[Value of peripheral blood rare cell EGFR gene amplification detection in the evaluation of benign and malignant pulmonary nodules].

Objective: To explore the value of detection of epidermal growth factor receptor (EGFR) gene amplification in peripheral blood rare cells in the assessment of benign and malignant pulmonary nodules. Methods: A total of 262 patients with pulmonary nodules were selected as the retrospectively study subjects from the Second Affiliated Hospital of Army Military Medical University and Peking Union Medical College Hospital from July 2022 to August 2023. There were 98 males and 164 females, with the age range from 16 to 79 (52.1±12.1) years. The EGFR gene amplification testing was performed on the rare cells enriched from patients' peripheral blood, and the clinical manifestations, CT imaging features, histopathological and/or pathological cytological confirmed results of patients were collected. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value of the method of detection of EGFR gene amplification in peripheral blood rare cells, and its diagnostic efficacy was evaluated. Results: Among the 262 patients, 143 were malignant pulmonary nodules and 119 were benign pulmonary nodules. The differences between malignant pulmonary nodules and benign pulmonary nodules in nodule diameter and nodule density were statistically significant (both P<0.001), while the differences in age, gender and nodule number were not statistically significant (all P>0.05). The number [M (Q1, Q3)] of EGFR gene amplification positive rare cells in patients with malignant pulmonary nodule was 8 (6, 11), which was higher than that in patients with benign pulmonary nodule [2 (1, 4), P<0.001]. The ROC curve results showed that when the optimal cut-off value was 5 (that was, the number of EGFR gene amplification positive rare cells was>5), the area under the curve (AUC) of the detection of EGFR gene amplification in peripheral blood rare cells for discrimination of benign and malignant pulmonary lesions was 0.816 (95%CI: 0.761-0.870), with a sensitivity of 83.2%, a specificity of 80.7%, and an accuracy of 82.1%. Based on the analysis of the diameter of the nodules, the AUC for distinguishing between benign and malignant pulmonary nodules with diameter 5-9 mm and 10-30 mm was 0.797 (95%CI: 0.707-0.887) and 0.809 (95%CI: 0.669-0.949), respectively, with sensitivity, specificity and accuracy reached 75% or above. Based on the analysis of nodule density, the AUC for distinguishing between benign and malignant solid nodule and subsolid nodule was 0.845 (95%CI: 0.751-0.939) and 0.790 (95%CI: 0.701-0.880), respectively, with sensitivity, specificity and accuracy reached 75% or above. Based on the analysis of nodule number, the AUC for distinguishing between benign and malignant solitary pulmonary nodule and multiple pulmonary nodule was 0.830 (95%CI: 0.696-0.965) and 0.817 (95%CI: 0.758-0.877), respectively, with sensitivity, specificity and accuracy reached 80% or above. Conclusion: The detection of EGFR gene amplification in peripheral blood rare cells contributes to the evaluation of benign and malignant pulmonary nodules, and can be used in the auxiliary diagnosis of benign and malignant pulmonary nodules.

[Analysis on dynamical mechanism of multi outbreaks of COVID-19].

Objective: In the context of COVID-19 pandemic, the epidemic severities, non-pharmaceutical intervention intensities, individual behavior patterns and vaccination coverage vary with countries in the world. China has experienced a long period without indigenous cases, unfortunately, multi local outbreaks caused by imported cases and other factors have been reported, posing great challenges to COVID-19 prevention and control in China. Thus it is necessary to explore the mechanisms of the re-emerged COVID-19 epidemics and their differences. Methods: Based on susceptible exposed infectious recovered (SEIR) epidemic dynamics model, we developed a set of novel evolution equations which can describe the dynamic processes of integrated influence of interventions, vaccination coverage and individual behavior changes on the re-emergency of COVID-19 epidemic. We developed methods to calculate the optimal intervention intensity and vaccination rate at which the size of susceptible population can be reduced to less than threshold for the re-emergency of COVID-19 epidemic. Results: If strong interventions or super interventions are lifted too early, even a small cause can lead to the re-emergence of COVID-19 epidemic at different degrees. Moreover, the stronger the early control measures lifted are, the more severe the epidemic is. The individual behavior changes for the susceptibility to the epidemic and the enhancement or lifting of prevention and control measures are key factors to influence the incidence the multi outbreaks of COVID-19. The optimist early intervention measures and timely optimization of vaccination can not only prevent the re-emergency of COVID-19 epidemic, but also effectively lower the peak of the first wave of the epidemic and delay its arrival. Conclusion: The study revealed that factors for the re-emergence of COVID-19 epidemics included the intensity and lifting of interventions, the change of individual behavior to the response of the epidemic, external incentives and the transmissibility of COVID-19.

[Advance on theoretical epidemiology models research of prevention and control of COVID-19].

COVID-19 has brought a significant impact to the global health system, and also opportunities and challenges to epidemiological researches. Theoretical epidemiological models can simulate the process of epidemic in scenarios under different conditions. Therefore, modeling researches can analyze the epidemical trend of COVID-19, predict epidemical risks, and evaluate effects of different control measures and vaccine policies. Theoretical epidemiological modeling researches provide scientific advice for the prevention and control of infectious diseases, and play a crucial role in containing COVID-19 over the past year. In this study, we review the theoretical epidemiological modeling researches on COVID-19 and summarize the role of theoretical epidemiological models in the prevention and control of COVID-19, in order to provide reference for the combination of mathematical modeling and epidemic control.

[Prediction modeling with data fusion and prevention strategy analysis for the COVID-19 outbreak].

Since December 2019, the outbreak of COVID-19 in Wuhan has spread rapidly due to population movement during the Spring Festival holidays. Since January 23rd, 2020, the strategies of containment and contact tracing followed by quarantine and isolation has been implemented extensively in mainland China, and the rates of detection and confirmation have been continuously increased, which have effectively suppressed the rapid spread of the epidemic. In the early stage of the outbreak of COVID-19, it is of great practical significance to analyze the transmission risk of the epidemic and evaluate the effectiveness and timeliness of prevention and control strategies by using mathematical models and combining with a small amount of real-time updated multi-source data. On the basis of our previous research, we systematically introduce how to establish the transmission dynamic models in line with current Chinese prevention and control strategies step by step, according to the different epidemic stages and the improvement of the data. By summarized our modelling and assessing ideas, the model formulations vary from autonomous to non-autonomous dynamic systems, the risk assessment index changes from the basic regeneration number to the effective regeneration number, and the epidemic development and assessment evolve from the early SEIHR transmission model-based dynamics to the recent dynamics which are mainly associated with the variation of the isolated and suspected population sizes.

Endophytic Bacillus velezensis strain B-36 is a potential biocontrol agent against lotus rot caused by Fusarium oxysporum.

AIM: The aim of this study was to screen potential lotus plant endophytic bacterial isolate for effective inhibition against lotus rot causing fungal pathogen Fusarium oxysporum. METHODS AND RESULTS: In this study, endophytic bacteria were isolated from lotus tissues and tested for antagonistic activities against the pathogenic fungus F. oxysporum. Among the putative endophytic Bacillus strains identified, suspensions of the strain B-36 showed the highest inhibition rate against F. oxysporum growth. Pot assays indicated that B-36 was effective in controlling F. oxysporum-inducing lotus rot. However, the control efficiency varied with the inoculation method and concentration, where injection of 800 µl B-36 suspension per plant (2 × 108  CFU per ml) into stems showed the highest control efficiencies of 77·1 and 60·0% for pre-inoculation and post-inoculation. In addition, the colonizing population levels (CPLs) of B-36 on lotus also varied with the inoculation method and concentration, with the highest CPLs, that is, 3·05 and 2·83 log(CFU per gram), being observed on lotus leaves and stems respectively for stem injection of 200 µl per plant. Moreover B-36 showed no noticeable effects on lotus seed germination rate or seedling growth. Finally, B-36 was characterized as Bacillus velezensis based on its morphology, Gram-positive characteristics, as well as its 16S rDNA and gyrB sequences. CONCLUSION: The isolate B-36 can be applied as a biocontrol agent against F. oxysporum-inducing lotus rot. SIGNIFICANCE OF IMPACT OF THE STUDY: The soil-borne fungus F. oxysporum causes lotus rot and severe yield loss, and currently available control methods are very limited. Here we identify a new promising biocontrol agent against lotus rot caused by F. oxysporum.

Impact of individual behaviour change on the spread of emerging infectious diseases.

Human behaviour plays an important role in the spread of emerging infectious diseases, and understanding the influence of behaviour changes on epidemics can be key to improving control efforts. However, how the dynamics of individual behaviour changes affects the development of emerging infectious disease is a key public health issue. To develop different formula for individual behaviour change and introduce how to embed it into a dynamic model of infectious diseases, we choose A/H1N1 and Ebola as typical examples, combined with the epidemic reported cases and media related news reports. Thus, the logistic model with the health belief model is used to determine behaviour decisions through the health belief model constructs. Furthermore, we propose 4 candidate infectious disease models without and with individual behaviour change and use approximate Bayesian computation based on sequential Monte Carlo method for model selection. The main results indicate that the classical compartment model without behaviour change and the model with average rate of behaviour change depicted by an exponential function could fit the observed data best. The results provide a new way on how to choose an infectious disease model to predict the disease prevalence trend or to evaluate the influence of intervention measures on disease control. However, sensitivity analyses indicate that the accumulated number of hospital notifications and deaths could be largely reduced as the rate of behaviour change increases. Therefore, in terms of mitigating emerging infectious diseases, both media publicity focused on how to guide people's behaviour change and positive responses of individuals are critical.

Identification of lipopeptides produced by Bacillus subtilis Czk1 isolated from the aerial roots of rubber trees.

We obtained a strain of Bacillus subtilis, which we named Czk1, from the aerial roots of rubber trees. This bacterial isolate exhibits strong antagonistic activity against Ganoderma pseudoferreum, Phellinus noxius, Helicobasidium compactum, Rigidoporus lignosus, Sphaerostilbe repens, and Colletotrichum gloeosporioides. Our earlier research has shown that the antagonistic activity of a fermentation supernatant Czk1 isolate produces a complex mixture of lipopeptides. In this study, we used methanol to extract crude lipopeptides, purified them using a Sephadex G-25 column, cloned the lipopeptide genes, and analyzed purified fractions by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) to identify the lipopeptides from B. subtilis strain Czk1. The cloned lipopeptide genes included those that encode the enzymes lpa, ituD, sfp, and fenB. The crude lipopeptides were purified and found in five fractions. Further analysis revealed that five fractions of the purified composition contained members of the surfactin, iturin, fengycin, and bacillomycin families of antibiotics. This suggests that these lipopeptides from strain Czk1 have potential as plant disease biocontrol agents.

Characterization of Causal Agents of a Novel Disease Inducing Brown-Black Spots on Tender Tea Leaves in China.

A novel disease characterized by small brown-black spots (1 to 2 mm in diameter) on tender tea leaves (Camellia sinensis) has been observed in many regions of Hubei Province, China, which severely affects the yield and quality of tea. Tea leaf samples with typical symptoms were collected from three major tea-cultivation regions of Hubei, and were subjected to pathogen isolation for etiological analysis. As a result, 34 Pestalotiopsis isolates were obtained from 20 samples, and they were identified as Pestalotiopsis theae (14 isolates), P. camelliae (12), and P. clavispora (8), determined by morphologies and phylogenetic analysis based on internal transcribed spacer, and partial ß-tubulin and translation elongation factor 1-alpha genes. Pathogenicity tests on detached tea leaves showed that no matter what mycelial discs or conidium suspensions were used, inoculation of the Pestalotiopsis fungi could result in small brown-black spots (1 to 2 mm in diameter) on wounded leaves, similar to those observed in the field in the sizes and colors. It also revealed that only P. theae had pathogenicity on unwounded tea leaves, and P. theae and P. clavispora showed significantly higher virulence than P. camelliae. Inoculation test with conidium suspension on intact tea leaves in the field further confirmed that P. theae as the pathogen of brown-black spots. Reisolation of the pathogens from diseased leaves confirmed that the symptom was caused by the inoculation of Pestalotiopsis fungi. The P. theae isolates responsible for brown-black spots were also compared with those for tea gray blight disease in growth rate, pathogenicity, and molecular characteristics in parallel. To our knowledge, this is the first report that the Pestalotiopsis fungi cause brown-black spot disease on tender tea leaves. The results provide important implications for the prevention and management of this economically important disease.

Effects of prolonged anesthesia with dexmedetomidine, fentanyl, or remifentanil on the self-renewal of mouse embryonic stem cells.

Previous study has indicated that exposure to anesthesia in early development leads to neuro-apoptosis and is followed by long-term cognitive dysfunction. Given that larger numbers of pregnant women currently receive anesthesia during the first trimester, we wanted to mimic this process in vitro using mouse embryonic stem cells (mESCs) and to explore how different anesthetics affect the self-renewal of mESCs. In the present study, mESCs were exposed to dexmedetomidine, fentanyl, or remifentanil at clinical concentrations for 48 h. The mESCs were then analyzed for cell proliferation and apoptosis. Furthermore, we used flow cytometry to analyze the cell cycle and quantitative real-time polymerase chain reaction to detect the gene expression during the cell cycle as well as the relevant stemness markers. We found that prolonged anesthesia with dexmedetomidine or fentanyl significantly inhibited mESC proliferation, with fewer cell numbers as well as decreased expression of cyclin B and cyclin E mRNA compared to that in the control group; meanwhile, p21 and RB2 gene expression was increased. Additionally, increases or decreases in the proportion of cells in the G1 and S phases, respectively, were observed in the dexmedetomidine- and fentanyl-treated groups. These anesthetics also repressed the gene expression of mESC stemness makers such as Oct4 and Sox2. However, remifentanil seemed to have no significant influence on the self-renewal of mESCs. These results demonstrated that prolonged anesthesia with dexmedetomidine or fentanyl, but not remifentanil, inhibited mESC proliferation by blocking the G1 to S transition, and repressed the maintenance of mESC stemness.

Mapping of HtNB, a gene conferring non-lesion resistance before heading to Exserohilum turcicum (Pass.), in a maize inbred line derived from the Indonesian variety Bramadi.

The gene HtNB confers non-lesion resistance to the fungal pathogen Exserohilum turcicum in maize. To map this gene, we developed two F2 populations, P111 (resistant line) x HuangZao 4 (susceptible line) and P111 x B73 (susceptible). HtNB was located on chromosome 8.07 bin, flanked by MAC216826-4 and umc2218 at distances of 3.3 and 3.4 cM, respectively. HtNB appears to be a new gene responsible for resistance to northern corn leaf blight. Functions of the genes in the region between umc1384 and umc2218 were predicted. In addition, several genes were found to be related to disease resistance, such as the genes encoding Ser/Thr protein kinase and protein-like leaf senescence.