DataSheet2_Gamma distribution based predicting model for breast cancer drug response based on multi-layer feature selection.ZIP

In the pursuit of precision medicine for cancer, a promising step is to predict drug response based on data mining, which can provide clinical decision support for cancer patients. Although some machine learning methods for predicting drug response from genomic data already exist, most of them focus on point prediction, which cannot reveal the distribution of predicted results. In this paper, we propose a three-layer feature selection combined with a gamma distribution based GLM and a two-layer feature selection combined with an ANN. The two regression methods are applied to the Encyclopedia of Cancer Cell Lines (CCLE) and the Cancer Drug Sensitivity Genomics (GDSC) datasets. Using ten-fold cross-validation, our methods achieve higher accuracy on anticancer drug response prediction compared to existing methods, with an R2 and RMSE of 0.87 and 0.53, respectively. Through data validation, the significance of assessing the reliability of predictions by predicting confidence intervals and its role in personalized medicine are illustrated. The correlation analysis of the genes selected from the three layers of features also shows the effectiveness of our proposed methods.</p

DataSheet1_Gamma distribution based predicting model for breast cancer drug response based on multi-layer feature selection.PDF

In the pursuit of precision medicine for cancer, a promising step is to predict drug response based on data mining, which can provide clinical decision support for cancer patients. Although some machine learning methods for predicting drug response from genomic data already exist, most of them focus on point prediction, which cannot reveal the distribution of predicted results. In this paper, we propose a three-layer feature selection combined with a gamma distribution based GLM and a two-layer feature selection combined with an ANN. The two regression methods are applied to the Encyclopedia of Cancer Cell Lines (CCLE) and the Cancer Drug Sensitivity Genomics (GDSC) datasets. Using ten-fold cross-validation, our methods achieve higher accuracy on anticancer drug response prediction compared to existing methods, with an R2 and RMSE of 0.87 and 0.53, respectively. Through data validation, the significance of assessing the reliability of predictions by predicting confidence intervals and its role in personalized medicine are illustrated. The correlation analysis of the genes selected from the three layers of features also shows the effectiveness of our proposed methods.</p

Additional file 3: of CDetection: CRISPR-Cas12b-based DNA detection with sub-attomolar sensitivity and single-base specificity

Review history. (DOCX 1323 kb

Engineered Wood with Hierarchically Tunable Microchannels toward Efficient Solar Vapor Generation

Wood-based solar steam evaporators have been attracting increasing interest due to their great potential for addressing water scarcity by utilizing sustainable materials and energy. However, engineering a 3D porous structure within the wood lumens and its effect on solar vapor evaporation have not yet been well explored. Here, a natural wood-based solar evaporator with hierarchical pores is fabricated by assembling polyvinyl alcohol within the lumens through an ice-templating approach. The polyvinyl alcohol porous network is engineered from vertically aligned microchannels to dendritically bridged pores with a narrowed size of a few micrometers and significantly increased surface area. Although the formation of plenty of microscopic channels increases the capillary force in comparison to the native wood lumen, the morphology change induces a high tortuosity factor of the porous structure, resulting in a reduced water transportation rate as well as an increased contact angle. On the other hand, the high surface area of the engineered wood lumens and the good hydrophilicity of the filled polyvinyl alcohol improve the ratio of the formed intermediate water, contributing to reduced vaporization enthalpy. Consequently, by using polydopamine as the photothermal material, the hierarchically structured polyvinyl alcohol–wood solar evaporator exhibits an evaporation rate of 1.6 kg m–2 h–1 under 1 sun irradiation and a high solar evaporation efficiency of up to 107%, which are higher than most of the reported natural-wood-based solar evaporators. Moreover, by exploring the correlation between porous morphology and performance, it has been found that the polyvinyl alcohol–wood composite not only presents an inexpensive and sustainable evaporator but also provides guidelines for designing high-performance steam generation devices

Engineered Wood with Hierarchically Tunable Microchannels toward Efficient Solar Vapor Generation

Wood-based solar steam evaporators have been attracting increasing interest due to their great potential for addressing water scarcity by utilizing sustainable materials and energy. However, engineering a 3D porous structure within the wood lumens and its effect on solar vapor evaporation have not yet been well explored. Here, a natural wood-based solar evaporator with hierarchical pores is fabricated by assembling polyvinyl alcohol within the lumens through an ice-templating approach. The polyvinyl alcohol porous network is engineered from vertically aligned microchannels to dendritically bridged pores with a narrowed size of a few micrometers and significantly increased surface area. Although the formation of plenty of microscopic channels increases the capillary force in comparison to the native wood lumen, the morphology change induces a high tortuosity factor of the porous structure, resulting in a reduced water transportation rate as well as an increased contact angle. On the other hand, the high surface area of the engineered wood lumens and the good hydrophilicity of the filled polyvinyl alcohol improve the ratio of the formed intermediate water, contributing to reduced vaporization enthalpy. Consequently, by using polydopamine as the photothermal material, the hierarchically structured polyvinyl alcohol–wood solar evaporator exhibits an evaporation rate of 1.6 kg m–2 h–1 under 1 sun irradiation and a high solar evaporation efficiency of up to 107%, which are higher than most of the reported natural-wood-based solar evaporators. Moreover, by exploring the correlation between porous morphology and performance, it has been found that the polyvinyl alcohol–wood composite not only presents an inexpensive and sustainable evaporator but also provides guidelines for designing high-performance steam generation devices

Additional file 1: of CDetection: CRISPR-Cas12b-based DNA detection with sub-attomolar sensitivity and single-base specificity

Figure S1. Non-specific DNase activity is conserved across Cas12 proteins. Figure S2. The RuvC domain is responsible for ssDNA trans-cleavage. Figure S3. Preference for Cas12b-mediated trans-activated cleavage of non-specific ssDNA. Figure S4. Sensitivity and specificity of AaCas12b-mediated DNA detection. Figure S5. Comparison of sensitivity of AaCas12b- and LbCas12a-based DNA detection. Figure S6. CDetection achieves sub-attomolar sensitivity in DNA detection. Figure S7. Develop CDetection platform. Figure S8. Accurate DNA detection using CDetection platform. Figure S9. Potential off-target analysis of CDetection. Figure S10. Rapid and accurate diagnostic applications of CDetection. Figure S11. Genetic variants from ClinVar that, in principle, can be detected by CDetection platform. (PDF 2218 kb

Additional file 2: of CDetection: CRISPR-Cas12b-based DNA detection with sub-attomolar sensitivity and single-base specificity

Table S1. Nucleic acids used in this study. Table S2. The components of buffers tested for Cas12b-mediated DNA detection in this study. (PDF 293 kb

Additional file 4: of Enhanced mammalian genome editing by new Cas12a orthologs with optimized crRNA scaffolds

Table S2. Sequences of targeting crRNAs used for in vitro RNA transcription. Table S3. Target sequences harboring various 5′ PAM sequences used for in vitro DNA cleavage assay. Table S4. Protospacer sequences used for genome editing. Table S5. crRNA scaffold optimization and screening. Table S6. Primer sequences used for PCR amplification. Table S7. Frequency of Cas12a- and SpCas9-mediated targeted indel mutations at on-target sites in human 293FT cells. Table S8. Off-target analysis by targeted deep sequencing in the human 293FT cells. Table S9. Off-target analysis by whole genome sequencing (WGS) in human 293FT cells. (PDF 395 kb

Additional file 1: of Enhanced mammalian genome editing by new Cas12a orthologs with optimized crRNA scaffolds

Supplementary methods. (PDF 124 kb

Additional file 5: of Enhanced mammalian genome editing by new Cas12a orthologs with optimized crRNA scaffolds

Supplementary Sequences. The humanized Cas12a coding sequences, protein sequences, U6-crRNA backbone sequences, mammalian and prokaryotic expression vector sequences used in this study. (PDF 183 kb