Preclinical studies of CD103 molecular imaging to guide cancer immunotherapy

In summary, this study aims to lay the foundation for the clinical application of CD103 immune PET by developing various tracer types and conducting preliminary in vivo exploration using animal models. It is our hope that these humanized CD103 immune PET tracers can non-invasively assess tumor-reactive T cell infiltration in patients, stratifying those who may benefit from immune checkpoint inhibitor therapy, ultimately providing further benefits to cancer patients

Exploring the Ecological Benefits of Dead Wood and the Opportunities of Interpreting Dead Wood to the Public

According to the Practice Guide of Managing deadwood in forests and woodlands, all types of dead and dying trees of 10 cm or more in diameter are recognised as deadwood. Dead wood is very important to the health of the forest, and this is increasingly recognized by environmentalists and ecologists. Dead wood is thought to be vital to the health of a wood or forest because it can help to reduce soil erosion and create stability (Gamekeeperstrust, 2019). Not only is it an aspect of the nutrient cycling process, it provides a stable, slow-release nitrogen source and is thought to play an important role in carbon storage. Falling logs can also increase the soil stability of the woodland (Pupplet, n.d.). Although every forest and woodland are different, and owners and managers have different management objectives, deadwood should be considered in most situations. Current evidence suggests that, over the long term, deadwood should amount to roughly 20 m3 per hectare averaged across the forest management unit. Some management actions are general to all woodlands, but there are others which are specific to woods or areas of higher ecological value. This approach requires that areas of high ecological value be identified during management planning. The public as the target users of our future design, their attitude is also essential to integrate the characteristics of dead wood into the design of urban environment landscape

An Empirical Study of Performance Evaluation Method EVA-based for Telecom Operators

Combining with EVA-based operation value chain of telecom operators, this paper researches the EVA evaluation scheme introduced by SASAC for central enterprises. In this paper, we design the model of EVA and OPE, ROI, ROE by using the regression analysis method firstly, then find out the relationship between EVA and traditional performance evaluation indexes by combining with the annual report three of telecom operators published in recent years. From the empirical study of Performance Evaluation Method EVA-based, we can find that EVA evaluation scheme is propitious to enhance the management and incentive effect of telecom operators, and promote the development of telecom industry healthily and stably. Key words: EVA; Operation value chain; Performance evaluation; Regression analysi

Hepatic and intestinal biotransformation gene expression and drug disposition in a dextran sulfate sodium-induced colitis mouse model

We examined the impact of gut inflammation on the expression of cytochrome P450 (P450) and other biotransformation genes in male mice using a dextran sulfate sodium (DSS)-induced colitis model. Several P450 isoforms, including CYP1A, CYP2B, CYP2C, and CYP3A, were down-regulated, accompanied by decreases in microsomal metabolism of diclofenac and nifedipine, in the liver and small intestine. The impact of the colitis on in vivo clearance of oral drugs varied for four different drugs tested: a small decrease for nifedipine, a relatively large decrease for lovastatin, but no change for pravastatin, and a large decrease in the absorption of cyclosporine A. To further assess the scope of influence of gut inflammation on gene expression, we performed genome-wide expression analysis using RNA-seq, which showed down-regulation of many CYPs, non-CYP phase-I enzymes, phase-II enzymes and transporters, and up-regulation of many other members of these gene families, in both liver and intestine of adult C57BL/6 mice, by DSS-induced colitis. Overall, our results indicate that gut inflammation suppresses the expression of many P450s and other biotransformation genes in the intestine and liver, and alters the pharmacokinetics for some but not all drugs, potentially affecting therapeutic efficacy or causing adverse effects in a drug-specific fashion.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Nanomechanoelectrical approach to highly sensitive and specific label-free DNA detection

Electronic detection of DNA oligomers offers the promise of rapid, miniaturized DNA analysis across various biotechnological applications. However, known all-electrical methods, which solely rely on measuring electrical signals in transducers during probe–target DNA hybridization, are prone to nonspecific electrostatic and electrochemical interactions, subsequently limiting their specificity and detection limit. Here, we demonstrate a nanomechanoelectrical approach that delivers ultra-robust specificity and a 100-fold improvement in detection limit. We drive nanostructural DNA strands tethered to a graphene transistor to oscillate in an alternating electric field and show that the transistor-current spectra are characteristic and indicative of DNA hybridization. We find that the inherent difference in pliability between unpaired and paired DNA strands leads to the spectral characteristics with minimal influence from nonspecific electrostatic and electrochemical interactions, resulting in high selectivity and sensitivity. Our results highlight the potential of high-performance DNA analysis based on miniaturized all-electronic settings

Automatic Implementation of Neural Networks through Reaction Networks -- Part I: Circuit Design and Convergence Analysis

Information processing relying on biochemical interactions in the cellular environment is essential for biological organisms. The implementation of molecular computational systems holds significant interest and potential in the fields of synthetic biology and molecular computation. This two-part article aims to introduce a programmable biochemical reaction network (BCRN) system endowed with mass action kinetics that realizes the fully connected neural network (FCNN) and has the potential to act automatically in vivo. In part I, the feedforward propagation computation, the backpropagation component, and all bridging processes of FCNN are ingeniously designed as specific BCRN modules based on their dynamics. This approach addresses a design gap in the biochemical assignment module and judgment termination module and provides a novel precise and robust realization of bi-molecular reactions for the learning process. Through equilibrium approaching, we demonstrate that the designed BCRN system achieves FCNN functionality with exponential convergence to target computational results, thereby enhancing the theoretical support for such work. Finally, the performance of this construction is further evaluated on two typical logic classification problems

Predicting changes in protein thermostability brought about by single- or multi-site mutations

<p>Abstract</p> <p>Background</p> <p>An important aspect of protein design is the ability to predict changes in protein thermostability arising from single- or multi-site mutations. Protein thermostability is reflected in the change in free energy (ΔΔ<it>G</it>) of thermal denaturation.</p> <p>Results</p> <p>We have developed predictive software, Prethermut, based on machine learning methods, to predict the effect of single- or multi-site mutations on protein thermostability. The input vector of Prethermut is based on known structural changes and empirical measurements of changes in potential energy due to protein mutations. Using a 10-fold cross validation test on the M-dataset, consisting of 3366 mutants proteins from ProTherm, the classification accuracy of random forests and the regression accuracy of random forest regression were slightly better than support vector machines and support vector regression, whereas the overall accuracy of classification and the Pearson correlation coefficient of regression were 79.2% and 0.72, respectively. Prethermut performs better on proteins containing multi-site mutations than those with single mutations.</p> <p>Conclusions</p> <p>The performance of Prethermut indicates that it is a useful tool for predicting changes in protein thermostability brought about by single- or multi-site mutations and will be valuable in the rational design of proteins.</p

Robust and accurate depth estimation by fusing LiDAR and Stereo

Depth estimation is one of the key technologies in some fields such as autonomous driving and robot navigation. However, the traditional method of using a single sensor is inevitably limited by the performance of the sensor. Therefore, a precision and robust method for fusing the LiDAR and stereo cameras is proposed. This method fully combines the advantages of the LiDAR and stereo camera, which can retain the advantages of the high precision of the LiDAR and the high resolution of images respectively. Compared with the traditional stereo matching method, the texture of the object and lighting conditions have less influence on the algorithm. Firstly, the depth of the LiDAR data is converted to the disparity of the stereo camera. Because the density of the LiDAR data is relatively sparse on the y-axis, the converted disparity map is up-sampled using the interpolation method. Secondly, in order to make full use of the precise disparity map, the disparity map and stereo matching are fused to propagate the accurate disparity. Finally, the disparity map is converted to the depth map. Moreover, the converted disparity map can also increase the speed of the algorithm. We evaluate the proposed pipeline on the KITTI benchmark. The experiment demonstrates that our algorithm has higher accuracy than several classic methods