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Tobacco is one of the most important economic crops in China. Disease is one of the main factors affecting the quality of tobacco production (Cai et al. 2022). Stem spot disease of tobacco was observed in the Planting Demonstration Garden in Chang Ning (26°37N; 112° 31E), Hunan Province of China, from May to June 2023. The disease seriously retarded tobacco growth and the incidence rate was about 30-50% of the plants(Yun Yan 87). Most of infected tobacco had black spots on the stems, and the spots expanded and joined together quickly, while many stems turned black and withered. For pathogen isolation, symptomatic stem samples were collected and disinfected with 75% ethanol for 30 s and 2% sodium hypochlorite for 1 minute, followed by rinsing with sterile distilled water three times. Subsequently, small pieces (5 × 5 mm) of diseased tissues were placed on potato dextrose agar (PDA) and incubated in the dark at 25 °C for 24 h to 36 h. The emerging fungal hyphal tips were transferred to PDA and purified by the single-spore method(Yu et al. 2022). In total, 16 cultures with the same appearance were isolated from 30 disease spots on the stem. Strain coded as hnxryc2 was randomly selected for identification. After culturing in PDA for 7 days, white and dense colonies wereobserved with a mean radial growth rate of 6.4 mm/day. The strain cultured 10 days on SNA. Morphological observations were made on 10-day-old culture on SNA medium, and macroconidia were sickle-shaped and slightly curved, with 3-5 septa (2.32-7.00 µm × 0.53-1.17 µm, n = 50), neither microconidia nor chlamydospores were observed. These morphological characteristics were consistent with the description of Fusarium humuli (Wang et al. 2019, Li et al. 2023). Furthermore, primers ITS1/ITS4, EF728F/EF986R, RPB1-F5/RPB1-R8 and fRPB2-5F2/fRPB2-7cR(Xie et al. 2023) were used to amplify the ITS region, EF-1α, RPB1, and RPB2 from strain hnxryc2, respectively. The sequence alignment of hnxryc2 with the NCBI database and FUSARIOID-ID shows the following results: The sequence of ITS region(GenBank accession number PP543715) was 100% identical to these of Fusarium sp. (MN428026.1), the sequences of EF-1α, RPB1, and RPB2 of strain hnxryc2(GenBank accession numbersOR257586, OR326856 and OR257587 respectively) were 99% to 100% identical to these of F. humuli (GenBank accession numbers MK289578.1, MZ824672.1 and MZ824673.1, respectively). Then a phylogenetic tree based on ITS region, EF-1α, and RPB2 sequences was constructed (Kroon et al. 2004). The strain hnxryc2 was more closely related to F. humuli (CGMCC3.19374 GenBank accession nos. MK280845.1, MK289570.1 and MK289724.1, respectively), with bootstrap values 88%. Pathogenicity tests were performed on detached stems of tobacco and potted plants. Wounded stems were inoculated with conidial suspensions (100 µL, 1×107 spores/mL), and the controls were inoculated with sterile water (Xu et al. 2023). The inoculated detached stems were kept in humid chambers (Zhong et al., 2019), each treatment was given a 12h/12h light/dark cycle at 25°C. Deep black spots were observed for 3 days after inoculation. After 9 days, typical symptoms similar to the original diseased plants in the field were found on all inoculated stems, while the control stems did not exhibit any symptoms. Pathogenicity assays were repeated thrice. The pathogen F. humuli was successfully reisolated from the stem of inoculated samples showing symptoms. To our knowledge, this is the first report of F. humuli inducing stem spot on tobacco in China. Since F. humuli is a common pathogenic fungus that infects different plant species, more attention should be paid to its prevalence in tobacco, and the potential risk of a disease outbreak in other provinces of China.

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TOPLESS/TOPLESS-RELATED (TPL/TPR) proteins belong to the Groucho (Gro)/Tup1 family co-repressors and act as broad co-repressors that modulate multiple phytohormone signalling pathways and various developmental processes in plant. However, TPL/TPR co-repressors so far are poorly understood in the rapeseed, one of the world-wide important oilseed crops. In this study, we comprehensively characterized eighteen TPL/TPR genes into five groups in the rapeseed genome. Members of TPL/TPR1/TPR4 and TPR2/TPR3 had close evolutionary relationship, respectively. All TPL/TPRs had similar expression patterns and encode conserved protein domain. In addition, we demonstrated that BnaA9.TPL interacted with all known plant repression domain (RD) sequences, which were distributed in non-redundant 24,238 (22.6 %) genes and significantly enriched in transcription factors in the rapeseed genome. These transcription factors were largely co-expressed with the TPL/TPR genes and involved in diverse pathway, including phytohormone signal transduction, protein kinases and circadian rhythm. Furthermore, BnaA9.TPL was revealed to regulate apical embryonic fate by interaction with Bna.IAA12 and suppression of PLETHORA1/2. BnaA9.TPL was also identified to regulate leaf morphology by interaction with Bna.AS1 (Asymmetric leaves 1) and suppression of KNOTTED-like homeobox genes and YABBY5. These data not only suggest the rapeseed TPL/TPRs play broad roles in different processes, but also provide useful information to uncover more TPL/TPR-mediated control of plant development in rapeseed.

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Sedum plumbizincicola is a cadmium (Cd) and zinc hyperaccumulator that can activate Cd by rhizosphere acidification. However, there is little understanding of the Cd leaching risk from polluted soil during phytoextraction process. Here, pot and column experiments were conducted to monitor soil Cd leaching characteristics under different rainfall simulation conditions during S. plumbizincicola phytoextraction. Soil Cd leaching increased significantly with increasing simulated rainfall intensity. Compared with normal rainfall (NR), weak rainfall (WR) resulted in a 34.3% decrease in Cd uptake by S. plumbizincicola and also led to a 68.7% decline in Cd leaching. In contrast, Cd leaching under heavy rainfall (HR) was 2.12 times that of NR in the presence of S. plumbizincicola. After two successive growing periods, phytoextraction resulted in a 53.5-66.4% decline in the amount of soil Cd leached compared with controls in which S. plumbizincicola was absent. Even compared with maize cropping as a control, S. plumbizincicola did not instigate a significant increase in Cd leaching. The contribution of Cd leaching loss to the decline in soil total Cd concentration was negligible after phytoextraction in the pot experiment. Overall, the results contribute to our understanding of soil Cd leaching risk by phytoextraction with S. plumbizincicola.

Repeated phytoextraction by hyperaccumulator Sedum plumbizincicola is an important remediation technology to remove Cd from contaminated soils. At the same time, Sedum plumbizincicola can also activate soil Cd by rhizosphere acidification. However, studies on the leaching risk of soil activated Cd during the phytoextraction process are very few. This study looked at the effects of Sedum plumbizincicola growth on soil Cd leaching with the changes in rainfall simulation and plant type. Results showed that repeated phytoextraction with Sedum plumbizincicola did not increase Cd leaching from contaminated soil.

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T follicular helper (Tfh) cells and their interactions with B cells within the germinal center play extensive roles in human immunodeficiency virus (HIV) pathology. However, their association with immune reconstitution during antiretroviral therapy (ART) is still unclear. The aim of this study was to determine the impact of Tfh and memory B cell function on T helper cell recovery in patients with acute or chronic HIV infection. A total of 100 HIV-infected individuals were enrolled in our study, classified into acute and chronic HIV infection groups (60 and 40, respectively), and subsequently classified into immunological responder (IR) and immunological nonresponder (INR) subgroups according to immune recovery outcomes after 96 weeks of ART. Liquid chromatography-mass spectrometry was used to quantify the temporal regulation patterns of B and CD4+ T-cell profiles among patients, and flow cytometry was used to investigate certain subsets of B and T cells. Here we showed that the prevalence of Tfh cells in the T helper cell population correlated negatively with CD4+ T-cell recovery. The proportion of CXCR3-  Tfh cells in patients with acute or chronic infection was associated with CD4+ T-cell count recovery, and the proportion of CD21+ memory B cells at baseline was significantly higher in those with improved immune recovery outcomes. Universal proteomic dysregulation of B and CD4+ T cells at baseline was detected in patients with acute infected and poor CD4+ T-cell recovery. Proteomics analysis revealed distinct temporal regulation profiles of both T helper cells and B cells between IRs and INRs among patients with acute infection. Our results suggest that the functions of memory B cells in INRs are dysregulated at the early stage of ART, possibly through disruption of Tfh cell function. The frequency and function of Tfh cells and their subsets are potential predictors of poor immune recovery.

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BACKGROUND: Glucocorticoid-induced osteoporosis is the most common secondary cause of osteoporosis, which increases the risk of fracture. Long non-coding RNA telomerase RNA elements (TERC) has been proven to be closely related to osteoporosis. However, the role of TERC in glucocorticoid-induced osteoporosis and its underlying molecular mechanism remains unclear. METHODS: The in vitro model of osteoporosis was established after bone marrow mesenchymal stem cells (BMSCs) were exposed to dexamethasone (DEX). The cell viability, alkaline phosphatase (ALP) activity and mineralized nodules of BMSCs were evaluated. The messenger RNA and protein levels were detected by quantitative real-time polymerase chain reaction and Western blot. The interaction between TERC, enhancer of zeste homolog 2 (EZH2) and dickkopf-1 (DKK1) was confirmed by chromatin immunoprecipitation and RNA immunoprecipitation assays. RESULTS: Bone marrow mesenchymal stem cells were isolated, identified and induced osteogenic differentiation. The findings showed that the levels of osteogenic marker genes, including ALP, Runt-related transcription factor 2 (RUNX2) and osteocalcin (OCN) in BMSCs were increased dependent on the osteogenic induction time. Similarly, TERC was significantly increased, but DKK1 was significantly decreased during BMSC osteogenic differentiation. Functional research showed that TERC overexpression promoted cell viability, ALP activity and mineralized nodules of BMSCs and increased the levels of osteogenic differentiation-related genes (ALP, RUNX2 and OCN), and TERC overexpression increased EZH2 protein level. Moreover, the decrease of cell viability, ALP activity and mineralized nodules induced by DEX was reversed by TERC overexpression. Furthermore, TERC inhibited DKK1 expression by promoting the histone modification of DKK1, and TERC overexpression alleviated DEX suppressed osteogenic differentiation of BMSCs by interaction with EZH2 to regulate DKK1. CONCLUSION: Our findings illustrated that TERC overexpression alleviated DEX-induced osteoporosis by recruiting EZH2 to regulate DKK1. Our research provided a novel direction for the treatment of glucocorticoid-induced osteoporosis.

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With the wide use of antiretroviral therapy in people living with HIV (PLWH), the mortality and morbidity rates among this community are dramatically decreasing. However, sleep disorder is still one of the prominent health issues among PLWH, and it lowers their quality of life. Although we already know the potential biological pathway that links poor sleep quality among PLWH, the potential contribution of the psychosocial pathway (e.g., stigma) is far from understood. In this study, we aimed to explore the potential serial mediating effects (HIV stigma-loneliness-depression-sleep quality) and potential moderating effects of perceived social support. We recruited a consecutive sample of 139 participants from voluntary counseling testing (VCT) clinics of Beijing Youan Hospital and participant referrals. Then, we used serial mediation models and moderated serial mediation models to fit our data. We found significant serial mediation effects between three types of HIV stigma (enacted, anticipated, and internalized) and sleep quality via depression and loneliness. Perceived social support also significantly moderated this serial mediation between enacted stigma, internalized stigma, and sleep quality. Our results highlight the potential role of perceived social support in moderating the negative effects of enacted and internalized stigma on sleep quality and identify potential psychosocial pathways.

People living with HIV (PLWH) may experience various kinds of prejudice and discrimination from others, anticipate experiencing social discrimination in the future, and hold negative beliefs about themselves, which may have a far-reaching negative impact on their mental health and physical health. Most of the studies have focused on the relationship between HIV-related stigma and mental health. In this study, we focused on the relationship between HIV-related stigma and sleep quality, one common symptom among people living with HIV, and found that HIV-related stigma may be associated with worse sleep quality via more depressive symptoms and loneliness feelings. Moreover, we found that social support, as one kind of resilience resource or "psychological lubricant", may buffer the detrimental influence of HIV-related stigma, especially for experiences of discrimination from others and negative self-image. Our preliminary findings highlight that future interventions targeting improving sleep quality among people living with HIV may consider offering social support services in combination with other biomedical services to reduce HIV-related stigma.

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IMPORTANCE: In the era of antiretroviral therapy (ART), the incidence of HIV-associated neurocognitive disorder (HAND) has not yet been controlled. With the exception of ART, there is no beneficial pharmacologic treatment. However, some studies have reported that computerized cognitive training (CCT) programs may improve cognitive function among people living with HIV. OBJECTIVE: To examine the association between CCT programs and 8 domains measuring cognitive function (7 domains) and daily function (1 domain) among people living with HIV. DATA SOURCES: Records from the Cochrane Library, PsycINFO, PubMed, and Web of Science were searched from database inception to December 15, 2020. Supplementary searches to identify missing studies were conducted in Google Scholar using updated search terms from database inception to November 18, 2021. STUDY SELECTION: Studies that compared changes before and after a CCT intervention among people living with HIV were included. Search terms were a combination of words associated with HIV (eg, people living with HIV, HIV, and/or AIDS) and cognitive training (eg, cognitive intervention, nonpharmacology intervention, computer game, video game, computerized training, cognitive exercise, cognitive stimulation, and/or cognitive enhancement). Studies were included if they (1) used CCT as the primary intervention or combined CCT with other types of interventions; (2) used placebo, passive control conditions, traditional cognitive training, or single training tasks as control conditions; (3) reported changes between baseline and posttraining; (4) included participants 18 years or older; and (5) were randomized clinical trials (RCTs). Studies were excluded if they (1) were not associated with HIV, (2) were research protocols or feedback reports, (3) were case reports, or (4) did not report findings for domains of interest. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently extracted data. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Random-effects models were used to quantitatively synthesize the existing data. MAIN OUTCOMES AND MEASURES: Primary outcomes were the meta-synthesized changes in each domain after CCT. RESULTS: Among 1245 records identified, 1043 were screened after removal of duplicates. Of those, 1019 records were excluded based on titles and abstracts, and 24 full-text articles were assessed for eligibility. After exclusions, 12 eligible RCTs were selected for inclusion in the meta-analysis. These RCTs involved 596 total participants, with 320 individuals in the CCT group (mean age, 47.5-59.7 years; 0%-94% female; 8.3-14.2 years of education) and 276 individuals in the control group (mean age, 44.2-60.0 years; 19%-90% female; 9.0-14.9 years of education). The average HIV inhibition ratio (the proportion of participants who achieved virological suppression) ranged from 30% to 100%, and the CD4+ T-cell count ranged from 471 to 833 cells/µL. The time since training ranged from 3 to 24 weeks. After receipt of CCT, function significantly improved in 6 of the 8 domains: abstraction and executive function (standardized mean difference [SMD], 0.58; 95% CI, 0.26-0.91; P < .001), attention and working memory (SMD, 0.62; 95% CI, 0.33-0.91; P < .001), memory (SMD, 0.59; 95% CI, 0.20-0.97; P = .003), motor skills (SMD, 0.50; 95% CI, 0.24-0.77; P < .001), speed of information processing (SMD, 0.65; 95% CI, 0.37-0.94; P < .001), and daily function (SMD, 0.44; 95% CI, 0.02-0.86; P = .04). Sensory and perceptual skills (SMD, 0.06; 95% CI, -0.36 to 0.48; P = .78) and verbal and language skills (SMD, 0.46; 95% CI, -0.07 to 0.99; P = .09) did not significantly improve after CCT. CONCLUSIONS AND RELEVANCE: This meta-analysis of RCTs found that CCT programs were associated with improvements in cognitive and daily function among people living with HIV. Future studies are needed to design optimal specific training programs and use implementation science to enable the transformation of CCT from a scientific research tool to a real-world clinical intervention.

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BACKGROUND: It is controversial whether the apolipoprotein E epsilon 4 allele (APOE ε4) is a risk gene for human immunodeficiency virus (HIV)-related neurocognitive impairment. This meta-analysis aimed to summarize evidence of the associations between APOE ε4 and cognitive impairment in people living with HIV (PLWH). METHODS: Our study conducted a systematic literature search of PubMed, Web of Science, Embase, Google Scholar, and ProQuest for studies published before April 11, 2022 that evaluated associations between APOE ε4 and cognitive impairment in adult PLWH (aged ≥18 years). We calculated pooled odds ratios (ORs) of global cognitive impairment and 95% confidence intervals (CIs) and standardized mean differences (SMDs) for specific cognitive domains between APOE ε4 carriers and non-carriers. Subgroup meta-analyses were used to evaluate the result profiles across different categorical variables. RESULTS: Twenty studies met the inclusion criteria, including 19 that evaluated global cognitive impairment. APOE ε4 was significantly associated with global cognitive impairment in PLWH (OR = 1.36, 95% CI = [1.05, 1.78], number of estimates [k] = 19, P = 0.02, random effects). Subgroup meta-analysis based percentage of females showed evident intergroup differences in global cognitive performance between ε4 carriers and non-carriers (P = 0.015). APOE ε4 carriers had lower cognitive test scores than non-carriers in all seven cognitive domains, including fluency (SMD = -0.51, 95% CI = [-0.76, -0.25], P < 0.001, k = 4, I2 = 0%), learning (SMD = -0.52, 95% CI = [-0.75, -0.28], P < 0.001, k = 5, I2 = 0%), executive function (SMD = -0.41, 95% CI = [-0.59, -0.23], P < 0.001, k = 8, I2 = 0%), memory (SMD = -0.41, 95% CI = [-0.61, -0.20], P < 0.001, k = 10, I2 = 36%), attention/working memory (SMD = -0.34, 95% CI = [-0.54, -0.14], P = 0.001, k = 6, I2 = 0%), speed of information processing (SMD = -0.34, 95% CI = [-0.53, -0.16], P < 0.001, k = 8, I2 = 0%), and motor function (SMD = -0.19, 95% CI = [-0.38, -0.01], P = 0.04, k = 7, I2 = 0%). CONCLUSIONS: Our meta-analysis provides significant evidence that APOE ε4 is a risk genotype for HIV-associated cognitive impairment, especially in cognitive domains of fluency, learning, executive function, and memory. Moreover, the impairment is sex specific. META ANALYSIS REGISTRATION: PROSPERO, CRD 42021257775.

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Background: The use of post-exposure prophylaxis (PEP) is effective in reducing HIV risk, but it is underused by men who have sex with men (MSM) due to certain psychological and sociostructural factors. This article assessed the awareness and use of PEP among MSM in an effort to increase the visibility and uptake of PEP among at-risk populations. Methods: We conducted a systematic literature search of the PubMed, Web of Science, PsycINFO, and Google Scholar electronic databases. Studies were screened for inclusion, and relevant data were abstracted, assessed for bias, and synthesized. Pooled effect estimates were calculated using random effects meta-analysis, meta-regression and subgroup analysis, and a qualitative review and risk of bias assessment were performed (PROSPERO, CRD42019123815). Results: Twenty eligible studies involving 12,579 MSM were included in the meta-analysis. The pooled estimate of the proportions of MSM who were aware of PEP was modest at 59.9% (95% CI: 50.5~68.7) and that of MSM who previously used PEP was very low at 4.9% (95% CI: 2.4~9.8). PEP awareness showed no clear change over time, while PEP use significantly changed over time. Multiple factors affected awareness, including educational attainment, race/ethnicity, levels of HIV stigma, access to condoms, and so on. Many factors could potentially impede or facilitate the use of PEP, such as income, lack of PEP information, and partnership. Conclusion: We observed that PEP is an underused HIV prevention strategy among MSM and that once MSM become aware of PEP, the majority are willing to use it if they are supported appropriately in terms of a range of individual, social, and structural barriers. Systematic Review Registration: http://www.cdr.york.ac.uk/prospero, PROSPERO [CRD42019123815].

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Bacteria are critical ecosystem drivers in both aquatic and terrestrial ecosystems. However, our understanding of the mechanisms generating and maintaining biodiversity on large spatial scales remains limited, especially mechanisms involving rare taxa in soil ecosystems. In the present study we took paddy soils in China as model ecosystems and studied the ecological diversity and assembly mechanisms of both the rare and abundant bacterial subcommunities. We collected 339 paddy soil samples from 113 sites across 19 Chinese provinces that span distances of up to 3869 km. The bacterial community was characterized by high-throughput sequencing of the 16S rRNA gene. The α-diversity of rare and abundant subcommunities showed opposite quadratic correlations with the key environmental factor soil pH. Rare taxa exhibited a stronger distance-decay relationship than the abundant subcommunity. Moreover, deterministic selection processes dominated in the assembly of the abundant subcommunity while stochastic processes dominated in that of the rare subcommunity based on both variation partitioning analysis and the phylogenetic null model. Soil pH was also the main deterministic factor driving the geographical distributions of both the rare and abundant subcommunity. Besides, mean annul temperature and soil texture were also found to be important factors affecting the biogeography and diversity patterns of abundant and rare subcommunities. These results indicate that the mechanisms generating and maintaining the diversity of the abundant and rare subcommunities were totally different in paddy soils, suggesting that these two subcommunities may respond differently to future environmental change.

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Deducing soil cadmium (Cd) safety thresholds should be different for rice cultivars with different capacities to accumulate Cd to guarantee safe rice production in China. This study developed prediction models based on soil properties and deduced soil safety thresholds for Cd translocation from thirty-three paddy soils by two contrasting rice cultivars, Yelicanghua (high Cd accumulator, HCd) and Longhuamaohu (low Cd accumulator, LCd). A total of 330 paired field validation samples were used to examine the accuracy of prediction models and soil safety thresholds. The average soil Cd concentration was 0.26 (range 0.057-0.72) mg kg-1. The average brown rice Cd concentrations were 0.14 (0.043-0.55) mg kg-1 in HCd and 0.024 (0.007-0.15) mg kg-1 in LCd in 2017, with corresponding values of 0.16 (0.016-0.66) and 0.027 (0.009-0.10) mg kg-1 in 2018. Soil total Cd and pH were the two most important variables exhibiting direct effects on Cd concentrations in HCd, explaining 66% of the variance across the 33 soils. Soil total Cd, pH and organic carbon (OC) were the three most important variables in LCd, explaining 75% of the variance. Soil safety thresholds ranged from 0.27 to 1.00 mg kg-1 for HCd and from 4.52 to 46.9 mg kg-1 for LCd with pH ranging from 4.5 to 8.0. The validation results suggest ∼60% for HCd or the current soil quality standard (SQS) and 88% for LCd of the validation samples were suitable to meet the food quality standard (FQS), with 6.4% and 12%, respectively, of the validation soils unsuitable for rice cultivation. The current Chinese SQS is too strict for LCd which may be grown safely in moderately polluted soils and the derivation of soil thresholds should therefore consider the abilities of different cultivars to accumulate Cd.

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In general, development of adequately complex mathematical models, such as deep neural networks, can be an effective way to improve the accuracy of learning models. However, this is achieved at the cost of reduced post-hoc model interpretability, because what is learned by the model can become less intelligible and tractable to humans as the model complexity increases. In this paper, we target a similarity learning task in the context of image retrieval, with a focus on the model interpretability issue. An effective similarity neural network (SNN) is proposed to offer not only to seek robust retrieval performance but also to achieve satisfactory post-hoc interpretability. The network is designed by linking the neuron architecture with the organization of a concept tree and by formulating neuron operations to pass similarity information between concepts. Various ways of understanding and visualizing what is learned by the SNN neurons are proposed. We also exhaustively evaluate the proposed approach using a number of relevant datasets against a number of state-of-the-art approaches to demonstrate the effectiveness of the proposed network. Our results show that the proposed approach can offer superior performance when compared against state-of-the-art approaches. Neuron visualization results are demonstrated to support the understanding of the trained neurons.

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The precise combination of image sensor and micro-lens array enables light-field cameras to record both angular and spatial information of incoming light, therefore, one can calculate disparity and depth from one single light-field image captured by one single light-field camera. In turn, 3D models of the recorded objects can be recovered, which means a 3D measurement system can be built using a light-field camera. However, reflective and texture-less areas in light-field images have complicated conditions, making it hard to correctly calculate disparity with existing algorithms. To tackle this problem, we introduce a novel end-to-end network VommaNet to retrieve multi-scale features from reflective and texture-less regions for accurate disparity estimation. Meanwhile, our network has achieved similar or better performance in other regions for both synthetic light-field images and real-world data compared to the state-of-the-art algorithms.

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Rapid industrialization and urbanization have accelerated the contamination of paddy soils with potentially toxic elements (PTEs). However, the status and the key factors responsible for the geographical variation in PTE concentrations in rice remain poorly understood. Here, a total of 113 pairs of soil and rice plant samples were collected from 19 provinces in four major rice producing areas of China to assess the geographical variation in total arsenic (As), cadmium (Cd) and lead (Pb) concentrations in the soil-rice system. Average total concentrations of As, Cd and Pb were 11.8, 0.45 and 25.7 mg kg-1, respectively, in the soils and 0.089, 0.087 and 0.036 mg kg-1 in the polished rice. The national maximum allowable concentrations of total soil As and Cd were exceeded in 6.19 and 33.6% of soils and that of Cd was exceeded in 7.96% of polished rice and no polished rice exceed the Pb limit. The As, Cd and Pb concentrations of rice were significantly and positively correlated (p < 0.05) with their corresponding soil available concentrations rather than with their soil total concentrations. Due to the combined effects of local rice varieties, cultivation of varieties with high Cd translocation factors and high Cd availability in acid soils, the highest rice Cd risk occurred in south China. The Cd concentrations in polished rice exceeded the maximum allowable by 4.0 and 15.8% in uncontaminated and contaminated soils, respectively. Results from 113 fixed samples may represent the actual current As, Cd and Pb status of rice in the main rice production areas nationally as they were very consistent with 574 random samples. In view of the high Cd contamination risk in acid soils of south China, countermeasures are needed to minimize Cd accumulation in rice crops in this region.

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A typical objective of data visualization is to generate low-dimensional plots that maximally convey the information within the data. The visualization output should help the user not only identify the local neighborhood structure of individual samples, but also obtain a global view of the relative positioning and separation between cohorts. Here, we propose a novel visualization framework designed to satisfy these needs. By incorporating additional cohort positioning and discriminative constraints into local neighbor preservation models through the use of computed cohort prototypes, effective control over the arrangements and proximities of data cohorts can be obtained. We introduce various embedding and projection algorithms based on objective functions addressing the different visualization requirements. Their underlying models are optimized effectively using matrix manifold procedures to incorporate the problem constraints. Additionally, to facilitate large-scale applications, a matrix decomposition based model is also proposed to accelerate the computation. The improved capabilities of the new methods are demonstrated using various state-of-the-art dimensionality reduction algorithms. We present many qualitative and quantitative comparisons, on both synthetic problems and real-world tasks of complex text and image data, that show notable improvements over existing techniques.

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A novel dual-drug delivery system (DDDS) for cancer chemotherapy has been established by employing highly purified and mildly oxidized large-inner-diameter multi-walled carbon nanotubes (LID-MWCNTs) as the vector. The LID-MWCNTs were modified with the antitumor drugs, cisplatin (CDDP) and doxorubicin (DOX). CDDP was encapsulated inside the nanotube vectors by a wet-chemical approach while DOX was attached to the external surfaces through non-covalently interaction. The loading efficiencies of CDDP and DOX were as high as 84.56 and 192.67%, respectively. Notably, after CDDP was encapsulated inside the nanotubes, a three-level blocking strategy, which included polyethylene glycol, folic acid and DOX, was employed to block the CDDP exits at different levels. The pH-sensitive release profile of CDDP was demonstrated using a modified characterization method, as well as that of DOX. Finally, the anticancer activity of the DDDS on MCF-7 cells was tested and a synergistic effect was recorded. This work is part of our LID-MWCNTs based drug delivery system studies, and provides a basis for developing a novel comprehensive antitumor treatment that combines chemotherapy and photothermal therapy.

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Citation screening, an integral process within systematic reviews that identifies citations relevant to the underlying research question, is a time-consuming and resource-intensive task. During the screening task, analysts manually assign a label to each citation, to designate whether a citation is eligible for inclusion in the review. Recently, several studies have explored the use of active learning in text classification to reduce the human workload involved in the screening task. However, existing approaches require a significant amount of manually labelled citations for the text classification to achieve a robust performance. In this paper, we propose a semi-supervised method that identifies relevant citations as early as possible in the screening process by exploiting the pairwise similarities between labelled and unlabelled citations to improve the classification performance without additional manual labelling effort. Our approach is based on the hypothesis that similar citations share the same label (e.g., if one citation should be included, then other similar citations should be included also). To calculate the similarity between labelled and unlabelled citations we investigate two different feature spaces, namely a bag-of-words and a spectral embedding based on the bag-of-words. The semi-supervised method propagates the classification codes of manually labelled citations to neighbouring unlabelled citations in the feature space. The automatically labelled citations are combined with the manually labelled citations to form an augmented training set. For evaluation purposes, we apply our method to reviews from clinical and public health. The results show that our semi-supervised method with label propagation achieves statistically significant improvements over two state-of-the-art active learning approaches across both clinical and public health reviews.

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This work is related to the combinatorial data analysis problem of seriation used for data visualization and exploratory analysis. Seriation re-sequences the data, so that more similar samples or objects appear closer together, whereas dissimilar ones are further apart. Despite the large number of current algorithms to realize such re-sequencing, there has not been a systematic way for analyzing the resulting sequences, comparing them, or fusing them to obtain a single unifying one. We propose a new positional proximity measure that evaluates the similarity of two arbitrary sequences based on their agreement on pairwise positional information of the sequenced objects. Furthermore, we present various statistical properties of this measure as well as its normalized version modeled as an instance of the generalized correlation coefficient. Based on this measure, we define a new procedure for consensus seriation that fuses multiple arbitrary sequences based on a quadratic assignment problem formulation and an efficient way of approximating its solution. We also derive theoretical links with other permutation distance functions and present their associated combinatorial optimization forms for consensus tasks. The utility of the proposed contributions is demonstrated through the comparison and fusion of multiple seriation algorithms we have implemented, using many real-world datasets from different application domains.

RESUMEN

In this paper, we study the co-embedding problem of how to map different types of patterns into one common low-dimensional space, given only the associations (relation values) between samples. We conduct a generic analysis to discover the commonalities between existing co-embedding algorithms and indirectly related approaches and investigate possible factors controlling the shapes and distributions of the co-embeddings. The primary contribution of this work is a novel method for computing co-embeddings, termed the automatic co-embedding with adaptive shaping (ACAS) algorithm, based on an efficient transformation of the co-embedding problem. Its advantages include flexible model adaptation to the given data, an economical set of model variables leading to a parametric co-embedding formulation, and a robust model fitting criterion for model optimization based on a quantization procedure. The secondary contribution of this work is the introduction of a set of generic schemes for the qualitative analysis and quantitative assessment of the output of co-embedding algorithms, using existing labeled benchmark datasets. Experiments with synthetic and real-world datasets show that the proposed algorithm is very competitive compared to existing ones.

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