Effect of tiotropium bromide, N-acetylcysteine and respiratory training on pulmonary function, activity tolerance and quality of life of patients with chronic obstructive pulmonary disease

Purpose: To investigate the effect of application of tiotropium bromide and N- acetylcysteine in combination with respiratory training on the treatment of patients with chronic obstructive pulmonary disease (COPD), and the effect of the combined treatment on pulmonary function, tolerance of physical activity, and quality of life.Methods: One hundred COPD patients admitted to The First People’s Hospital of Guiyang (February 2019 - March 2021) were randomly and equally assigned to groups X and Y. Patients in Y were given tiotropium bromide in combination with N-acetylcysteine, while group X was treated with respiratory training, in addition to the treatment regimen in Y. Treatment efficacy, incidence of adverse reactions, pulmonary function indices, activity tolerance, quality of life (QLI) score, activities of daily living (ADL) score, and incidence of COPD at 2 weeks, 1 month and 2 months after treatment were determined, and compared between the two groups.Results: Relative to group Y, group X had significantly higher treatment efficacy, QLI score and ADL score (p < 0.05). Furthermore, group X also had better pulmonary function indices and activity tolerance, lower incidence of adverse reactions, and lower COPD incidence at 2 weeks, 1 month and 2 months after treatment (p < 0.05).Conclusion: Tiotropium bromide and N-acetylcysteine in combination with respiratory training enhanced therapeutic effect, pulmonary function, activity tolerance and quality of life of COPD patients

Empowering Dual-Encoder with Query Generator for Cross-Lingual Dense Retrieval

In monolingual dense retrieval, lots of works focus on how to distill knowledge from cross-encoder re-ranker to dual-encoder retriever and these methods achieve better performance due to the effectiveness of cross-encoder re-ranker. However, we find that the performance of the cross-encoder re-ranker is heavily influenced by the number of training samples and the quality of negative samples, which is hard to obtain in the cross-lingual setting. In this paper, we propose to use a query generator as the teacher in the cross-lingual setting, which is less dependent on enough training samples and high-quality negative samples. In addition to traditional knowledge distillation, we further propose a novel enhancement method, which uses the query generator to help the dual-encoder align queries from different languages, but does not need any additional parallel sentences. The experimental results show that our method outperforms the state-of-the-art methods on two benchmark datasets.Comment: EMNLP 2022 main conferenc

RUEL: Retrieval-Augmented User Representation with Edge Browser Logs for Sequential Recommendation

Online recommender systems (RS) aim to match user needs with the vast amount of resources available on various platforms. A key challenge is to model user preferences accurately under the condition of data sparsity. To address this challenge, some methods have leveraged external user behavior data from multiple platforms to enrich user representation. However, all of these methods require a consistent user ID across platforms and ignore the information from similar users. In this study, we propose RUEL, a novel retrieval-based sequential recommender that can effectively incorporate external anonymous user behavior data from Edge browser logs to enhance recommendation. We first collect and preprocess a large volume of Edge browser logs over a one-year period and link them to target entities that correspond to candidate items in recommendation datasets. We then design a contrastive learning framework with a momentum encoder and a memory bank to retrieve the most relevant and diverse browsing sequences from the full browsing log based on the semantic similarity between user representations. After retrieval, we apply an item-level attentive selector to filter out noisy items and generate refined sequence embeddings for the final predictor. RUEL is the first method that connects user browsing data with typical recommendation datasets and can be generalized to various recommendation scenarios and datasets. We conduct extensive experiments on four real datasets for sequential recommendation tasks and demonstrate that RUEL significantly outperforms state-of-the-art baselines. We also conduct ablation studies and qualitative analysis to validate the effectiveness of each component of RUEL and provide additional insights into our method.Comment: CIKM 2023 AD

Large Language Models are Diverse Role-Players for Summarization Evaluation

Text summarization has a wide range of applications in many scenarios. The evaluation of the quality of the generated text is a complex problem. A big challenge to language evaluation is that there is a clear divergence between existing metrics and human evaluation. For example, the quality of a document summary can be measured by human annotators from both objective aspects, such as grammatical and semantic correctness, as well as subjective dimensions, such as comprehensiveness, succinctness, and interestingness. Most of the automatic evaluation methods like BLUE/ROUGE may be not able to capture the above dimensions well. In this paper, we propose a new evaluation framework based on LLMs, which provides a comprehensive evaluation framework by comparing generated text and reference text from both objective and subjective aspects. First, we propose to model objective and subjective dimensions of generated text based on roleplayers prompting mechanism. Furthermore, we introduce a context-based prompting mechanism that is able to generate dynamic roleplayer profiles based on input context. Finally, we design a multi-roleplayer prompting technology based on batch prompting to integrate multiple evaluation results into evaluation results. Experimental results on two real datasets for summarization show that our model is highly competitive and has a very high consistency with human annotators

Lexicon-Enhanced Self-Supervised Training for Multilingual Dense Retrieval

Recent multilingual pre-trained models have shown better performance in various multilingual tasks. However, these models perform poorly on multilingual retrieval tasks due to lacking multilingual training data. In this paper, we propose to mine and generate self-supervised training data based on a large-scale unlabeled corpus. We carefully design a mining method which combines the sparse and dense models to mine the relevance of unlabeled queries and passages. And we introduce a query generator to generate more queries in target languages for unlabeled passages. Through extensive experiments on Mr. TYDI dataset and an industrial dataset from a commercial search engine, we demonstrate that our method performs better than baselines based on various pre-trained multilingual models. Our method even achieves on-par performance with the supervised method on the latter dataset.Comment: EMNLP 2022 Finding

Allele frequency analysis of Chinese chestnut (Castanea mollissima) populations using fluorescent simple sequence repeats (SSR) analysis

The aim of this study was to establish a method for allele frequency detection in bulk samples. The abundance of polymerase chain reaction (PCR) products in bulk leaf samples was detected using fluorescent labeled Simple sequence repeat (SSR) primers and an Applied biosystems (AB) automatic DNA analyzer. Compared with the conventional SSR technique based on polyacrylamide gel electrophoresis (PAGE) and silver staining, fluorescent SSR was much more sensitive. A total of 78 alleles, an average of 4.6 alleles per locus, were detected among 17 chestnut populations with the primer CmTCR10 (NED) and a total of 41 alleles, an average of 2.4 alleles per locus, were detected with the primer CmTCR24 (6-FAM). Multiplexing the PCR reaction by combining the primer pairs of CmTCR10 and CmTCR24, using different fluorescent dyes for different primers, showed that the alleles could be discriminated and the sizes of the amplified segments were similar. Furthermore, the exact sizes of the amplified fragments and the abundance of the PCR products were determined by fluorescent SSR. After data analysis with GeneScan software and allele calling and output with Genotyper software, allele frequencies were calculated for equal pooled samples in each population using the FREQS-R module in the R statistical computing language. The results indicate that it is feasible to determine allele frequencies in bulked samples based on the detection of SSR-PCR products. The advantages and additional applications of this method are also discussed. The abundance of the PCR products can be used to determine the allele frequencies in bulk samples of chestnut populations.Keywords: Fluorescent simple sequence repeats (SSR), chestnut population, bulk sampling, allele frequencie

The spatial effects of rural toilet retrofitting investment on farmers' medical and health expenditure in China

BackgroundChina stretches across a vast area, and different geographical environments and economic and social development conditions, along with learning imitation and factor flow among participants can lead to two major spatial characteristics of toilet retrofitting investment: spatial heterogeneity and spatial correlation.MethodsThis study contributes to explore this topic by assessing the spatial heterogeneity and spatial correlation of toilet retrofitting investment on farmers' medical and health expenditure based on the spatial econometric model.Results(1) There are significant spatial agglomeration characteristics of both the toilet retrofitting investment and farmers' medical and health expenditure in China. (2) At the national level, the rural toilet retrofitting investment will influence the farmers' medical and health expenditure, and the effect on the local area is greater than on the surrounding areas. (3) After taking into account the differences in natural geographical environment and social and economic development, China is divided into four regions: east, central, west and northeast. In terms of spatial effects within different regions, the intensity of the impact of toilet retrofitting investment on local farmers' medical and health expenditure is in the order of central > eastern > western > northeast. The improvement of people's livelihood in the eastern and central regions by toilet retrofitting investment would lead to imitation by surrounding regions, thus reflecting spillover effects, while in the western region, toilet retrofitting investment would trigger fierce competition in related industries and factor markets, manifesting the competition effect. (4) As for the spatial effects across different regions, the toilet retrofitting investment produces spillover effects in all four regions, among which the intensity of the influence effect is the greatest in the central-western region, followed by the west-northeast, and the influence effect in the east-west is not significant.DiscussionThe comprehensive promotion of rural toilet retrofitting should not only focus on investment in the western and northeastern regions, but also strengthen regional communication and cooperation to improve rural residents' health and quality of life

TCF21 is related to testis growth and development in broiler chickens

Additional file 1: Table S1. Generations of NEAUHLF chickens used for the different analyses in the current study

DICER1 regulated let-7 expression levels in p53-induced cancer repression requires cyclin D1.

Let-7 miRNAs act as tumour suppressors by directly binding to the 3\u27UTRs of downstream gene products. The regulatory role of let-7 in downstream gene expression has gained much interest in the cancer research community, as it controls multiple biological functions and determines cell fates. For example, one target of the let-7 family is cyclin D1, which promotes G0/S cell cycle progression and oncogenesis, was correlated with endoribonuclease DICER1, another target of let-7. Down-regulated let-7 has been identified in many types of tumours, suggesting a feedback loop may exist between let-7 and cyclin D1. A potential player in the proposed feedback relationship is Dicer, a central regulator of miRNA expression through sequence-specific silencing. We first identified that DICER1 is the key downstream gene for cyclin D1-induced let-7 expression. In addition, we found that let-7 miRNAs expression decreased because of the p53-induced cell death response, with deregulated cyclin D1. Our results also showed that cyclin D1 is required for Nutlin-3 and TAX-induced let-7 expression in cancer repression and the cell death response. For the first time, we provide evidence that let-7 and cyclin D1 form a feedback loop in regulating therapy response of cancer cells and cancer stem cells, and importantly, that alteration of let-7 expression, mainly caused by cyclin D1, is a sensitive indicator for better chemotherapies response

NASA-Approved Rotary Bioreactor Enhances Proliferation of Human Epidermal Stem Cells and Supports Formation of 3D Epidermis-Like Structure

The skin is susceptible to different injuries and diseases. One major obstacle in skin tissue engineering is how to develop functional three-dimensional (3D) substitute for damaged skin. Previous studies have proved a 3D dynamic simulated microgravity (SMG) culture system as a “stimulatory” environment for the proliferation and differentiation of stem cells. Here, we employed the NASA-approved rotary bioreactor to investigate the proliferation and differentiation of human epidermal stem cells (hEpSCs). hEpSCs were isolated from children foreskins and enriched by collecting epidermal stem cell colonies. Cytodex-3 micro-carriers and hEpSCs were co-cultured in the rotary bioreactor and 6-well dish for 15 days. The result showed that hEpSCs cultured in rotary bioreactor exhibited enhanced proliferation and viability surpassing those cultured in static conditions. Additionally, immunostaining analysis confirmed higher percentage of ki67 positive cells in rotary bioreactor compared with the static culture. In contrast, comparing with static culture, cells in the rotary bioreactor displayed a low expression of involucrin at day 10. Histological analysis revealed that cells cultured in rotary bioreactor aggregated on the micro-carriers and formed multilayer 3D epidermis structures. In conclusion, our research suggests that NASA-approved rotary bioreactor can support the proliferation of hEpSCs and provide a strategy to form multilayer epidermis structure