Optimiranje podloge u proizvodnji bioaktivnih egzopolisaharida submerznim uzgojem gljive Agaricus brasiliensis S. Wasser et al. (=A. blazei Murrill ss. Heinem)

The effects of media components, including carbon source, KH2PO4, and vitamin B1, on the production and quality of Agaricus brasiliensis S. Wasser et al. (=A. blazei Murrill ss. Heinem) exopolysaccharides (ABEP) were studied in submerged culture. The quality of ABEP was characterized on the basis of their stimulation of the release of tumor necrosis factor-alpha (TNF-α) by macrophage cell line RAW 246.7 and their molecular mass distribution. Glucose was the best carbon source for the production of mycelial biomass and ABEP. The medium composition significantly affected both the relative content of β-(1-3)-glucan and the molecular mass (Mr) in the ABEP and, as a consequence, it also affected the biological activity of ABEP. A medium containing 3.0 g/L of KH2PO4 gave an ABEP of the highest biological activity (1440 pg of TNF-α/mL/5x10^4 cells), while a medium containing 10 mg/L of vitamin B1 gave an ABEP with a biological activity of 1080 pg of TNF-α/mL/5x10^4 cells. In a bubble column bioreactor, an optimized medium gave a 1.35-fold increase in ABEP production with a 1.51-fold increase of its biological activity, when compared to the basic medium. This work demonstrates that the relative content of β-(1-3)-glucan in the ABEP is a useful reference indicator of biological activity.Istražen je učinak sastojaka podloge, kao što su izvor ugljika, KH2PO4 i vitamin B1, na proizvodnju egzopolisaharida gljive Agaricus brasiliensis S. Wasser et al. (=A. blazei Murrill ss. Heinem.) submerznim uzgojem i njihovu kvalitetu. Kvaliteta egzopolisaharida gljive A. brasiliensis (ABEP) procijenjena je prema tome koliko potiče otpuštanje tumor nekrozis faktora alfa (TNF-α) stanične linije makrofaga RAW 246.7 i raspodjelu molekularne mase. Glukoza je najbolji izvor ugljika za proizvodnju biomase micelija i egzopolisaharida gljive A. brasiliensis. Sastav podloge značajno je utjecao na relativni udio i molekularnu masu ß-(1-3)-glukana iz egzopolisaharida i time na njihovu biološku aktivnost. Korištenjem podloge s 3,0 g/L KH2PO4 proizvedeni su egzopolisaharidi najveće biološke aktivnosti (1440 pg of TNF-α/mL/5×10^4) stanica), a s podlogom kojoj je dodano 10 mg/L vitamina B1 proizvedeni su egzopolisaharidi s biološkom aktivnošću od 1080 pg of TNF-α/mL/5×10^4) stanica. U usporedbi s osnovnom podlogom, upotrebom optimirane podloge u bioreaktorima s kolonom s barbotirajućim mjehurićima, proizvodnja egzopolisaharida povećala se 1,35 puta, a biološka aktivnost 1,5 puta. U radu je navedeno da je relativni udio ß-(1-3)-glukana u egzopolisaharidima koristan pokazatelj njihove biološke aktivnosti

Advancing heat stress detection in dairy cows through machine learning and computer vision

Heat stress detection in dairy cows has long been connected with production loss. However, the reduction in milk yield lags behind the exposure to heat stress events for about two days. Other stress responses, such as physiological and behavioural changes, are well documented to be activated by dairy cows in the earlier stage of heat stress compared with production loss. Among all candidate indicators, body surface temperatures (BST), respiration rate (RR), and relevant behaviours have been concluded to be the most appropriate indicators due to their high feasibility of acquisition and early response. Vision-based methods are promising for accurate measurements while adhering to animal welfare principles. Meanwhile, predictive models show a non-invasive alternative to obtain these data and can provide useful insights with their interpretations. Thus, this thesis aimed to provide non-invasive solutions to the detection of heat stress in dairy cows by using artificial intelligence techniques. The detailed research content and relevant conclusions are as follows: An automated tool based on improved UNet was proposed to collect facial BST from five facial landmarks (i.e., eyes, muzzle, nostrils, ears, and horns) on cattle infrared images. The baseline UNet model was improved by replacing the traditional convolutional layers in the decoder with Ghost modules and adding efficient channel attention modules. The improved UNet outperformed other comparable models with the highest mean Intersection of Union of 80.76% and a slightly slower but still good inference speed of 32.7 frames per second (FPS). Agreement analysis reveals small to negligible differences between the temperatures obtained automatically in the area of eyes and ears and the ground truth. A vision-based method was proposed to measure RR for multiple dairy cows lying on free stalls. The proposed method involved various computer vision tasks (i.e., instance segmentation, object detection, object tracking, video stabilisation, and optical flow) to obtain respiration-related signals and finally utilised Fast Fourier Transform to extract RR. The results show that the measured RR had a Pearson correlation coefficient of 0.945, a root mean square error (RMSE) of 5.24 breaths per minute (bpm), and an intraclass correlation coefficient of 0.98 compared with visual observation. The average processing time and FPS on 55 test video clips (mean ± standard deviation duration of 16 ± 4 s) was 8.2 s and 64, respectively. A deep learning-based model was proposed to recognise cow behaviours (i.e., drinking, eating, lying, standing-in, and standing-out) that are known to be influenced by heat stress. The YOLOv5s model was selected due to its ability to compress the weight size while maintaining accuracy. It had a mean average precision of 0.985 and an inference speed of 73 FPS. Further validation demonstrates the excellent capacity of the proposed model in measuring herd-level behavioural indicators, with an intraclass correlation coefficient of 0.97 compared with manual observation. Critical thresholds were determined by using piecewise regression models with environmental indicators as the predictors and animal-based indicators as the outcomes. An ambient temperature (Ta) threshold was determined at 26.1 °C when the automated measured mean eye temperature reached 35.3 °C. A Ta threshold of 23.6 °C and a temperature-humidity index (THI) threshold of 72 were determined when the automated measured RR reached 61.1 and 60.4 bpm, respectively. In addition, the test dairy herd began to change their standing and lying behaviour at the earliest Ta of 23.8 ℃ or THI of 68.5. Four machine learning algorithms were used to predict RR, vaginal temperature (VT), and eye temperature (ET) from 13 predictor variables from three dimensions: production, cow-related, and environmental factors. The artificial neural networks yielded the lowest RMSE for predicting RR (13.24 bpm), VT (0.30 ℃), and ET (0.29 ℃). The results interpreted with partial dependence plots and Local Interpretable Model-agnostic Explanations show that P.M. measurements and winter calving contributed most to high RR and VT predictions, whereas lying posture, high Ta, and low wind speed contributed most to high ET predictions. Based on these results, an integrative application of all the proposed measurement, prediction, and assessment methods has been suggested, wherein RGB and infrared cameras are used to measure animal-based indicators, and critical thresholds, along with model interpretation, are used to assess the heat stress state of dairy cows. This strategy ensures timely and thorough cooling of cows in all areas of the dairy farm, thereby minimising the negative impact of heat stress to the greatest extent

Study of Fully Homomorphic Encryption over Integers

Fully homomorphic encryption has long been regarded as an open problem of cryptography. The method of constructing first fully homomorphic encryption scheme by Gentry is complicate so that it has been considered difficult to understand. This paper explains the idea of constructing fully homomorphic encryption and presents a general framework from various scheme of fully homomorphic encryption. Specially, this general framework can show some possible ways to construct fully homomorphic encryption. We then analyze the procedure how to obtaining fully homomorphic encryption over the integers. The analysis of recrypt procedure show the growth of noise, and the bound of noise in recrypt procedure is given. Finally, we describe the steps of implementation.

Transcription Factor E2F1 Regulates the Expression of ADRB2

Adrenergic beta-2-receptor (ADRB2) is highly expressed in various tissue cells, affecting the susceptibility, development, and drug efficacy of diseases such as bronchial asthma and malignant tumor. However, the transcriptional regulatory mechanism of the human ADRB2 gene remains unclear. This study aimed to clarify whether E2F transcription factor 1 (E2F1) was involved in the transcriptional regulation of the human ADRB2 gene. First, the 5\u27 flanking region of the human ADRB2 gene was cloned, and its activity was detected using A549 and BEAS-2B cells. Second, it was found that the overexpression of E2F1 could increase promoter activity by a dual-luciferase reporter gene assay. In contrast, treatment of knockdown of E2F1 significantly resulted in a decrease in its promoter activity. Moreover, mutation of the binding site of E2F1 greatly reduced the potential of human ADRB2 promoter transcriptional activity to be regulated by E2F1 overexpression and knockdown. Additionally, by real-time quantitative PCR and Western blot analysis, we demonstrated that overexpression of E2F1 elevated the ADRB2 mRNA expression and protein levels while si-E2F1 reduced its expression. Finally, the consequence of the chromatin immunoprecipitation assay showed that E2F1 was able to bind to the promoter region of ADRB2 in vivo. These results confirmed that E2F1 upregulated the expression of the human ADRB2 gene

Nucleation of transition waves via collisions of elastic vector solitons

In this work, we show that collisions of one type of nonlinear wave can lead to generation of a different kind of nonlinear wave. Specifically, we demonstrate the formation of topological solitons (or transition waves) via collisions of elastic vector solitons, another type of nonlinear wave, in a multi-stable mechanical system with coupling between translational and rotational degrees of freedom. We experimentally observe the nucleation of a phase transformation arising from colliding waves, and we numerically investigate head-on and overtaking collisions of solitary waves with vectorial properties (i.e., elastic vector solitons). Unlike KdV-type solitons, which maintain their shape despite collisions, our system shows that collisions of two vector solitons can cause nucleation of a new phase via annihilation of the vector soltions, triggering the propagation of transition waves. The propagation of these depends both on the amount of energy carried by the vector solitons and on their respective rotational directions. The observation of the initiation of transition waves with collisions of vector solitons in multistable mechanical systems serves as an example of new fundamental nonlinear wave interactions, and could also prove useful in applications involving reconfigurable structures

The Prognostic Significance of Combining VEGFA, FLT1 and KDR mRNA Expressions in Brain Tumors

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Modulating the Activity of the DLPFC and OFC Has Distinct Effects on Risk and Ambiguity Decision-Making: A tDCS Study

Human beings are constantly exposed to two types of uncertainty situations, risk and ambiguity. Neuroscientific studies suggest that the dorsolateral prefrontal cortex (DLPFC) and the orbital frontal cortex (OFC) play significant roles in human decision making under uncertainty. We applied the transcranial direct current stimulation (tDCS) device to modulate the activity of participants’ DLPFC and OFC separately, comparing the causal relationships between people’s behaviors and the activity of the corresponding brain cortex when confronted with situations of risk and ambiguity. Our experiment employed a pre–post design and a risk/ambiguity decision-making task, from which we could calculate the preferences via an estimation model. We found evidences that modulating the activity of the DLPFC using right anodal/left cathodal tDCS significantly enhanced the participants’ preferences for risk, whereas modulating the activity of the OFC with right anodal/left cathodal tDCS significantly decreased the participants’ preferences for ambiguity. The reverse effects were also observed in the reversed tDCS treatments on the two areas. Our results suggest that decision-making processes under risk and ambiguity are complicated and may be encoded in two distinct circuits in our brains as the DLPFC primarily impacts decisions under risk whereas the OFC affects ambiguity

Optimiranje podloge u proizvodnji bioaktivnih egzopolisaharida submerznim uzgojem gljive Agaricus brasiliensis S. Wasser et al. (=A. blazei Murrill ss. Heinem)

The effects of media components, including carbon source, KH2PO4, and vitamin B1, on the production and quality of Agaricus brasiliensis S. Wasser et al. (=A. blazei Murrill ss. Heinem) exopolysaccharides (ABEP) were studied in submerged culture. The quality of ABEP was characterized on the basis of their stimulation of the release of tumor necrosis factor-alpha (TNF-α) by macrophage cell line RAW 246.7 and their molecular mass distribution. Glucose was the best carbon source for the production of mycelial biomass and ABEP. The medium composition significantly affected both the relative content of β-(1-3)-glucan and the molecular mass (Mr) in the ABEP and, as a consequence, it also affected the biological activity of ABEP. A medium containing 3.0 g/L of KH2PO4 gave an ABEP of the highest biological activity (1440 pg of TNF-α/mL/5x10^4 cells), while a medium containing 10 mg/L of vitamin B1 gave an ABEP with a biological activity of 1080 pg of TNF-α/mL/5x10^4 cells. In a bubble column bioreactor, an optimized medium gave a 1.35-fold increase in ABEP production with a 1.51-fold increase of its biological activity, when compared to the basic medium. This work demonstrates that the relative content of β-(1-3)-glucan in the ABEP is a useful reference indicator of biological activity.Istražen je učinak sastojaka podloge, kao što su izvor ugljika, KH2PO4 i vitamin B1, na proizvodnju egzopolisaharida gljive Agaricus brasiliensis S. Wasser et al. (=A. blazei Murrill ss. Heinem.) submerznim uzgojem i njihovu kvalitetu. Kvaliteta egzopolisaharida gljive A. brasiliensis (ABEP) procijenjena je prema tome koliko potiče otpuštanje tumor nekrozis faktora alfa (TNF-α) stanične linije makrofaga RAW 246.7 i raspodjelu molekularne mase. Glukoza je najbolji izvor ugljika za proizvodnju biomase micelija i egzopolisaharida gljive A. brasiliensis. Sastav podloge značajno je utjecao na relativni udio i molekularnu masu ß-(1-3)-glukana iz egzopolisaharida i time na njihovu biološku aktivnost. Korištenjem podloge s 3,0 g/L KH2PO4 proizvedeni su egzopolisaharidi najveće biološke aktivnosti (1440 pg of TNF-α/mL/5×10^4) stanica), a s podlogom kojoj je dodano 10 mg/L vitamina B1 proizvedeni su egzopolisaharidi s biološkom aktivnošću od 1080 pg of TNF-α/mL/5×10^4) stanica. U usporedbi s osnovnom podlogom, upotrebom optimirane podloge u bioreaktorima s kolonom s barbotirajućim mjehurićima, proizvodnja egzopolisaharida povećala se 1,35 puta, a biološka aktivnost 1,5 puta. U radu je navedeno da je relativni udio ß-(1-3)-glukana u egzopolisaharidima koristan pokazatelj njihove biološke aktivnosti