Cotton GhNAC4 promotes drought tolerance by regulating secondary cell wall biosynthesis and ribosomal protein homeostasis.

Drought has a severe impact on the quality and yield of cotton. Deciphering the key genes related to drought tolerance is important for understanding the regulation mechanism of drought stress and breeding drought-tolerant cotton cultivars. Several studies have demonstrated that NAC transcription factors are crucial in the regulation of drought stress, however, the related functional mechanisms are still largely unexplored. Here, we identified that NAC transcription factor GhNAC4 positively regulated drought stress tolerance in cotton. The expression of GhNAC4 was significantly induced by abiotic stress and plant hormones. Silencing of GhNAC4 distinctly impaired the resistance to drought stress and overexpressing GhNAC4 in cotton significantly enhanced the stress tolerance. RNA-seq analysis revealed that overexpression of GhNAC4 enriched the expression of genes associated with the biosynthesis of secondary cell walls and ribosomal proteins. We confirmed that GhNAC4 positively activated the expressions of GhNST1, a master regulator reported previously in secondary cell wall formation, and two ribosomal protein-encoding genes GhRPL12 and GhRPL18p, by directly binding to their promoter regions. Overexpression of GhNAC4 promoted the expression of downstream genes associated with the secondary wall biosynthesis, resulting in enhancing secondary wall deposition in the roots, and silencing of GhRPL12 and GhRPL18p significantly impaired the resistance to drought stress. Taken together, our study reveals a novel pathway mediated by GhNAC4 that promotes secondary cell wall biosynthesis to strengthen secondary wall development and regulates the expression of ribosomal protein-encoding genes to maintain translation stability, which ultimately enhances drought tolerance in cotton.

Suppression of GhGLU19 encoding ß-1,3-glucanase promotes seed germination in cotton.

BACKGROUND: In eudicots, germination begins with water uptake by the quiescent dry seed and is greatly related to the permeability of micropyle enriched callose layers. Once imbibition starts, seeds undergo a cascade of physiological, biochemical, and molecular events to initiate cellular activities. However, the effects of callose on water uptake and following seed metabolic events during germination are largely unknown. Cotton (Gossypium hirsutum) is a eudicot plant with natural fiber and edible oil production for humans. Here, we addressed this question by examining the role of GhGLU19, a gene encoding ß-1,3-glucanase, in cotton seed germination. RESULTS: GhGLU19 belongs to subfamily B and was expressed predominately in imbibed seeds and early seedlings. Compared to wild type, GhGLU19-suppressing and GhGLU19-overexpressing transgenic cotton lines showed the higher and lower seed germination percentage, respectively. Callose was enriched more at inner integument (ii) than that in embryo and seed coat in cotton seeds. In GhGLU19-suppressing lines, callose at ii of cotton seeds was greatly increased and brought about a prolonged water uptake process during imbibition. Both proteomic and transcriptomic analysis revealed that contrary to GhGLU19-overexpressing lines, the glycolysis and pyruvate metabolism was decreased, and abscisic acid (ABA) biosynthesis related genes were downregulated in imbibed seeds of GhGLU19-suppressing lines. Also, endogenous ABA was significantly decreased in GhGLU19-suppressing line while increased in GhGLU19-overexpressing line. CONCLUSIONS: Our results demonstrate that suppression of GhGLU19 improves cotton seed germination via accumulating callose of inner integument, modulating glycolysis and pyruvate metabolism, and decreasing ABA biosynthesis. This study provides a potential way for improving germination percentage in cotton seed production, and other eudicot crops.

Emoji use in China: popularity patterns and changes due to COVID-19.

Emojis are small pictograms that are frequently embedded within micro-texts to more directly express emotional meanings. To understand the changes in the emoji usage of internet users during the COVID-19 outbreak, we analysed a large dataset collected from Weibo, the most popular Twitter-like social media platform in China, from December 1, 2019, to March 20, 2020. The data contained 38,183,194 microblog posts published by 2,239,472 unique users in Wuhan. We calculated the basic statistics of users' usage of emojis, topics, and sentiments and analysed the temporal patterns of emoji occurrence. After examining the emoji co-occurrence structure, we finally explored other factors that may affect individual emoji usage. We found that the COVID-19 outbreak greatly changed the pattern of emoji usage; i.e., both the proportion of posts containing emojis and the ratio of users using emojis declined substantially, while the number of posts remained the same. The daily proportion of Happy emojis significantly declined to approximately 32%, but the proportions of Sad- and Encouraging-related emojis rose to 24% and 34%, respectively. Despite a significant decrease in the number of nodes and edges in the emoji co-occurrence network, the average degree of the network increased from 34 to 39.8, indicating that the diversity of emoji usage increased. Most interestingly, we found that male users were more inclined towards using regular textual language with fewer emojis after the pandemic, suggesting that during public crises, male groups appeared to control their emotional display. In summary, the COVID-19 pandemic remarkably impacted individual sentiments, and the normal pattern of emoji usage tends to change significantly following a public emergency. Supplementary Information: The online version contains supplementary material available at 10.1007/s10489-022-03195-y.

Location inference for hidden population with online text analysis.

BACKGROUND: Understanding the geographic distribution of hidden population, such as men who have sex with men (MSM), sex workers, or injecting drug users, are of great importance for the adequate deployment of intervention strategies and public health decision making. However, due to the hard-to-access properties, e.g., lack of a sampling frame, sensitivity issue, reporting error, etc., traditional survey methods are largely limited when studying such populations. With data extracted from the very active online community of MSM in China, in this study we adopt and develop location inferring methods to achieve a high-resolution mapping of users in this community at national level. METHODS: We collect a comprehensive dataset from the largest sub-community related to MSM topics in Baidu Tieba, covering 628,360 MSM-related users. Based on users' publicly available posts, we evaluate and compare the performances of mainstream location inference algorithms on the online locating problem of Chinese MSM population. To improve the inference accuracy, other approaches in natural language processing are introduced into the location extraction, such as context analysis and pattern recognition. In addition, we develop a hybrid voting algorithm (HVA-LI) by allowing different approaches to vote to determine the best inference results, which guarantees a more effective way on location inference for hidden population. RESULTS: By comparing the performances of popular inference algorithms, we find that the classic gazetteer-based algorithm has achieved better results. And in the HVA-LI algorithms, the hybrid algorithm consisting of the simple gazetteer-based method and named entity recognition (NER) is proven to be the best to deal with inferring users' locations disclosed in short texts on online communities, improving the inferring accuracy from 50.3 to 71.3% on the MSM-related dataset. CONCLUSIONS: In this study, we have explored the possibility of location inferring by analyzing textual content posted by online users. A more effective hybrid algorithm, i.e., the Gazetteer & NER algorithm is proposed, which is conducive to overcoming the sparse location labeling problem in user profiles, and can be extended to the inference of geo-statistics for other hidden populations.

Analyzing hidden populations online: topic, emotion, and social network of HIV-related users in the largest Chinese online community.

BACKGROUND: Traditional survey methods are limited in the study of hidden populations due to the hard to access properties, including lack of a sampling frame, sensitivity issue, reporting error, small sample size, etc. The rapid increase of online communities, of which members interact with others via the Internet, have generated large amounts of data, offering new opportunities for understanding hidden populations with unprecedented sample sizes and richness of information. In this study, we try to understand the multidimensional characteristics of a hidden population by analyzing the massive data generated in the online community. METHODS: By elaborately designing crawlers, we retrieved a complete dataset from the "HIV bar," the largest bar related to HIV on the Baidu Tieba platform, for all records from January 2005 to August 2016. Through natural language processing and social network analysis, we explored the psychology, behavior and demand of online HIV population and examined the network community structure. RESULTS: In HIV communities, the average topic similarity among members is positively correlated to network efficiency (r = 0.70, p < 0.001), indicating that the closer the social distance between members of the community, the more similar their topics. The proportion of negative users in each community is around 60%, weakly correlated with community size (r = 0.25, p = 0.002). It is found that users suspecting initial HIV infection or first in contact with high-risk behaviors tend to seek help and advice on the social networking platform, rather than immediately going to a hospital for blood tests. CONCLUSIONS: Online communities have generated copious amounts of data offering new opportunities for understanding hidden populations with unprecedented sample sizes and richness of information. It is recommended that support through online services for HIV/AIDS consultation and diagnosis be improved to avoid privacy concerns and social discrimination in China.

Nonrepresentativeness of Human Mobility Data and its Impact on Modeling Dynamics of the COVID-19 Pandemic: Systematic Evaluation.

BACKGROUND: In recent years, a range of novel smartphone-derived data streams about human mobility have become available on a near-real-time basis. These data have been used, for example, to perform traffic forecasting and epidemic modeling. During the COVID-19 pandemic in particular, human travel behavior has been considered a key component of epidemiological modeling to provide more reliable estimates about the volumes of the pandemic's importation and transmission routes, or to identify hot spots. However, nearly universally in the literature, the representativeness of these data, how they relate to the underlying real-world human mobility, has been overlooked. This disconnect between data and reality is especially relevant in the case of socially disadvantaged minorities. OBJECTIVE: The objective of this study is to illustrate the nonrepresentativeness of data on human mobility and the impact of this nonrepresentativeness on modeling dynamics of the epidemic. This study systematically evaluates how real-world travel flows differ from census-based estimations, especially in the case of socially disadvantaged minorities, such as older adults and women, and further measures biases introduced by this difference in epidemiological studies. METHODS: To understand the demographic composition of population movements, a nationwide mobility data set from 318 million mobile phone users in China from January 1 to February 29, 2020, was curated. Specifically, we quantified the disparity in the population composition between actual migrations and resident composition according to census data, and shows how this nonrepresentativeness impacts epidemiological modeling by constructing an age-structured SEIR (Susceptible-Exposed-Infected- Recovered) model of COVID-19 transmission. RESULTS: We found a significant difference in the demographic composition between those who travel and the overall population. In the population flows, 59% (n=20,067,526) of travelers are young and 36% (n=12,210,565) of them are middle-aged (P<.001), which is completely different from the overall adult population composition of China (where 36% of individuals are young and 40% of them are middle-aged). This difference would introduce a striking bias in epidemiological studies: the estimation of maximum daily infections differs nearly 3 times, and the peak time has a large gap of 46 days. CONCLUSIONS: The difference between actual migrations and resident composition strongly impacts outcomes of epidemiological forecasts, which typically assume that flows represent underlying demographics. Our findings imply that it is necessary to measure and quantify the inherent biases related to nonrepresentativeness for accurate epidemiological surveillance and forecasting.

Obstructive Sleep Apnea Syndrome Exacerbates NASH Progression via Selective Autophagy-Mediated Eepd1 Degradation.

Obstructive sleep apnea syndrome (OSAS), characterized by chronic intermittent hypoxia (CIH), is an independent risk factor for aggravating non-alcoholic steatohepatitis (NASH). The prevailing mouse model employed in CIH research is inadequate for the comprehensive exploration of the impact of CIH on NASH development due to reduced food intake observed in CIH-exposed mice, which deviates from human responses. To address this issue, a pair-feeding investigation with CIH-exposed and normoxia-exposed mice is conducted. It is revealed that CIH exposure aggravates DNA damage, leading to hepatic fibrosis and inflammation. The analysis of genome-wide association study (GWAS) data also discloses the association between Eepd1, a DNA repair enzyme, and OSAS. Furthermore, it is revealed that CIH triggered selective autophagy, leading to the autophagic degradation of Eepd1, thereby exacerbating DNA damage in hepatocytes. Notably, Eepd1 liver-specific knockout mice exhibit aggravated hepatic DNA damage and further progression of NASH. To identify a therapeutic approach for CIH-induced NASH, a drug screening is conducted and it is found that Retigabine dihydrochloride suppresses CIH-mediated Eepd1 degradation, leading to alleviated DNA damage in hepatocytes. These findings imply that targeting CIH-mediated Eepd1 degradation can be an adjunctive approach in the treatment of NASH exacerbated by OSAS.

Coagulation Factor VII Fine-tunes Hepatic Steatosis by Blocking AKT-CD36-Mediated Fatty Acid Uptake.

Nonalcoholic fatty liver disease (NAFLD) is considered a risk factor for cardiovascular and cerebrovascular disease owing to its close association with coagulant disturbances. However, the precise biological functions and mechanisms that connect coagulation factors to NAFLD pathology remain inadequately understood. Herein, with unbiased bioinformatics analyses followed by functional testing, we demonstrate that hepatic expression of coagulation factor VII (FVII) decreases in patients and mice with NAFLD/nonalcoholic steatohepatitis (NASH). By using adenovirus-mediated F7-knockdown and hepatocyte-specific F7-knockout mouse models, our mechanistic investigations unveil a noncoagulant function of hepatic FVII in mitigating lipid accumulation and lipotoxicity. This protective effect is achieved through the suppression of fatty acid uptake, orchestrated via the AKT-CD36 pathway. Interestingly, intracellular FVII directly interacts with AKT and PP2A, thereby promoting their association and triggering the dephosphorylation of AKT. Therapeutic intervention through adenovirus-mediated liver-specific overexpression of F7 results in noteworthy improvements in liver steatosis, inflammation, injury, and fibrosis in severely afflicted NAFLD mice. In conclusion, our findings highlight coagulation factor FVII as a critical regulator of hepatic steatosis and a potential target for the treatment of NAFLD and NASH.

Human Post-Translational SUMOylation Modification of SARS-CoV-2 Nucleocapsid Protein Enhances Its Interaction Affinity with Itself and Plays a Critical Role in Its Nuclear Translocation.

Viruses, such as Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), infect hosts and take advantage of host cellular machinery for genome replication and new virion production. Identifying and elucidating host pathways for viral infection is critical for understanding the development of the viral life cycle and novel therapeutics. The SARS-CoV-2 N protein is critical for viral RNA (vRNA) genome packaging in new virion formation. Using our quantitative Förster energy transfer/Mass spectrometry (qFRET/MS) coupled method and immunofluorescence imaging, we identified three SUMOylation sites of the SARS-CoV-2 N protein. We found that (1) Small Ubiquitin-like modifier (SUMO) modification in Nucleocapsid (N) protein interaction affinity increased, leading to enhanced oligomerization of the N protein; (2) one of the identified SUMOylation sites, K65, is critical for its nuclear translocation. These results suggest that the host human SUMOylation pathway may be critical for N protein functions in viral replication and pathology in vivo. Thus, blocking essential host pathways could provide a novel strategy for future anti-viral therapeutics development, such as for SARS-CoV-2 and other viruses.

Betaine-homocysteine methyltransferase promotes adipocyte commitment and insulin resistance via p38 MAPK/Smad signaling.

OBJECTIVE: Betaine-homocysteine methyltransferase (Bhmt) belongs to the family of methyltransferases and is involved in the one-carbon metabolic cycle, which is associated with the risk of diabetes and adiposity. This study aimed to explore whether Bhmt participated in the development of obesity or its associated diabetes, as well as the mechanism involved. METHODS: The expression levels of Bhmt were examined in stromal vascular fraction cells and mature adipocytes in obesity and nonobesity. Knockdown and overexpression of Bhmt in C3H10T1/2 cells were used to investigate Bhmt's function in adipogenesis. Bhmt's role in vivo was analyzed using an adenovirus-expressing system and a high-fat diet-induced obesity mouse model. RESULTS: Bhmt was highly expressed in stromal vascular fraction cells rather than mature adipocytes of adipose tissue and was upregulated in adipose tissue in obesity and C3H10T1/2-commited preadipocytes. Overexpression of Bhmt promoted adipocyte commitment and differentiation in vitro and exacerbated adipose tissue expansion in vivo, with a concomitant increase in insulin resistance, whereas Bhmt silencing exhibited opposite effects. Mechanistically, Bhmt-induced adipose expansion was mediated by stimulating the p38 MAPK/Smad pathway. CONCLUSIONS: The findings of this study highlight the obesogenic and diabetogenic role of adipocytic Bhmt and propose Bhmt as a promising therapeutic target for obesity and obesity-related diabetes.

Targeted trapping of endogenous endothelial progenitor cells for myocardial ischemic injury repair through neutrophil-mediated SPIO nanoparticle-conjugated CD34 antibody delivery and imaging.

Endothelia progenitor cell (EPC)-based revascularization therapies have shown promise for the treatment of myocardial ischemic injury. However, applications and efficacy are limited by the relatively inefficient recruitment of endogenous EPCs to the ischemic area, while implantation of exogenous EPCs carries the risk of tumorigenicity. In this study, we developed a therapeutic protocol that relies on the capacity of neutrophils (NEs) to target lesions and release preloaded EPC-binding molecules for high efficiency capture. Neutrophils were loaded with superparamagnetic iron oxide nanoparticles conjugated to an antibody against the EPC surface marker CD34 (SPIO-antiCD34/NEs), and the therapeutic efficacy in ischemic mouse heart following SPIO-antiCD34/NEs injection was monitored by SPIO-enhanced magnetic resonance imaging (MRI). These SPIO-antiCD34/NEs exhibited unimpaired cell viability, superoxide generation, and chemotaxis in vitro as well as satisfactory biocompatibility in vivo. In a mouse model of acute myocardial infarction (MI), SPIO-antiCD34 accumulation could be observed 0.5 h after intravenous injection of SPIO-antiCD34/NEs. Moreover, the degree of CD133+ EPC accumulation at MI sites was three-fold higher than in control MI model mice, while ensuing microvessel density was roughly two-fold higher than controls and left ventricular ejection fraction was > 50%. Therapeutic cell biodistribution, MI site targeting, and treatment effects were confirmed by SPIO-enhanced MRI. This study offers a new strategy to improve the endogenous EPC-based myocardial ischemic injury repair through NEs mediated SPIO nanoparticle conjugated CD34 antibody delivery and imaging. STATEMENT OF SIGNIFICANCE: The efficacy of endogenous endothelial progenitor cell (EPC)-based cardiovascular repair therapy for ischemic heart damage is limited by relatively low EPC accumulation at the target site. We have developed a method to improve EPC capture by exploiting the strong targeting ability of neutrophils (NEs) to ischemic inflammatory foci and the capacity of these treated cells to release of preloaded cargo with EPC-binding affinity. Briefly, NEs were loaded with superparamagnetic iron oxide nanoparticles conjugated to an antibody against the EPC surface protein CD34 (SPIO-antiCD34). Thus, we explored sites targeting with nanocomposites cargo for non-invasive EPCs interception and therapy tracking. We demonstrate that SPIO-antiCD34 released from NEs can effectively capture endogenous EPCs and thereby promote heart revascularization and functional recovery in mice. Moreover, the entire process can be monitored by SPIO-enhanced magnetic resonance imaging including therapeutic cell biodistribution, myocardial infarction site targeting, and tissue repair.

Combining Preoperative and Postoperative Inflammatory Indicators Can Better Predict the Recurrence of Hepatocellular Carcinoma After Partial Hepatectomy.

PURPOSE: Previous studies have shown that various preoperative inflammatory indicators can predict the prognosis of hepatocellular carcinoma (HCC), but the role of postoperative inflammatory indicators remains unclear. This study aimed to explore the prognostic value of postoperative inflammatory indicators and whether combining preoperative and postoperative inflammatory indicators can improve the predictive performance of the prognostic model. PATIENTS AND METHODS: Eighty-eight patients with primary HCC were included in this study. A preoperative model, postoperative model, and combined model that integrated preoperative and postoperative inflammatory indicators were established. The prognostic value of the models was evaluated by the area under the curve of time-dependent receiver operating characteristic curves (td-AUC). RESULTS: Multivariate analysis of preoperative and postoperative inflammatory indicators and clinicopathological indicators found that tumor number, alpha-fetoprotein (AFP) level, and the preoperative platelet-lymphocyte ratio (prePLR), preoperative prognostic nutritional index (prePNI), and postoperative neutrophil-lymphocyte ratio (postNLR) were independent prognostic factors for the disease-free survival. The prognostic efficacy of the postNLR at 2 years and 3 years was better than that of tumor number, AFP level, and the prePLR, and prePNI. The combined model had higher td-AUC values than the preoperative model, postoperative model, American Joint Committee on Cancer 8th edition stage, and Barcelona Clinic Liver Cancer stage at 2 years (0.814 vs 0.754, 0.765, 0.513 and 0.527, respectively), and 3 years (0.786 vs 0.749, 0.753, 0.509 and 0.529, respectively). The predictive performance of the combined model was better than that of the preoperative model, postoperative model, and traditional clinical stage. CONCLUSION: Postoperative inflammatory indicators were valuable prognostic indicators. The combination of preoperative and postoperative inflammatory indicators improved the predictive performance of the prognostic model. We should pay more attention to postoperative inflammatory indicators.

VEGF Family Gene Expression as Prognostic Biomarkers for Alzheimer's Disease and Primary Liver Cancer.

BACKGROUND: To analyze the expression of vascular endothelial growth factor (VEGF) in hepatocellular carcinoma (HCC) and cognitive impairment, explore the relationship between the expression of VEGF family genes and prognosis of patients with HCC, and evaluate the predictive ability of VEGF in cognitive impairment using computerized methods. METHODS: VEGF expression in liver cancer tissues and normal tissues was analyzed using bioinformatics methods. The Kaplan-Meier survival analysis method was also used to analyze the relationship between VEGF expression and the prognosis of patients with HCC. Furthermore, immune infiltration assessment and gene set enrichment analysis were performed. Meanwhile, the differential expression of VEGF family genes between patients with Alzheimer's disease (AD) and healthy controls was also checked. RESULTS: Based on The Cancer Genome Atlas (TCGA) database, the VEGF family genes (VEFGA, VEGFB, VEGFC, and VEGFD) were highly expressed in cancer tissues and were significantly associated with poor prognosis in HCC. In HCC, the VEGF family genes showed significant heterogeneity in their functional and immune infiltration characteristics. Finally, VEGF family genes were identified as prognostic biomarkers in AD and risk prediction markers in HCC. CONCLUSIONS: VEGF is highly expressed in patients with HCC and lowly expressed in patients with AD. VEGF has opposite opposing roles in the treatment of tumors and cognitive impairment.

The phytochemical hyperforin triggers thermogenesis in adipose tissue via a Dlat-AMPK signaling axis to curb obesity.

Stimulation of adipose tissue thermogenesis is regarded as a promising avenue in the treatment of obesity. However, pharmacologic engagement of this process has proven difficult. Using the Connectivity Map (CMap) approach, we identified the phytochemical hyperforin (HPF) as an anti-obesity agent. We found that HPF efficiently promoted thermogenesis by stimulating AMPK and PGC-1α via a Ucp1-dependent pathway. Using LiP-SMap (limited proteolysis-mass spectrometry) combined with a microscale thermophoresis assay and molecular docking analysis, we confirmed dihydrolipoamide S-acetyltransferase (Dlat) as a direct molecular target of HPF. Ablation of Dlat significantly attenuated HPF-mediated adipose tissue browning both in vitro and in vivo. Furthermore, genome-wide association study analysis indicated that a variation in DLAT is significantly associated with obesity in humans. These findings suggest that HPF is a promising lead compound in the pursuit of a pharmacological approach to promote energy expenditure in the treatment of obesity.

Mobility in China, 2020: a tale of four phases.

2020 was an unprecedented year, with rapid and drastic changes in human mobility due to the COVID-19 pandemic. To understand the variation in commuting patterns among the Chinese population across stable and unstable periods, we used nationwide mobility data from 318 million mobile phone users in China to examine the extreme fluctuations of population movements in 2020, ranging from the Lunar New Year travel season (chunyun), to the exceptional calm of COVID-19 lockdown, and then to the recovery period. We observed that cross-city movements, which increased substantially in chunyun and then dropped sharply during the lockdown, are primarily dependent on travel distance and the socio-economic development of cities. Following the Lunar New Year holiday, national mobility remained low until mid-February, and COVID-19 interventions delayed more than 72.89 million people returning to large cities. Mobility network analysis revealed clusters of highly connected cities, conforming to the social-economic division of urban agglomerations in China. While the mass migration back to large cities was delayed, smaller cities connected more densely to form new clusters. During the recovery period after travel restrictions were lifted, the netflows of over 55% city pairs reversed in direction compared to before the lockdown. These findings offer the most comprehensive picture of Chinese mobility at fine resolution across various scenarios in China and are of critical importance for decision making regarding future public-health-emergency response, transportation planning and regional economic development, among others.

Dynamic prediction of overall survival: a retrospective analysis on 979 patients with Ewing sarcoma from the German registry.

OBJECTIVES: This study aimed at developing a dynamic prediction model for patients with Ewing sarcoma (ES) to provide predictions at different follow-up times. During follow-up, disease-related information becomes available, which has an impact on a patient's prognosis. Many prediction models include predictors available at baseline and do not consider the evolution of disease over time. SETTING: In the analysis, 979 patients with ES from the Gesellschaft für Pädiatrische Onkologie und Hämatologie registry, who underwent surgery and treatment between 1999 and 2009, were included. DESIGN: A dynamic prediction model was developed to predict updated 5-year survival probabilities from different prediction time points during follow-up. Time-dependent variables, such as local recurrence (LR) and distant metastasis (DM), as well as covariates measured at baseline, were included in the model. The time effects of covariates were investigated by using interaction terms between each variable and time. RESULTS: Developing LR, DM in the lungs (DMp) or extrapulmonary DM (DMo) has a strong effect on the probability of surviving an additional 5 years with HRs and 95% CIs equal to 20.881 (14.365 to 30.353), 6.759 (4.465 to 10.230) and 17.532 (13.210 to 23.268), respectively. The effects of primary tumour location, postoperative radiotherapy (PORT), histological response and disease extent at diagnosis on survival were found to change over time. The HR of PORT versus no PORT at the time of surgery is equal to 0.774 (0.594 to 1.008). One year after surgery, the HR is equal to 1.091 (0.851 to 1.397). CONCLUSIONS: The time-varying effects of several baseline variables, as well as the strong impact of time-dependent variables, show the importance of including updated information collected during follow-up in the prediction model to provide accurate predictions of survival.

Network Evolution of a Large Online MSM Dating Community: 2005-2018.

Due to multiple sexual partners and low rates of condom use, the HIV infection rate among MSM (men who have sex with men) is much higher than that of the general population. In order to analyze the characteristics of online activities of MSM, and to understand the evolution of their social networks, in this study we collect a comprehensive dataset, covering the period from January 2005 to June 2018, from the largest Chinese online community, Baidu Tieba. We build an online dating network for MSM-related individuals in the gay-bar community, and analyze the network from static and dynamic aspects. It is found that there is a strong homophily regarding the cities where users reside when developing interactions with others, and that most network measurements tend to be stable at the later stages of evolution, while the size of the largest community fluctuates. This is an indication that the network is formed of rapidly flexible interactions which changes quickly. In comparison with studies on heterosexual networks, we find that the MSM dating network shows differences in many aspects, such as the positive degree-degree correlation and high clustering coefficient, suggesting different thinking and measures should be taken in the policy making of public health management towards the MSM population.

Temporal Characteristics of the Chinese Aviation Network and their Effects on the Spread of Infectious Diseases.

Aviation transportation systems have developed rapidly in recent years and have become a focus for research on the modeling of epidemics. However, despite the number of studies on aggregated topological structures and their effects on the spread of disease, the temporal sequence of flights that connect different airports have not been examined. In this study, to analyze the temporal pattern of the Chinese Aviation Network (CAN), we obtain a time series of topological statistics through sliding the temporal CAN with an hourly time window. In addition, we build two types of Susceptible-Infectious (SI) spreading models to study the effects of linking sequence and temporal duration on the spread of diseases. The results reveal that the absence of links formed by flights without alternatives at dawn and night causes a significant decrease in the centralization of the network. The temporal sparsity of linking sequence slows down the spread of disease on CAN, and the duration of flights intensifies the sensitiveness of CAN to targeted infection. The results are of great significance for further understanding of the aviation network and the dynamic process, such as the propagation of delay.

Imaging through the pupal case of Drosophila melanogaster.

The longstanding use of Drosophila as a model for cell and developmental biology has yielded an array of tools. Together, these techniques have enabled analysis of cell and developmental biology from a variety of methodological angles. Live imaging is an emerging method for observing dynamic cell processes, such as cell division or cell motility. Having isolated mutations in uncharacterized putative cell cycle proteins it became essential to observe mitosis in situ using live imaging. Most live imaging studies in Drosophila have focused on the embryonic stages that are accessible to manipulation and observation because of their small size and optical clarity. However, in these stages the cell cycle is unusual in that it lacks one or both of the gap phases. By contrast, cells of the pupal wing of Drosophila have a typical cell cycle and undergo a period of rapid mitosis spanning about 20 hr of pupal development. It is easy to identify and isolate pupae of the appropriate stage to catch mitosis in situ. Mounting intact pupae provided the best combination of tractability and durability during imaging, allowing experiments to run for several hours with minimal impact on cell and animal viability. The method allows observation of features as small as, or smaller than, fly chromosomes. Adjustment of microscope settings and the details of mounting, allowed extension of the preparation to visualize membrane dynamics of adjacent cells and fluorescently labeled proteins such as tubulin. This method works for all tested fluorescent proteins and can capture submicron scale features over a variety of time scales. While limited to the outer 20 µm of the pupa with a conventional confocal microscope, this approach to observing protein and cellular dynamics in pupal tissues in vivo may be generally useful in the study of cell and developmental biology in these tissues.