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Recent studies highlight that oceanic motions associated with horizontal scales smaller than 50 km, defined here as submesoscales, lead to anomalous vertical heat fluxes from colder to warmer waters. This unique transport property is not captured in climate models that have insufficient resolution to simulate these submesoscale dynamics. Here, we use an ocean model with an unprecedented resolution that, for the first time, globally resolves submesoscale heat transport. Upper-ocean submesoscale turbulence produces a systematically-upward heat transport that is five times larger than mesoscale heat transport, with winter-time averages up to 100 W/m 2 for mid-latitudes. Compared to a lower-resolution model, submesoscale heat transport warms the sea surface up to 0.3 °C and produces an upward annual-mean air–sea heat flux anomaly of 4–10 W/m 2 at mid-latitudes. These results indicate that submesoscale dynamics are critical to the transport of heat between the ocean interior and the atmosphere, and are thus a key component of the Earth’s climate. Oceanic motions associated with horizontal scales smaller than 50 km remain unresolved in climate models. Here the authors show that motions in this scale range are critical to the global transport of heat between the ocean interior and the atmosphere, and are thus a key component of the Earth’s climate.

Human–object interaction (HOI) detection identifies a “set of interactions” in an image involving the recognition of interacting instances and the classification of interaction categories. The complexity and variety of image content make this task challenging. Recently, the Transformer has been applied in computer vision and received attention in the HOI detection task. Therefore, this paper proposes a novel Part Refinement Tandem Transformer (PRTT) for HOI detection. Unlike the previous Transformer-based HOI method, PRTT utilizes multiple decoders to split and process rich elements of HOI prediction and introduces a new part state feature extraction (PSFE) module to help improve the final interaction category classification. We adopt a novel prior feature integrated cross-attention (PFIC) to utilize the fine-grained partial state semantic and appearance feature output obtained by the PSFE module to guide queries. We validate our method on two public datasets, V-COCO and HICO-DET. Compared to state-of-the-art models, the performance of detecting human–object interaction is significantly improved by the PRTT.

Rating prediction is crucial in recommender systems as it enables personalized recommendations based on different models and techniques, making it of significant theoretical importance and practical value. However, presenting these recommendations in the form of lists raises the challenge of improving the list’s quality, making it a prominent research topic. This study focuses on enhancing the ranking quality of recommended items in user lists while ensuring interpretability. It introduces fuzzy membership functions to measure user attributes on a multi-dimensional item label vector and calculates user similarity based on these features for prediction and recommendation. Additionally, the user similarity network is modeled to extract community information, leading to the design of a set of corresponding recommendation algorithms. Experimental results on two commonly used datasets demonstrate the effectiveness of the proposed algorithm in enhancing list ranking quality, reducing prediction errors, and maintaining recommendation diversity and accurate user preference classification. This research highlights the potential of integrating heuristic methods with complex network theory and fuzzy techniques to enhance recommendation system performance with interpretability in mind.

Slope One algorithm and its descendants measure user-score distance and use the statistical score distance between users to predict unknown ratings, as opposed to the typical collaborative filtering algorithm that uses similarity for neighbor selection and prediction. Compared to collaborative filtering systems that select only similar neighbors, algorithms based on user-score distance typically include all possible related users in the process, which needs more computation time and requires more memory. To improve the scalability and accuracy of distance-based recommendation algorithm, we provide a user-item link prediction approach that combines user distance measurement with similarity-based user selection. The algorithm predicts unknown ratings based on the filtered users by calculating user similarity and removing related users with similarity below a threshold, which reduces 26 to 29 percent of neighbors and improves prediction error, ranking, and prediction accuracy overall.

Background To date, no single colorectal cancer (CRC) screening strategy has been determined to be applicable worldwide. In China, a CRC screening protocol that combines double fecal immunochemical tests (FITs) and a high-risk factor questionnaire (HRFQ) as the first stage of screening and colonoscopy as the second stage of screening (scenario A) was adapted by the Chinese Ministry of Health in 2006. However, applying this CRC screening protocol nationally remains difficult because its effectiveness and convenience are controversial. This study evaluated the effects of subitems of the CRC screening protocol in China. Methods CRC screening results (scenario A) from Jiashan County, China, (2007–2009) were used to analyze the detection rates of CRC and advanced neoplasms as well as the cost-effectiveness of the protocol. Scenario A was divided into scenarios B–G (by selecting some items at the first stage of screening) for analysis. Results Compared with scenario A, removing the whole HRFQ (scenario F) reduced advanced neoplasm and adenoma detections by 29.8 and 41.2%, respectively, whereas the whole HRFQ accounted for 10.1% of the total screening cost. Removing FITs (scenario G) reduced CRC, advanced neoplasm and adenoma detections by 71.8, 56.9 and 47.7%, respectively, and the costs per case of CRC and advanced neoplasm were 82.0 and 19.1% higher, respectively, than those in scenario A. In scenarios B–E (deleting some high-risk factor questions on the HRFQ), the odds ratios (ORs) of the detection rates and costs per CRC, advanced neoplasm, adenoma, and neoplasm case were near 1.00. Scenarios C and D reduced the high-risk population and total screening costs by less than 6.0 and 4.1%, respectively. Scenarios E and B (FITs and a personal history of cancer or colorectal adenoma were reserved) reduced the high-risk population by 17.6 and 24.2% and the total screening costs by 11.2 and 15.4%, respectively, while the numbers of CRC cases were not missed, and advanced neoplasms detected decreased by only 5 and 11%, respectively. Conclusion The results of this study demonstrate that FITs and a personal history of colorectal adenoma are the most effective items in the Chinese CRC screening protocol.

The existing chemo/radiotherapy fail to eliminate cancer cells due to the restriction of either drug resistance or radio tolerance. The predicament urges researchers to continuously explore alternative strategy for achieving a potent curative effect. Functional chlorin gold nanorods (Ce6-AuNR@SiO -d-CPP) were fabricated aiming at treating breast cancer by photothermal/photodynamic therapy (PTT/PDT). The nanostructure was developed by synthesizing Au nanorods as the photothermal conversion material, and by coating the pegylated mesoporous SiO as the shell for entrapping photosensitizer Ce6 and for linking the D-type cell penetrating peptide (d-CPP). The function of Ce6-AuNR@SiO -d-CPP was verified on human breast cancer MCF-7 cells and MCF-7 cells xenografts in nude mice. Under combinational treatment of PTT and PDT, Ce6-AuNR@SiO -d-CPP demonstrated a strong cytotoxicity and apoptosis inducing effects in breast cancer cells in vitro, and a robust treatment efficacy in breast cancer-bearing nude mice. The uptake mechanism involved the energy-consuming caveolin-mediated endocytosis, and Ce6-AuNR@SiO -d-CPP in PTT/PDT mode could induce apoptosis by multiple pathways in breast cancer cells. Ce6-AuNR@SiO -d-CPP demonstrated a robust efficacy in the treatment of breast cancer by photothermal/photodynamic therapy. Therefore, the present study could offer a new promising strategy to treat the refractory breast cancer.

Feeding rates serve as a vital indicator for adjusting the working parameters of the combine harvester. A non-invasive diagnostic approach to predicting the feed rates of combine harvesters by collecting vibration signals of the inclined conveyor was introduced in this study. To establish a feed rate prediction model, the correlation between feeding rates and vibration signal characteristics was investigated. Vibration signal characteristics in both the time domain and frequency domain were also analyzed in detail. The RMS (root mean square) value and the total RMS value of the one-third octave extracted from the vibration signal were utilized to establish a feed rate prediction model, and field tests were conducted to verify the model performance. The experimental results indicated that the relative errors of the established model range from 3.1% to 4.9% when harvesting rice. With the developed feed rate prediction system, the control system of the combine harvester can acquire feed rate information in real time, and the working parameters can be adjusted in advance, thereby, it can be expected to greatly enhance the working performance of the combine harvesters.

Genome-wide association studies are revolutionizing the search for the genes underlying human complex diseases. The main decisions to be made at the design stage of these studies are the choice of the commercial genotyping chip to be used and the numbers of case and control samples to be genotyped. The most common method of comparing different chips is using a measure of coverage, but this fails to properly account for the effects of sample size, the genetic model of the disease, and linkage disequilibrium between SNPs. In this paper, we argue that the statistical power to detect a causative variant should be the major criterion in study design. Because of the complicated pattern of linkage disequilibrium (LD) in the human genome, power cannot be calculated analytically and must instead be assessed by simulation. We describe in detail a method of simulating case-control samples at a set of linked SNPs that replicates the patterns of LD in human populations, and we used it to assess power for a comprehensive set of available genotyping chips. Our results allow us to compare the performance of the chips to detect variants with different effect sizes and allele frequencies, look at how power changes with sample size in different populations or when using multi-marker tags and genotype imputation approaches, and how performance compares to a hypothetical chip that contains every SNP in HapMap. A main conclusion of this study is that marked differences in genome coverage may not translate into appreciable differences in power and that, when taking budgetary considerations into account, the most powerful design may not always correspond to the chip with the highest coverage. We also show that genotype imputation can be used to boost the power of many chips up to the level obtained from a hypothetical \"complete\" chip containing all the SNPs in HapMap. Our results have been encapsulated into an R software package that allows users to design future association studies and our methods provide a framework with which new chip sets can be evaluated.

Neo-adjuvant chemotherapy is an effective strategy for improving treatment of breast cancers. However, the efficacy of this treatment strategy is limited for treatment of triple negative breast cancer (TNBC). Gene therapy may be a more effective strategy for improving the prognosis of TNBC. A novel 25 nucleotide sense strand of miRNA was designed to treat TNBC by silencing the Slug gene, and encapsulated into DSPE-PEG -tLyp-1 peptide-modified functional liposomes. The efficacy of miRNA liposomes was evaluated on invasive TNBC cells and TNBC cancer-bearing nude mice. Furthermore, functional vinorelbine liposomes were constructed to investigate the anticancer effects of combined treatment. The functional miRNA liposomes had a round shape and were nanosized (120 nm). Functional miRNA liposomes were effectively captured by TNBC cells in vitro and were target to mitochondria. Treatment with functional liposomes silenced the expression of and Slug protein, inhibited the TGF-β1/Smad pathway, and inhibited invasiveness and growth of TNBC cells. In TNBC cancer-bearing mice, functional miRNA liposomes exerted a stronger anticancer effect than functional vinorelbine liposomes, and combination therapy with these two formulations resulted in nearly complete inhibition of tumor growth. Preliminary safety evaluations indicated that the functional miRNA liposomes did not affect body weight or cause damage to any major organs. Furthermore, the functional liposomes significantly increased the half-life of the drug in the blood of cancer-bearing nude mice, and increased drug accumulation in breast cancer tissues. In this study, we constructed novel functional miRNA liposomes. These liposomes silenced Slug expression and inhibited the TGF-β1/Smad pathway in TNBC cells, and enhanced anticancer efficacy in mice using combined chemotherapy. Hence, the present study demonstrated a promising strategy for gene therapy of invasive breast cancer.

Background AT-rich interactive domain-containing protein 1A (ARID1A) is a subunit of the mammary SWI/SNF chromatin remodeling complex and a tumor suppressor protein. The loss of ARID1A been observed in several types of human cancers and associated with poor patient prognosis. Previously, we have reported that ARID1A protein was rapidly ubiquitinated and destructed in gastric cancer cells during DNA damage response. However, the ubiquitin e3 ligase that mediated this process remains unclear. Materials and methods The interaction between ARID1A and β-TRCP was verified by co-immunoprecipitation (Co-IP) assay. The degron site of ARID1A protein was analyzed by bioinformatics assay. Short hairpin RNAs (shRNAs) were used to knockdown (KD) gene expression. Results Here we show that DNA damage promotes ARID1A ubiquitination and subsequent destruction via the ubiquitin E3 ligase complex SCFβ-TRCP. β-TRCP recognizes ARID1A through a canonical degron site (DSGXXS) after its phosphorylation in response to DNA damage. Notably, genetic inactivation of the Ataxia Telangiectasia Mutated (ATM) kinase impaired DNA damage-induced ARID1A destruction. Conclusions Our studies provide a novel molecular mechanism for the negative regulation of ARID1A by β-TRCP and ATM in DNA damaged gastric cancer cells.