Antibiotic synergistic effect surge bioenergy potential and pathogen resistance of Chlorella variabilis biofilm.

Tetracycline (TC) and ciprofloxacin (CF) induce a synergistic effect that alters the biochemical composition, leading to a decrease in the growth and photosynthetic efficiency of microalgae. But the current study provides a novel insight into stress-inducing techniques that trigger a change in macromolecules, leading to an increase in the bioenergy potential and pathogen resistance of Chlorella variabilis biofilm. The study revealed that in a closed system, a light intensity of 167 µmol/m2/s causes 93.5% degradation of TC and 16% degradation of CF after 7 days of exposure, hence availing the products for utilization by C. variabilis biofilm. The resistance to pathogens invasion was linked to 85% and 40% increase in the expression level of photosystem II oxygen-evolving enhancer protein 3 (PsbQ), and mitogen activated kinase (MAK) respectively. The results also indicate that a surge in light intensity triggers 49% increase in the expression level of lysophosphatidylcholine (LPC) (18:2), which is an important lipidomics that can easily undergo transesterification into bioenergy. The thermogravimetric result indicates that the biomass sample of C. variabilis biofilm cultivated under light intensity of 167 µmol/m2/s produces a higher residual mass of 45.5% and 57.5 under air and inert conditions, respectively. The Fourier transform infrared (FTIR) indicates a slight shift in the major functional groups, while the energy-dispersive X-ray spectroscopy (SEM-EDS) and X-ray fluorescence (XRF) indicate clear differences in the morphology and elemental composition of the biofilm biomass in support of the increase bioenergy potential of C. variabilis biofilm. The current study provides a vital understanding of a innovative method of cultivation of C. variabilis biofilm, which is resistant to pathogens and controls the balance between fatty acid and TAG synthesis leading to surge in bioenergy potential and environmental sustainability.

A review of microalgae biofilm as an eco-friendly approach to bioplastics, promoting environmental sustainability.

In this comprehensive review, we delve into the challenges hindering the large-scale production of microalgae-based bioplastics, primarily focusing on economic feasibility and bioplastic quality. To address these issues, we explore the potential of microalgae biofilm cultivation as a sustainable and highly viable approach for bioplastic production. We present a proposed method for producing bioplastics using microalgae biofilm and evaluate its environmental impact using various tools such as life cycle analysis (LCA), ecological footprint analysis, resource flow analysis, and resource accounting. While pilot-scale and large-scale LCA data are limited, we utilize alternative indicators such as energy efficiency, carbon footprint, materials management, and community acceptance to predict the environmental implications of commercializing microalgae biofilm-based bioplastics. The findings of this study indicate that utilizing microalgae biofilm for bioplastic production offers significant environmental sustainability benefits. The system exhibits low energy requirements and a minimal carbon footprint. Moreover, it has the potential to address the issue of wastewater by utilizing it as a carbon source, thereby mitigating associated problems. However, it is important to acknowledge certain limitations associated with the method proposed in this review. Further research is needed to explore and engineer precise techniques for manipulating microalgae biofilm structure to optimize the accumulation of desired metabolites. This could involve employing chemical triggers, metabolic engineering, and genetic engineering to achieve the intended goals. In conclusion, this review highlights the potential of microalgae biofilm as a viable and sustainable solution for bioplastic production. While acknowledging the advantages, it also emphasizes the need for continued synthetic studies to enhance the efficiency and reliability of this approach. By addressing the identified drawbacks and maximizing the utilization of advanced techniques, we can further harness the potential of microalgae biofilm in contributing to a more environmentally friendly and economically feasible bioplastic industry.

The Role of CCTA-derived Cardiac Structure and Function Analysis in the Prediction of Readmission in Nonischemic Heart Failure.

Cardiac function and structure significantly impact nonischemic heart failure (HF) patient outcomes. This study investigated 236 patients (107 nonischemic heart failure, 129 healthy) to assess the relationship between coronary computed tomography angiography (CCTA)-derived parameters and clinical outcomes. Among the nonischemic heart failure patients, 37.3% experienced readmissions. In this group, specific CCTA measurements were identified as significant predictors of readmission: epicardial adipose tissue (CTEAT) at 54.49 cm3 (HR: 1.05; 95% CI: 1.03-1.07; P < 0.001), cardiac muscle mass to lumen volume (CTV/M) at 20% (HR: 0.59; 95% CI: 0.48-0.72; P < 0.001), peri-coronary adipose (CTPCAT) at -64.68 HU (HR: 1.1; 95% CI: 1.03-1.16; P = 0.002) for the right coronary artery, -81.07 HU (HR: 1.3; 95% CI: 1.1-1.53; P = 0.002) for the left anterior descending artery, and -73.42 HU (HR: 1.33; 95% CI: 1.18-1.51; P < 0.001) for the circumflex branch of the left coronary artery. In patients with nonischemic heart failure, increased CTEAT, CTPCAT, and CTV/M independently predicted rehospitalization.

Attention and feature transfer based knowledge distillation.

Existing knowledge distillation (KD) methods are mainly based on features, logic, or attention, where features and logic represent the results of reasoning at different stages of a convolutional neural network, and attention maps symbolize the reasoning process. Because of the continuity of the two in time, transferring only one of them to the student network will lead to unsatisfactory results. We study the knowledge transfer between the teacher-student network to different degrees, revealing the importance of simultaneously transferring knowledge related to the reasoning process and reasoning results to the student network, providing a new perspective for the study of KD. On this basis, we proposed the knowledge distillation method based on attention and feature transfer (AFT-KD). First, we use transformation structures to transform intermediate features into attentional and feature block (AFB) that contain both inference process information and inference outcome information, and force students to learn the knowledge in AFBs. To save computation in the learning process, we use block operations to align the teacher-student network. In addition, in order to balance the attenuation ratio between different losses, we design an adaptive loss function based on the loss optimization rate. Experiments have shown that AFT-KD achieves state-of-the-art performance in multiple benchmark tests.

Transcriptomic changes in Nicotiana tabacum leaves during mosaic virus infection.

To provide a detailed insight into the early biological process of tobacco mosaic disease, transcriptomic changes in tobacco leaves were surveyed at 1, 3 and 5 days after mono-infected by Tobacco mosaic virus (TMV) and co-infected by Cucumber mosaic virus (CMV) and TMV. At the three different stages, there were 2372, 3168 and 2045 differentially expressed genes (DEGs) in mono-infected leaves, and 2388, 3281 and 3417 DEGs were identified in co-infected leaves. There were 836, 1538 and 1185 common DEGs between the mono-infection and co-infection at the three time points, respectively. These common DEGs were enriched in the pathways, such as photosynthesis, biosynthesis of secondary metabolites, plant-pathogen interaction, porphyrin and chlorophyll metabolism, phenylalanine metabolism and phenylpropanoid biosynthesis. Photosynthesis pathway was observably down-regulated, and defense response pathways were markedly up-regulated. These pathways have been found to be related to tobacco mosaic disease. Of these common DEGs, the changes in expression of argonaute proteins, thioredoxins and peroxidases showed that the activation of RNA silencing and the destruction of redox balance can be induced by tobacco mosaic virus infection, resulting in the reset of biology process and damage in tobacco plants. Additionally, the occurrence of symptoms in co-infected tobacco plants was more early and serious than mono-infection, indicating that there is synergy between TMV and CMV in co-infected tobacco plants. The timely usage of antiviral agents and plant resistance inducers can decrease the incidence of tobacco mosaic disease through changing the expression of some DEGs, indicating that these genes can be used to screen novel plant resistance inducers and antiviral agents. Overall, our results were helpful in clarifying the mechanism of tobacco mosaic disease and provided novel strategies for the prevention of tobacco mosaic disease.