Clinical and genetic characteristics in lymphoma patients with a second solid malignancy

Diagnosis and treatment of multiple primary malignancies are becoming a new challenge in clinical practice worldwide. The present study aimed to characterize the clinical and genetic features of multiple primary malignancies in patients with synchronous or metachronous lymphoma and another solid tumor. We retrospectively analyzed 11 cases with lymphoma and another solid tumor. The germline mutations in plasma cell-free DNA samples and somatic mutations in lymphoma and solid tumor tissue samples were identified using targeted next-generation sequencing. In the 11 lymphoma patients, the most common type of concurrent solid tumor was colon adenocarcinoma (case 3, 5, 9 11) followed by papillary thyroid carcinoma (case 1, 7, 10). Metachronous lymphoma and solid tumor in 6 patients were treated with corresponding standard therapy asynchronously. Chemotherapy for colon adenocarcinoma during the interval of lymphoma chemotherapy led to excellent outcome in two patients. Immediate chemotherapy for lymphoma plus elective surgery for synchronous papillary thyroid carcinoma also yielded good prognosis in two patients with synchronous double primaries. Interestingly, we found that 10 of 11 patients with lymphoma and another solid tumor harbored germline mutations in Fanconi anemia complementation group (FANC) genes, including FANCI, FANCA, FANCG, FANCL, FANCD1, FANCF, FANCJ, and FANCS. In summary, comprehensive study of the clinical and genetic features of patients with multiple primary malignancies may improve diagnosis and treatment in the future. Mutations in FANC genes might be a predisposition to tumorigenesis of lymphoma patients with a second solid malignancy

A rapid evaluation method for design strategies of high-rise office buildings achieving nearly zero energy in Guangzhou

The construction of nearly zero energy buildings (NZEB) has achieved dramatical impact on global warming and energy crises. It is still a challenge for designers to derive design strategies on how to achieve NZEB in the early design stage, because a complex modelling process with many input parameters of the current NZEB design and evaluation tool is still unavoidable. This article, therefore, aims to introduce a tool suitable for the rapid and reliable evaluation of NZEB design strategies for high rise office building in the city of Guangzhou in China. Firstly, a high-rise office building with typical geometry features is established by sensitivity analysis and survey, thereby the reference building consumption is obtained. Secondly, comprehensive simulations on cases with various envelope features, air conditioning performances and lighting control methods is carried out. Based on the sensitivity analysis on simulation results, key influencing parameters are selected out, effective strategies which fulfills "Technical standard for nearly zero energy buildings (NZEBTS)" are put forward. Finally, a parametric building energy evaluation model is built by regression analysis on simulation results. Combined with energy efficiency index from "NZEBTS", an evaluation tool is developed to help designer determine NZEB strategies. The results revealed that the most effective strategies to achieve NZEB in Guangzhou are to apply high performance external windows, improve air conditioning systems and utilize intelligent zone-controlled lighting systems, meanwhile, the utilization ratio of renewable energy (eta(s)) should be more than 40% of building total annual energy consumption

Conv-Former: A Novel Network Combining Convolution and Self-Attention for Image Quality Assessment

To address the challenge of no-reference image quality assessment (NR-IQA) for authentically and synthetically distorted images, we propose a novel network called the Combining Convolution and Self-Attention for Image Quality Assessment network (Conv-Former). Our model uses a multi-stage transformer architecture similar to that of ResNet-50 to represent appropriate perceptual mechanisms in image quality assessment (IQA) to build an accurate IQA model. We employ adaptive learnable position embedding to handle images with arbitrary resolution. We propose a new transformer block (TB) by taking advantage of transformers to capture long-range dependencies, and of local information perception (LIP) to model local features for enhanced representation learning. The module increases the model’s understanding of the image content. Dual path pooling (DPP) is used to keep more contextual image quality information in feature downsampling. Experimental results verify that Conv-Former not only outperforms the state-of-the-art methods on authentic image databases, but also achieves competing performances on synthetic image databases which demonstrate the strong fitting performance and generalization capability of our proposed model

Supplemental Material - Three-stage channel sprays carbon nanotubes onto carbon fibers surface, preparing high performance carbon fibers composites

Supplemental Material for Three-stage channel sprays carbon nanotubes onto carbon fibers surface, preparing high performance carbon fibers composites by Chuanqi Zhang, Song Shi, Chenyu Gao, Da Zhang, Lansen Bi, Lintao Wang and Yan He in Journal of Composite Materials</p