Quantitative analysis of the genes affecting development of the hypopharyngeal gland in honey bees (Apis mellifera L.)

Royal jelly has many important biological functions, however the molecular mechanism of royal jelly secretion in hypopharyngeal gland (HG) is still not well understood. In our previously study, six genes (SV2C, eIF-4E, PDK1, IMP, cell growth-regulating nucleolar protein and TGF-βR1) have been shown to might be associated with royal jelly secretion. In this study, the relative expression levels of these genes were examined in the hypopharyngeal gland of workers at different developmental stages (nurse, forager and reversed nurse stages). The results indicated that the relative expression levels of SV2C, eIF-4E, IMP, cell growth-regulating nucleolar protein and TGF-βR1 were reversed at reversed nurse stage compared to forager stage. We concluded that these genes are possibly candidates related to hypopharyngeal gland development or royal jelly secretion

ARA-net: an attention-aware retinal atrophy segmentation network coping with fundus images

BackgroundAccurately detecting and segmenting areas of retinal atrophy are paramount for early medical intervention in pathological myopia (PM). However, segmenting retinal atrophic areas based on a two-dimensional (2D) fundus image poses several challenges, such as blurred boundaries, irregular shapes, and size variation. To overcome these challenges, we have proposed an attention-aware retinal atrophy segmentation network (ARA-Net) to segment retinal atrophy areas from the 2D fundus image.MethodsIn particular, the ARA-Net adopts a similar strategy as UNet to perform the area segmentation. Skip self-attention connection (SSA) block, comprising a shortcut and a parallel polarized self-attention (PPSA) block, has been proposed to deal with the challenges of blurred boundaries and irregular shapes of the retinal atrophic region. Further, we have proposed a multi-scale feature flow (MSFF) to challenge the size variation. We have added the flow between the SSA connection blocks, allowing for capturing considerable semantic information to detect retinal atrophy in various area sizes.ResultsThe proposed method has been validated on the Pathological Myopia (PALM) dataset. Experimental results demonstrate that our method yields a high dice coefficient (DICE) of 84.26%, Jaccard index (JAC) of 72.80%, and F1-score of 84.57%, which outperforms other methods significantly.ConclusionOur results have demonstrated that ARA-Net is an effective and efficient approach for retinal atrophic area segmentation in PM

Numerical and experimental analysis on green laser crystallization of amorphous silicon thin films

The laser fluence effect on crystallization of amorphous silicon irradiated by a frequency-doubled Nd: YAG laser has been studied both theoretically and experimentally. An effective numerical model is set up to predict the melting threshold and the optimized laser fluence for crystallization of 200nm amorphous silicon. Temperature distribution with time and melt depth are analyzed. Besides the model, Raman spectra of thin films treated with different fluences are measured to confirm the phase transition and to determine the optimized fluence. The calculating results accord well with those obtained from the experimental data in this research

Complete Genome Sequence of Bacillus amyloliquefaciens Strain BH072, Isolated from Honey

The genome of Bacillus amyloliquefaciens strain BH072, isolated from a honey sample and showing strong antimicrobial activity against plant pathogens, is 4.07 Mb and harbors 3,785 coding sequences (CDS). Several gene clusters for nonribosomal synthesis of antimicrobial peptides and a complete gene cluster for biosynthesis of mersacidin were detected

Deep learning-based dynamic forecasting method and application for ultra-deep fractured reservoir production

Addressing the complex challenges in dynamic production forecasting for the deep-ultra-deep fractured carbonate reservoirs in the Tarim Basin’s Tahe Oilfield, characterized by numerous influencing factors, strong temporal variations, high non-linearity, and prediction difficulties, We proposes a prediction method based on Gated Recurrent Unit networks (GRU). Initially, the production data and influencing factors are subjected to dimensionality reduction using Pearson correlation coefficient and principal component analysis methods to obtain multi-attribute time series data. Subsequently, deep learning modeling of time series data is conducted using Gated Recurrent Unit networks. The model is then optimized using the Optuna algorithm and applied to the dynamic production forecasting of the deep-ultra-deep fractured carbonate reservoirs in the Tahe Oilfield. The results demonstrate that the Gated Recurrent Unit network model optimized by Optuna excels in the dynamic production forecasting of the Tahe fractured carbonate reservoirs. Compared with the traditional method, the mean absolute error (MAE), the root mean square error (MSE) and the mean absolute percentage error (MAPE) are reduced by 0.04, 0.1 and 1.1, respectively. This method proves to be more adaptable to the production forecasting challenges of deep fractured reservoirs, providing an effective means to enhance model performance. It holds significant practical value and importance in guiding the development of fractured reservoirs

Self-Reference Emerges Earlier than Emotion during an Implicit Self-Referential Emotion Processing Task: Event-Related Potential Evidence

Self-referential emotion refers to the process of evaluating emotional stimuli with respect to the self. Processes indicative of a self-positivity bias are reflected in electroencephalogram (EEG) signals at ~400 ms when the task does not require a discrimination of self from other. However, when distinguishing between self-referential and other-referential emotions is required, previous studies have shown inconsistent temporal dynamics of EEG signals in slightly different tasks. Based on the observation of early self–other discrimination, we hypothesized that self would be rapidly activated in the early stage to modulate emotional processing in the late stage during an implicit self-referential emotion. To test this hypothesis, we employed an implicit task in which participants were asked to judge the order of Chinese characters of trait adjectives preceded by a self (“I”) or other pronoun (“He” or “She”). This study aimed to explore the difference of social-related emotional evaluation from self-reference; the other pronoun was not defined to a specific person, rather it referred to the general concept. Sixteen healthy Chinese subjects participated in the experiment. Event-related potentials (ERPs) showed that there were self-other discrimination effects in the N1 (80–110 ms) and P1 (170–200 ms) components in the anterior brain. The emotional valence was discriminated in the later component of N2 (220–250 ms). The interaction between self-reference and emotional valence occurred during the late positive potential (LPP; 400–500 ms). Moreover, there was a positive correlation between response time (RT) and N1 in the self-reference condition based on the positive-negative contrast, suggesting a modulatory effect of the self-positivity bias. The results indicate that self-reference emerges earlier than emotion and then combines with emotional processing in an implicit task. The findings extend the view that the self plays a highly integrated and modulated role in self-referential emotion processing

Overexpression of the FBA and TPI genes promotes high production of HDMF in Zygosaccharomyces rouxii

4-Hydroxy-2,5-dimethyl-3 (2H)-furanone (HDMF) is widely used in the food industry as a spice and flavoring agent with high market demand. In this study, fructose-1,6-bisphosphate aldolase (FBA) and triose phosphate isomerase (TPI) were overexpressed in Zygosaccharomyces rouxii in the form of single and double genes, respectively, via electroporation. High-yield HDMF-engineered yeast strains were constructed by combining the analysis of gene expression levels obtained by real-time fluorescence quantitative PCR technology and HDMF production measured by HPLC. The results showed that there was a significant positive correlation between the production of HDMF and the expression levels of the FBA and TPI genes in yeast; the expression levels of the FBA and TPI genes were also positively correlated (p < 0.05). Compared with the wild type (WT), the engineered strains F10-D, T17-D, and TF15-A showed marked increases in HDMF production and FBA and TPI gene expression (p < 0.05) and exhibited great genetic stability with no obvious differences in biomass or colony morphology. In addition, the exogenous addition of d-fructose promoted the growth of Z. rouxii. Among the engineered strains, when fermented in YPD media supplemented with d-fructose for 5 days, TF15-A (overexpressing the FBA and TPI genes) generated the highest HDMF production of 13.39 mg/L, which is 1.91 times greater than that of the wild-type strain. The results above indicated that FBA and TPI, which are key enzymes involved in the process of HDMF biosynthesis by Z. rouxii, positively regulate the synthesis of HDMF at the transcriptional level. d-fructose can be used as a precursor for the biosynthesis of HDMF by engineered yeast in industrial production

A correlation analysis of HHV infection and its predictive factors in an HIV-seropositive population in Yunnan, China

Human herpesviruses (HHVs) have a particularly high prevalence in certain high-risk populations and cause increased morbidity and mortality in patients with acquired immunodeficiency syndrome (AIDS). Screening and treating subclinical HHV infections reduce human immunodeficiency virus (HIV) infection incidence, disease progression, and transmission. However, there are few studies on HHVs, HIV coinfection rates, and their related risk factors. We aimed to clarify the prevalence of all eight HHVs in peripheral blood samples collected from HIV-positive patients, and explore the association of HHV infection in HIV-positive patients in an HIV-seropositive population in Yunnan. We recruited 121 HIV-positive patients with highly active antiretroviral therapy (HAART) and 45 healthy individuals. All the eight HHVs were detected using polymerase chain reaction and their epidemiological information and clinical data were collected and statistically analyzed. A high prevalence of HHVs (89.3%) was observed in individuals with HIV infections and with herpes simplex virus (HSV)-2 (65.3%), and HSV-1 (59.5%) being the most common. Coinfection with more than two different HHVs was more common in patients with HIV infections receiving HAART (72.7%) than in healthy controls. Older age, being married, higher HIV-1 plasma viral loads, and use of antiviral protease inhibitors were independently correlated with an increased frequency of HHVs, but we found no association with CD4 count, WHO HIV clinical stage, and HIV infection duration. Our findings are of great significance for the prevention of HHV opportunistic infection in patients with AIDS and their clinical treatment

On the use of nanocellulose as reinforcement in polymer matrix composites

AbstractNanocellulose is often being regarded as the next generation renewable reinforcement for the production of high performance biocomposites. This feature article reviews the various nanocellulose reinforced polymer composites reported in literature and discusses the potential of nanocellulose as reinforcement for the production of renewable high performance polymer nanocomposites. The theoretical and experimentally determined tensile properties of nanocellulose are also reviewed. In addition to this, the reinforcing ability of BC and NFC is juxtaposed. In order to analyse the various cellulose-reinforced polymer nanocomposites reported in literature, Cox–Krenchel and rule-of-mixture models have been used to elucidate the potential of nanocellulose in composite applications. There may be potential for improvement since the tensile modulus and strength of most cellulose nanocomposites reported in literature scale linearly with the tensile modulus and strength of the cellulose nanopaper structures. Better dispersion of individual cellulose nanofibres in the polymer matrix may improve composite properties