosis and tumor immune infiltration remain inadequately elucidated. Methods: To analyze pan-cancer data, we employed multiple public databases. Gene expression evaluation was performed using tissue microarray (TMA) and single-cell sequencing data. Furthermore, four different approaches were employed to assess the prognostic importance of FDX1 in glioma. We conducted the analysis of differential expression genes (DEGs) and Gene Set Enrichment Analysis (GSEA) to identify immune-related predictive signaling pathways. Somatic mutations were assessed using Tumor Mutation Burden (TMB) and waterfall plots. Immune cell infiltration was evaluated with five different algorithms. Furthermore, we performed in vitro investigations to evaluate the biological roles of FDX1 in glioma. Results: Glioma samples exhibited upregulation of FDX1, which in turn predicted poor prognosis and was positively associated with unfavorable clinicopathological characteristics. Notably, the top four enriched signaling pathways were immune-related, and the discovery revealed a connection between the expression of FDX1 and the frequency of mutations or the TMB. The FDX1_high group exhibited heightened infiltration of immune cells, and there existed a direct association between the expression of FDX1 and the regulation of immune checkpoint. In vitro experiments demonstrated that FDX1 knockdown reduced proliferation, migration, invasion and transition from G2 to M phase in glioma cells. Conclusion: In glioma, FDX1 demonstrated a positive association with the advancement of malignancy and changes in the infiltration of immune cells