Transfer of stripe rust resistance from Aegilops variabilis to bread wheat

In terms of area, the bread wheat producing regions of China comprise the largest area in the world that is constantly threatened by stripe rust epidemics. Consequently, it is important to exploit new adultplant resistance genes in breeding. This study reports the transfer of stripe rust resistance from Aegilops variabilis to bread wheat resulting in resistant line, TKL2(R). Genetic analysis of the segregating populations derived from a cross between TKL2(R) and a susceptible sister line, TKL2(S), indicated that the adult-plant resistance to Puccinia striiformis f. sp. tritici in TKL2(R) is conferred by a single dominant gene. This gene provided resistance to physiological races currently endemic to China, thus indicating its potential usefulness in wheat breeding.Keywords: Aegilops variabilis, gene transfer, Puccinia striiformis f. sp. tritici, Triticum aestivum, wide hybridizatio

Mine or mother’s? Exploring the self-ownership effect across cultures

Peer reviewedPublisher PD

Current perspectives on cell-assisted lipotransfer for breast cancer patients after radiotherapy

Abstract Background Cell-assisted lipotransfer (CAL), a technique of autologous adipose transplantation enriched with adipose-derived stem cells (ADSCs), has the potential to improve cosmetic outcomes at irradiated sites. However, many concerns have been raised about the possibility of ADSCs increasing oncological risk in cancer patients. With the increasing demand for CAL reconstruction, there is an urgent need to determine whether CAL treatment could compromise oncological safety after radiotherapy, as well as to evaluate its efficacy in guiding clinical decisions. Methods A PRISMA-compliant systematic review of the safety and efficacy of CAL in breast cancer patients after radiotherapy was conducted. The PubMed, Ovid, Cochrane Library, and ClinicalTrials.gov databases were comprehensively searched from inception to 31 December 2021. Results The search initially yielded 1185 unique studies. Ultimately, seven studies were eligible. Based on the limited outcome evidence, CAL did not increase recurrence risk in breast cancer patients but presented aesthetic improvement and higher volumetric persistence in a long-term follow-up. Although breast reconstruction with CAL also had oncological safety after radiotherapy, these patients needed more adipose tissue and had relatively lower fat graft retention than the non-irradiated patients (P < 0.05). Conclusions CAL has oncological safety and does not increase recurrence risk in irradiated patients. Since CAL doubles the amount of adipose required without significantly improving volumetric persistence, clinical decisions for irradiated patients should be made more cautiously to account for the potential costs and aesthetic outcomes. There is limited evidence at present; thus, higher-quality, evidence-based studies are required to establish a consensus on breast reconstruction with CAL after radiotherapy

Digital-Twin-Based System for Foam Cleaning Robots in Spent Fuel Pools

This paper introduces a digital-twin-based system for foam cleaning robots in spent fuel pools, aiming to efficiently clean foam in spent fuel pools. The system adopts a four-layer architecture, including the physical entity layer, twin data layer, twin model layer, and application service layer. Initially, the robot was modeled in two dimensions, encompassing physical and kinematic aspects. Subsequently, data collection and fusion were carried out using laser radar and depth cameras, establishing a virtual model of the working scenario and mapping the physical entity to the digital twin model. Building upon this foundation, improvements were made in applying the full-coverage path planning algorithm by integrating a pure tracking algorithm, thereby enhancing the cleaning efficiency. Obstacle detection and localization were conducted using infrared and depth cameras positioned above the four corners of the spent fuel pool, with the digital twin platform transmitting coordinates to the robot for obstacle avoidance operations. Finally, comparative experiments were conducted on the robot’s full-coverage algorithm, along with simulation experiments on the robot’s position and motion direction. The experimental results indicated that this approach reduced the robot’s overall cleaning time and energy consumption. Furthermore, it enabled motion data detection for the digital twin robot, reducing the risk of collisions during the cleaning process and providing insights and directions for the intelligent development of foam cleaning robots

Establishment of a Nomogram Based on Inflammatory Response-Related Methylation Sites in Intraoperative Visceral Adipose Tissue to Predict EWL% at One Year After LSG

Guanyang Chen,1,&ast; Zhehong Li,2,&ast; Qing Sang,1,&ast; Liang Wang,2 Qiqige Wuyun,2 Zheng Wang,2 Weijian Chen,2 Chengyuan Yu,1 Dongbo Lian,2 Nengwei Zhang2 1Department of General Surgery, Peking University Ninth School of Clinical Medicine, Beijing, People’s Republic of China; 2Department of General Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Dongbo Lian; Nengwei Zhang, Email [email protected]; [email protected]: Laparoscopic sleeve gastrectomy (LSG) is considered as an effective bariatric and metabolic surgery for patients with severe obesity. Chronic low-grade inflammation of adipose tissue is associated with obesity and obesity-related complications.Objective: This study intends to establish a nomogram based on inflammatory response-related methylation sites in intraoperative visceral adipose tissue (VAT) to predict excess weight loss (EWL)% at one-year after LSG.Methods: Based on EWL% at one-year after LSG, patients were divided into two groups: the satisfied group (group-A, EWL%≥ 50%) and the unsatisfied group (group-B, EWL%< 50%). Next, we defined genes corresponding to the methylation sites in the 850 K methylation microarray as methylation-related genes (MRGs). We then took the intersection of MRGs and inflammatory response-related genes. After that, inflammatory response-related methylation sites were identified based on overlapping genes. Moreover, difference analysis was carried out to obtain inflammatory response-related differentially methylated sites (IRRDMSs) between group-A and group-B. LASSO analysis was used to identify the hub methylation sites. Finally, we developed a nomogram based on the hub methylation sites.Results: There were 26 patients in the study, with 13 in group-A and 13 in group-B. After data filtering and difference analysis, 200 IRRDMSs were identified (143 hypermethylated sites and 57 hypomethylated sites). Then, we identified three hub methylation sites (cg03610073, cg03208951, and cg18746357) by LASSO analysis and built a predictive nomogram (Area under the curve=0.953).Conclusion: The predictive nomogram based on three inflammatory-related methylation sites (cg03610073, cg03208951, and cg18746357) in intraoperative visceral adipose tissue can predict one-year EWL% after LSG effectively.Keywords: DNA methylation, excess weight loss, laparoscopic sleeve gastrectomy, inflammation, nomogra

Recent Progress of Protein Tertiary Structure Prediction

The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI) algorithms has substantially expedited advancements in protein structure prediction, yielding numerous significant milestones. In particular, the end-to-end deep learning method AlphaFold2 has facilitated the rise of structure prediction performance to new heights, regularly competitive with experimental structures in the 14th Critical Assessment of Protein Structure Prediction (CASP14). To provide a comprehensive understanding and guide future research in the field of protein structure prediction for researchers, this review describes various methodologies, assessments, and databases in protein structure prediction, including traditionally used protein structure prediction methods, such as template-based modeling (TBM) and template-free modeling (FM) approaches; recently developed deep learning-based methods, such as contact/distance-guided methods, end-to-end folding methods, and protein language model (PLM)-based methods; multi-domain protein structure prediction methods; the CASP experiments and related assessments; and the recently released AlphaFold Protein Structure Database (AlphaFold DB). We discuss their advantages, disadvantages, and application scopes, aiming to provide researchers with insights through which to understand the limitations, contexts, and effective selections of protein structure prediction methods in protein-related fields

Mapping fallow fields using Sentinel-1 and Sentinel-2 archives over farming-pastoral ecotone of Northern China with Google Earth Engine

The cropland in the farming-pastoral ecotone of Northern China is highly unstable owing to environmental restoration projects, poor soil fertility, poverty, and rural labor loss, and it is characterized by a large number of fallow fields. Mapping fallow fields in a farming-pastoral ecotone can help in evaluating the impact of complex cropland landscapes on the environment and food security. To map the fallow fields using the Sentinel-1 and Sentinel-2 archives, a multi-metric dataset of vertical transmit–vertical receive + vertical transmit–horizontal receive polarization was established. Moreover, spectral bands and vegetation index datasets were established using Google Earth Engine to classify cropped and fallow fields using the Random Forest classifier. The overall accuracies and Kappa coefficients of different datasets were assessed to examine the dataset with the highest overall accuracy in the main growing season. A 10 m resolution fallow map for 2020 was then generated based on the combined Sentinel-1 and Sentinel-2 datasets with the highest overall accuracy and Kappa coefficients were 95.82% and 0.92, respectively. In addition, the time-series characteristics of the entropy eigenvalues generated via dual-polarization decomposition were quantitatively evaluated to clarify the contribution of the Sentinel-1 synthetic-aperture radar archive to the fallow field mapping. The eigenvalues were more sensitive to the phenological characteristics of cropped and fallow fields than the original backscatter signal of the Sentinel-1 data. Moreover, the mapping method was tested at different time intervals by gradually aggregating the results across an increasing number of months to optimize the fallow field monitoring using the minimum number of observations possible within a short period. Data aggregated over August achieved the highest one-month accuracy; it was also very close to the observations from the whole growing season. The results further emphasize the influence of Sentinel-1 archives on fallow field mapping. Overall, this study clarifies the potential applicability of Sentinel archives for monitoring and mapping managing patterns of agricultural land in a region