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Xu Su,1,* Yimei Zhang,1,* Huilin Zhou,1 Fang Ma,1 Xiaorong Jin,1 Yangjuan Bai,2 Wei Wei,3 Xiong Zhang,1 Min Zhou1 1Department of Nursing, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China; 2Cardiology Department, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China; 3Digestive Surgery Department, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China*These authors contributed equally to this workCorrespondence: Fang Ma, Department of Nursing, The First Affiliated Hospital of Kunming Medical University, No. 295, Xichang Road, Kunming, 650032, People’s Republic of China, Email rebeccamalei@126.comPurpose: Studies had reported some influencing factors of health behavior among patients with coronary heart disease(CHD) after percutaneous coronary intervention(PCI). However, considering that human perceptions are complex, unrestricted and dynamically changing. A longitudinal qualitative study was conducted to explore the determinants of health-related behaviors of patients after PCI and dynamic changes of these determinants at the 1st, 3rd, and 6th months.Patients and Methods: Using purposive sampling, 18 patients undergoing PCI were interviewed. The conventional content analysis method was used to identify categories and subcategories. Semi-structured, face-to-face or telephone in-depth interviews were conducted at the cardiology unit of a tertiary referral hospital in Yunnan Province, China from March 2022 to January 2023.Results: Seven categories with some subcategories were constructed from the data, categorized into three domains. Firstly, individual factors include (i) Personal coping with healthy lifestyle requirements (tried but failed; I can do it), (ii) individual perception and feeling toward disease (knowing about the disease; belief of cure; fears of relapse), and (iii) personal benefits (improv

Hang Zhou,1 Fang Ma,2 Yi Zhang,2 Youqin Tan,2 Yangjuan Bai,3 Qiulan Hu,4 Wei Wei,5 Yanjiao Wang1 1Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China; 2Department of Nursing, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China; 3Cardiology Department, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China; 4ICU in Geriatric Department, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China; 5Neurosurgery Department, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of ChinaCorrespondence: Yanjiao Wang, Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 295#, Xichang Road, Kunming, People’s Republic of China, Tel +86-138-889-29699, Email mayuwyj1974@126.com Correspondence: Fang Ma, Department of Nursing, The First Affiliated Hospital of Kunming Medical University, 295#, Xichang Road, Kunming, People’s Republic of China, Tel +86-159-251-89957, Email rebeccamalei@126.comPurpose: To explore perceptions of antipsychotics associated side-effects among family caregivers of patients with schizophrenia.Patients and Methods: A descriptive qualitative study was applied in a tertiary referral hospital in China. Purposeful sampling of 18 family caregivers of patients with schizophrenia were interviewed about their perceptions towards antipsychotics related side effects.Results: According to content analysis, three themes emerged from the data: (a) nightmare in the treatment with the categories of sleep disturbances; physical impairment; appearance impairment; (b) opposite attitudes toward side-effect with the categories of being vigilant; do not care; (c) diverse ways of coping side-effects with the categories of asking for help from professionals; self-determined; try any quack’s prescription.

Xiao-Min Zhang, Ming-Hui Lun, Wei Du, Fang Ma, Ze-Qing Huang Department of Anesthesiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institution, NO.44 Xiaoheyan Road, Dadong District, Shenyang, Liaoning Province, 110042, People’s Republic of ChinaCorrespondence: Xiao-Min Zhang; Ze-Qing Huang Department of Anesthesiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institution, No.44 Xiaoheyan Road, Dadong District, Shenyang, Liaoning Province, 110042, People’s Republic of China Email zhangxiaomin.99@163.com; huangzeqing0@163.comObjective: To observe the ameliorative effect of kappa opioid receptor (KOR) agonist on rats with neuropathic pain (NP) and investigate the mechanism of action of the calcium ion (Ca2+)/calcium/calmodulin-dependent protein kinase II (CaMKII)/cyclic AMP response element-binding protein (CREB) pathway.Methods: A total of 40 Sprague Dawley rats were randomly divided into four groups: sham-operation group (Sham group), NP model group (NP group), NP + KOR agonist U50488H group (NU group) and NP + specific CaMKII antagonist (KN93) + U50488H group (NKU group). The thermal withdrawal latency (TWL) and mechanical withdrawal threshold (MWT) of each group of rats were determined. ELISA was applied to examine the changes in inflammatory factors and oxidative stress factors, and the apoptotic rate in dorsal root ganglia was observed using TUNEL staining. Ca2+ concentration, content of oxidative stress index ROS and the release of calcitonin gene-related peptide (CGRP) and N-methyl-D-aspartate receptor (NMDAR) in the dorsal root ganglia were measured by the immunofluorescence assay. Finally, Western blotting was performed to detect expression changes in the Ca2+/CaMKII/CREB pathway.Results: The KOR agonist U50488H could improve the values of TWL and MWT of NP the rats, inhibit inflammatory responses and relieve oxidative stress injury. Its mechanisms of action were associated with U5048

Prompt tuning learns soft prompts to condition frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gradually reached the performance level of fine-tuning as the model scale increases, there is still a large performance gap between prompt tuning and fine-tuning for models of moderate and small scales (typically less than 11B parameters). In this paper, we empirically show that the trained prompt tokens can have a negative impact on a downstream task and thus degrade its performance. To bridge the gap, we propose a novel Prompt tuning model with an eXtremely small scale (XPrompt) under the regime of lottery tickets hypothesis. Specifically, XPrompt eliminates the negative prompt tokens at different granularity levels through a hierarchical structured pruning, yielding a more parameter-efficient prompt yet with a competitive performance. Comprehensive experiments are carried out on SuperGLUE tasks, and the extensive results indicate that XPrompt is able to close the performance gap at smaller model scales., Comment: 15 pages, accepted to EMNLP 2022 main conference

Structural bias has recently been exploited for aspect sentiment triplet extraction (ASTE) and led to improved performance. On the other hand, it is recognized that explicitly incorporating structural bias would have a negative impact on efficiency, whereas pretrained language models (PLMs) can already capture implicit structures. Thus, a natural question arises: Is structural bias still a necessity in the context of PLMs? To answer the question, we propose to address the efficiency issues by using an adapter to integrate structural bias in the PLM and using a cheap-to-compute relative position structure in place of the syntactic dependency structure. Benchmarking evaluation is conducted on the SemEval datasets. The results show that our proposed structural adapter is beneficial to PLMs and achieves state-of-the-art performance over a range of strong baselines, yet with a light parameter demand and low latency. Meanwhile, we give rise to the concern that the current evaluation default with data of small scale is under-confident. Consequently, we release a large-scale dataset for ASTE. The results on the new dataset hint that the structural adapter is confidently effective and efficient to a large scale. Overall, we draw the conclusion that structural bias shall still be a necessity even with PLMs., Comment: 10 pages, 4 figures, 5 tables, accepted to COLING 2022, code is available at https://github.com/GeneZC/StructBias

Multimodal emotion recognition in conversations (mERC) is an active research topic in natural language processing (NLP), which aims to predict human's emotional states in communications of multiple modalities, e,g., natural language and facial gestures. Innumerable implicit prejudices and preconceptions fill human language and conversations, leading to the question of whether the current data-driven mERC approaches produce a biased error. For example, such approaches may offer higher emotional scores on the utterances by females than males. In addition, the existing debias models mainly focus on gender or race, where multibias mitigation is still an unexplored task in mERC. In this work, we take the first step to solve these issues by proposing a series of approaches to mitigate five typical kinds of bias in textual utterances (i.e., gender, age, race, religion and LGBTQ+) and visual representations (i.e, gender and age), followed by a Multibias-Mitigated and sentiment Knowledge Enriched bi-modal Transformer (MMKET). Comprehensive experimental results show the effectiveness of the proposed model and prove that the debias operation has a great impact on the classification performance for mERC. We hope our study will benefit the development of bias mitigation in mERC and related emotion studies., Comment: 10 pages, 5 figures, accepted to NLPCC 2022

Aspect-based sentiment analysis (ABSA) aims at predicting sentiment polarity (SC) or extracting opinion span (OE) expressed towards a given aspect. Previous work in ABSA mostly relies on rather complicated aspect-specific feature induction. Recently, pretrained language models (PLMs), e.g., BERT, have been used as context modeling layers to simplify the feature induction structures and achieve state-of-the-art performance. However, such PLM-based context modeling can be not that aspect-specific. Therefore, a key question is left under-explored: how the aspect-specific context can be better modeled through PLMs? To answer the question, we attempt to enhance aspect-specific context modeling with PLM in a non-intrusive manner. We propose three aspect-specific input transformations, namely aspect companion, aspect prompt, and aspect marker. Informed by these transformations, non-intrusive aspect-specific PLMs can be achieved to promote the PLM to pay more attention to the aspect-specific context in a sentence. Additionally, we craft an adversarial benchmark for ABSA (advABSA) to see how aspect-specific modeling can impact model robustness. Extensive experimental results on standard and adversarial benchmarks for SC and OE demonstrate the effectiveness and robustness of the proposed method, yielding new state-of-the-art performance on OE and competitive performance on SC., Comment: 12 pages, accepted to NLPCC 2022

Background: The disability weight (DW) quantifies the severity of health states from disease sequela and is a pivotal parameter for disease burden calculation. We conducted a national and subnational DW measurement in China. Methods: In 2020–2021, we conducted a web-based survey to assess DWs for 206 health states in 31 Chinese provinces targeting health workers via professional networks. We fielded questions of paired comparison (PC) and population health equivalence (PHE). The PC data were analysed by probit regression analysis, and the regression results were anchored by results from the PHE responses on the DW scale between 0 (no loss of health) and 1 (health loss equivalent to death). Findings: We used PC responses from 468,541 respondents to estimate DWs of health states. Eight of 11 domains of health had significantly negative coefficients in the regression of the difference between Chinese and Global Burden of Disease (GBD) DWs, suggesting lower DW values for health states with mention of these domains in their lay description. We noted considerable heterogeneity within domains, however. After applying these Chinese DWs to the 2019 GBD estimates for China, total years lived with disability (YLDs) increased by 14·9% to 177 million despite lower estimates for musculoskeletal disorders, cardiovascular diseases, mental disorders, diabetes and chronic kidney disease. The lower estimates of YLDs for these conditions were more than offset by higher estimates of common, low-severity conditions. Interpretation: The differences between the GBD and Chinese DWs suggest that there might be some contextual factors influencing the valuation of health states. While the reduced estimates for mental disorders, alcohol use disorder, and dementia could hint at a culturally different valuation of these conditions in China, the much greater shifts in YLDs from low-severity conditions more likely reflects methodological difficulty to distinguish between health states that vary

Neural text matching models have been used in a range of applications such as question answering and natural language inference, and have yielded a good performance. However, these neural models are of a limited adaptability, resulting in a decline in performance when encountering test examples from a different dataset or even a different task. The adaptability is particularly important in the few-shot setting: in many cases, there is only a limited amount of labeled data available for a target dataset or task, while we may have access to a richly labeled source dataset or task. However, adapting a model trained on the abundant source data to a few-shot target dataset or task is challenging. To tackle this challenge, we propose a Meta-Weight Regulator (MWR), which is a meta-learning approach that learns to assign weights to the source examples based on their relevance to the target loss. Specifically, MWR first trains the model on the uniformly weighted source examples, and measures the efficacy of the model on the target examples via a loss function. By iteratively performing a (meta) gradient descent, high-order gradients are propagated to the source examples. These gradients are then used to update the weights of source examples, in a way that is relevant to the target performance. As MWR is model-agnostic, it can be applied to any backbone neural model. Extensive experiments are conducted with various backbone text matching models, on four widely used datasets and two tasks. The results demonstrate that our proposed approach significantly outperforms a number of existing adaptation methods and effectively improves the cross-dataset and cross-task adaptability of the neural text matching models in the few-shot setting., Comment: 10 pages, accepted to SIGIR 2022

Aspect sentiment classification (ASC) aims at determining sentiments expressed towards different aspects in a sentence. While state-of-the-art ASC models have achieved remarkable performance, they are recently shown to suffer from the issue of robustness. Particularly in two common scenarios: when domains of test and training data are different (out-of-domain scenario) or test data is adversarially perturbed (adversarial scenario), ASC models may attend to irrelevant words and neglect opinion expressions that truly describe diverse aspects. To tackle the challenge, in this paper, we hypothesize that position bias (i.e., the words closer to a concerning aspect would carry a higher degree of importance) is crucial for building more robust ASC models by reducing the probability of mis-attending. Accordingly, we propose two mechanisms for capturing position bias, namely position-biased weight and position-biased dropout, which can be flexibly injected into existing models to enhance representations for classification. Experiments conducted on out-of-domain and adversarial datasets demonstrate that our proposed approaches largely improve the robustness and effectiveness of current models., Comment: 7 pages, 2 figures, 4 tables, accepted to Findings of ACL 2021. Repo: https://github.com/BD-MF/POS4ASC

Wenxiao Jia,*,1 Jiaqin Zhang,*,2 Fang Ma,1 Shengjie Hao,1 Xue Li,1 Ruiting Guo,1 Qianqian Gao,1 Yundong Sun,1 Jihui Jia,1 Wenjuan Li11Key Laboratory for Experimental Teratology of Chinese Ministry of Education, The Shandong Provincial Key Laboratory of Infection and Immunology, Department of Microbiology, School of Basic Medical Sciences, Shandong University, Jinan, People’s Republic of China; 2Department of Clinical Laboratory, The First Affiliated Hospital of Xiamen University, Xiamen, People’s Republic of ChinaCorrespondence: Wenjuan LiKey Laboratory for Experimental Teratology of Chinese Ministry of Education, The Shandong Provincial Key Laboratory of Infection and Immunology, Department of Microbiology, School of Basic Medical Sciences, Shandong University, No. 44, Wenhuaxi Road, Jinan, Shangdong Province, People’s Republic of ChinaTel +86 5 318 838 2579Fax +86 5 318 838 2502Email wenjli@sdu.edu.cn*These authors contributed equally to this workBackground: Long noncoding RNAs (LncRNAs) have been confirmed to play crucial roles in cancer biology. Gastric cancer (GC) is the third leading cause of cancer related death, and Helicobacter pylori (H. pylori) is the major risk factor for GC. In this study, we focused on the roles of H. pylori-related lncRNAs in the progression of GC.Method: Differentially expressed lncRNAs were identified through RNA-seq analysis of H. pylori-infected GC cells.Results: We found that the expression of the lncRNA THAP9-AS1 was up-regulated after infection of GC cells with H. pylori and was higher in GC tissues than in gastritis tissues. Colony formation, CCK8 and transwell assays were executed to show that THAP9-AS1 can promote GC cell proliferation and migration in vitro. Our study identified the pro-oncogenic lncRNA THAP9-AS1, which has a higher expression level in GC tissues than in gastritis tissues and which promoted the proliferation and migration of GC cells in vitro.Conclusion: These findings may prov

For wastewater-related issues (WRI), life cycle assessment (LCA) is often used to evaluate environmental impacts and derive optimization strategies. To promote the application of LCA for WRI, it is critical to incorporate local impact of water pollutants. Organic pollution, a main type of water pollution, has not been given much consideration in current LCA systems. This paper investigates the necessity of setting a regionalized impact category to reflect the local impact of organic pollution. A case study is conducted concerning an upgraded wastewater treatment plant (WWTP) in China, which is assumed to meet different sewage control strategies. Chemical oxygen demand (COD) is selected to represent the organic pollution and treated as an individual impact category. CML 2002 is used to quantify the environmental impacts of different strategies. Results show that abnormal LCA results are generated with the traditional eutrophication impact category, and after the introduction of COD, more reasonable LCA results are obtained, making the entire comparison of different control strategies more meaningful and compelling. Moreover, BEES, Ecovalue 08, and Chinese factors are adopted here as different weighting methods. Different weighting results exhibited various trade-offs for the increasingly strict control strategies; the results of BEES and Ecovalue08 underlined the potential environmental burden, but the results of Chinese factors only emphasized the local environmental improvement. It is concluded that setting regionalized impact category for organic pollution can make LCA results more reasonable in wastewater treatment, especially in evaluating Chinese cases because of the serious water pollution caused by large quantities of COD emission., Sanitary Engineering

The increasing salinity in aquatic environments has had a negative impact on the biodegradation of atrazine, an extensively used herbicide which has been proven to pollute soil and water ecosystems. In the present study, a novel atrazine-degrading strain (ZXY-2) was isolated from industrial wastewater and identified as the Arthrobacter genus with the 16S rRNA gene. Results indicated that the strain showed a high salinity tolerance, and was able to tolerate NaCl concentrations up to 10% (w/w). Plackett–Burman (PB) multifactorial design and response surface methodology (RSM) were then employed to optimize the culturing conditions. Results showed that among the selected fifteen factors, six contributing factors were obtained. Subsequently, by employing the RSM to model and optimize atrazine degradation, a biodegradation efficiency of 12.73 mg L−1 h−1 was reached under optimal conditions (34.04 °C, pH 9.0, inoculum size 10% (v/v), 2.212 g L−1 of sucrose, 6 g L−1 of Na2HPO4·12H2O, and 50 mg L−1 of atrazine). In addition, a statistically quadratic polynomial mathematical model was suggested (R2 = 0.9873). In contrast to other atrazine-degrading bacteria, ZXY-2 appears to be adapted to life under high salinity conditions and sustains excellent atrazine degradation performance. Therefore it could potentially be applied in atrazine bioremediation., Sanitary Engineering

Wei Guo,1,2,* Yabing Zheng,2,* Bing Xu,1 Fang Ma,1 Chang Li,3 Xiaoqian Zhang,4 Yao Wang,1 Xiaotian Chang1 1Medical Research Center, Shandong Provincial Qianfoshan Hospital, 2Obstetrical Department, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, Shandong, 3Pathology Department, Tengzhou Central People’s Hospital, Tengzhou, 4Clinical Laboratory, PKU Care Luzhong Hospital, Zibo, Shandong, People’s Republic of China *These authors contributed equally to this work Background: Peptidylarginine deiminase (PAD) catalyzes the conversion of arginine residues to citrulline residues, termed citrullination. Recent studies have suggested that PAD isoform 2 (PADI2) plays an important role in tumors, although its tumorigenic effect and mechanism are largely unknown. Materials and methods: Immunohistochemistry and enzyme-linked immunosorbent assay (ELISA) were used to investigate the expression level of PADI2 in various tumor tissues and patient blood samples, respectively. MNK-45 and Bel-7402 tumor cell lines originating from gastric and liver tumors, respectively, were treated with anti-PADI2 siRNA, and the subsequent cell proliferation, apoptosis and migration were observed. Polymerase chain reaction (PCR) arrays, including Cancer PathwayFinder, Oncogenes and Tumor Suppressor Genes, p53 Signaling Pathway, Signal Transduction Pathway and Tumor Metastasis PCR arrays, were used to investigate the tumorigenic pathway of PADI2 in the siRNA-treated tumor cells. This analysis was verified by real-time PCR. Results: Immunohistochemistry detected significantly increased expression of PADI2 in invasive breast ductal carcinoma, cervical squamous cell carcinoma, colon adenocarcinoma, liver hepatocellular carcinoma, lung cancer, ovarian serous papillary adenocarcinoma and papillary thyroid carcinoma samples. ELISA detected a twofold increase in PADI2 expression in the blood of 48.3% of patients with liver cancer, 38% of patients with cervical carcinom

Establishment of adequate levels of sialylation is crucial for sperm survival and function after insemination; however, the mechanism for the addition of the sperm sialome has not been identified. Here, we report evidence for several different mechanisms that contribute to the establishment of the mature sperm sialome. Directly quantifying the source of the nucleotide sugar CMP-beta-N-acetylneuraminic acid in epididymal fluid indicates that transsialylation occurs in the upper epididymis. Western blots for the low-molecular-mass sialoglycoprotein (around 20-50 kDa) in C57BL/6 mice epididymal fluid reflect that additional sialome could be obtained by glycosylphosphatidylinositol-anchored sialoglycopeptide incorporation during epididymal transit in the caput of the epididymis. Additionally, we found that in Cmah (CMP-N-acetylneuraminic acid hydroxylase)-/- transgenic mice, epididymal sperm obtained sialylated-CD52 from seminal vesicle fluid (SVF). Finally, we used Gfp (green fluorescent protein)+/+ mouse sperm to test the role of sialylation on sperm for protection from female leukocyte attack. There is very low phagocytosis of the epididymal sperm when compared to that of sperm coincubated with SVF. Treating sperm with Arthrobacter ureafaciens sialidase (AUS) increased phagocytosis even further. Our results highlight the different mechanisms of increasing sialylation, which lead to the formation of the mature sperm sialome, as well as reveal the sialome's function in sperm survival within the female genital tract.

"Sexual health vulnerability among Latino/a sexual and gender minorities is poorly understood, despite high rates of HIV and STDs among Latino/as, particularly in new settlement states in the southern US. The lack of a model specific to Latino/a sexual and gender minorities complicates the study of vulnerability. To move vulnerability research forward with this population, key constructs must be defined and processes for model development described. Clarity in the operationalization of vulnerability, as well as in the approach for adapting a vulnerability model to Latino/a sexual and gender minorities, can improve replicability to other similar populations and standardize a method toward model development. This study tests a new theoretical model of vulnerability for Latino/a sexual and gender minorities by adapting the General Model of Vulnerability. A community-based participatory research partnership recruited Latino/a sexual and gender minorities (i.e., men who have sex with men and transgender women; N=186) in North Carolina to participate in the HOLA intervention. Using baseline data collected in 2012, I performed latent class analysis to operationalize vulnerability across three domains (i.e., socioeconomic stability, health care, and social) using eight indicators (i.e., educational attainment, employment status, routine check-up, social support, acculturation, racial/ethnic and sexual discrimination, and internalized homonegativity) to identify underlying classes of vulnerability, then tested the association between class membership and three sexual health behaviors (i.e., HIV testing, STD testing, and condom use). In this sample, I identified three latent classes of vulnerability: High Education and Employment (18.8% of the sample; characterized by high educational attainment and employment status), Low Education and High Social Support (63.4%), and High Education and Discrimination (17.7%; high educational attainment and racial/ethnic and sexual discrimination). Membership in the Low Education and High Social Support class and the High Education and Discrimination class was significantly associated with more condomless anal or vaginal intercourse, whereas membership in the High Education and Employment class was associated with less condomless anal or vaginal intercourse (p < 0.05). I found no significant associations between vulnerability and HIV testing nor STD testing. Overall, the results from this study found that the identification of latent classes of vulnerability differentially predicted a sexual health behavior among Latino/a sexual and gender minorities in NC. These findings highlight the utility of identifying typologies of vulnerability to predict patterns of sexual health behavior. This information can be used to tailor future efforts to specific groups of Latino/a sexual and gender minorities, as well as other vulnerable populations living in other parts of the US. Developing intervention components that harness facilitators (e.g., social support) and address barriers (e.g., discrimination) to health, focusing specifically on those uniquely vulnerable, is critical to increasing the reach and effectiveness of tailored health promotion and HIV/STD prevention programming."--Abstract from author supplied metadata.

We present a new, novel approach to obtaining a network's connectivity. More specifically, we show that there exists a relationship between a network's graph isoperimetric properties and its conditional connectivity. A network's connectivity is the minimum number of nodes, whose removal will cause the network disconnected. It is a basic and important measure for the network's reliability, hence its overall robustness. Several conditional connectivities have been proposed in the past for the purpose of accurately reflecting various realistic network situations, with extra connectivity being one such conditional connectivity. In this paper, we will use isoperimetric properties of the hypercube network to obtain its extra connectivity. The result of the paper for the first time establishes a relationship between the age-old isoperimetric problem and network connectivity., Comment: 17 pages, 0 figures

Aims Changes in the phenotype of crops (phenotypic plasticity) are known to play an important role in determining responses to nutrient availability, with the direction and magnitude of plasticity of individual traits being crucial for grain yields. Our study analysed the direction, magnitude and hierarchy of plastic responses of yield-related traits (i.e. biomass allocation and yield components) of rice (Oryza sativa L.) to nutrient availability. We estimated the effect of inoculation with arbuscular mycorrhizal fungi (AMF) on these characteristics of phenotypic plasticity. Methods A field experiment was carried out in northeast China, providing rice with six NPK fertilizer levels with or without inoculation with Glomus mosseae. At maturity, we quantified biomass allocation traits (shoot:root ratio and panicle:shoot ratio) and yield component traits (panicle number per hill, spikelet number per panicle, percentage of filled spikelets and seed weight). We also assessed the direction of change in each trait and the magnitude of trait plasticity. Important Findings In non-inoculated plants, we found that biomass allocation and seed-number traits (i.e. panicle number per hill, spikelet number per panicle and percentage of filled spikelets) responded to fertilization in the same direction, increasing with rising fertilization. Panicle formation was the most plastic trait, while seed mass was the least plastic trait. AMF inoculation nullified the relationship between most biomass allocation and seed-number traits (except for that between panicle:shoot ratio and the percentage of filled spikelets) but increased the magnitude of plasticity in biomass allocation traits without altering the hierarchy of traits’ plasticity. These results underscore the importance of plasticity of yield-related traits per se, and the impact of AMF on plasticity, for maintaining rice yields under low fertilization regimes.

Fang-Jing Ma,1–3,* Zhe-Bin Liu,1,2,* Li Qu,4,* Shuang Hao,1,2 Guang-Yu Liu,1,2 Jiong Wu,1,2 Zhi-Ming Shao1,2 1Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, 2Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China; 3Department of Breast Surgery, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, Xinjiang, People’s Republic of China; 4Department of General Surgery, Zhejiang Hospital, Hangzhou, People’s Republic of China  *These authors have contributed equally to this workBackground: Type 2 diabetes mellitus (T2DM) is one of the most common chronic metabolic diseases. Increased cause-specific mortality and decreased disease-free survival (DFS) have been reported among cancer patients with T2DM compared with patients without T2DM, even after adjustments of other comorbidities. However, less is known about the impact of T2DM and other comorbidities on DFS in Chinese patients with early stage triple-negative breast cancer (TNBC).Patients and methods: We assessed patients who were newly diagnosed with early stage primary TNBC at the Department of Breast Surgery, Fudan University, from 2003 to 2011. Of the 1,100 TNBC patients, 865 female patients had invasive and early stage TNBC. The association of the variables in the T2DM and non-T2DM groups was compared using the Pearson's chi-square and independent t-tests. DFS was estimated using the Kaplan–Meier method. The effects of T2DM and other possible risk factors on DFS were assessed by Cox proportional hazards regression using univariate or multivariate analysis.Results: A total of 865 early stage primary TNBC cases were studied, including 104 (12.02%) subjects with T2DM. Metastatic or recurrent disease was detected in 24 (23.08%) patients in the T2DM group and 35 (4.60%) patients in the non-T