Expanding CRISPR/Cas9 Genome Editing Capacity in Zebrafish Using SaCas9.

The type II CRISPR/Cas9 system has been used widely for genome editing in zebrafish. However, the requirement for the 5'-NGG-3' protospacer-adjacent motif (PAM) of Cas9 from Streptococcus pyogenes (SpCas9) limits its targeting sequences. Here, we report that a Cas9 ortholog from Staphylococcus aureus (SaCas9), and its KKH variant, successfully induced targeted mutagenesis with high frequency in zebrafish. Confirming previous findings, the SpCas9 variant, VQR, can also induce targeted mutations in zebrafish. Bioinformatics analysis of these new Cas targets suggests that the number of available target sites in the zebrafish genome can be greatly expanded. Collectively, the expanded target repertoire of Cas9 in zebrafish should further facilitate the utility of this organism for genetic studies of vertebrate biology

Personalized Estimate of Chemotherapy-Induced Nausea and Vomiting: Development and External Validation of a Nomogram in Cancer Patients Receiving Highly/Moderately Emetogenic Chemotherapy.

Chemotherapy-induced nausea and vomiting (CINV) is presented in over 30% of cancer patients receiving highly/moderately emetogenic chemotherapy (HEC/MEC). The currently recommended antiemetic therapy is merely based on the emetogenic level of chemotherapy, regardless of patient's individual risk factors. It is, therefore, critical to develop an approach for personalized management of CINV in the era of precision medicine.A number of variables were involved in the development of CINV. In the present study, we pooled the data from 2 multi-institutional investigations of CINV due to HEC/MEC treatment in Asian countries. Demographic and clinical variables of 881 patients were prospectively collected as defined previously, and 862 of them had full documentation of variables of interest. The data of 548 patients from Chinese institutions were used to identify variables associated with CINV using multivariate logistic regression model, and then construct a personalized prediction model of nomogram; while the remaining 314 patients out of China (Singapore, South Korea, and Taiwan) entered the external validation set. C-index was used to measure the discrimination ability of the model.The predictors in the final model included sex, age, alcohol consumption, history of vomiting pregnancy, history of motion sickness, body surface area, emetogenicity of chemotherapy, and antiemetic regimens. The C-index was 0.67 (95% CI, 0.62-0.72) for the training set and 0.65 (95% CI, 0.58-0.72) for the validation set. The C-index was higher than that of any single predictor, including the emetogenic level of chemotherapy according to current antiemetic guidelines. Calibration curves showed good agreement between prediction and actual occurrence of CINV.This easy-to-use prediction model was based on chemotherapeutic regimens as well as patient's individual risk factors. The prediction accuracy of CINV occurrence in this nomogram was well validated by an independent data set. It could facilitate the assessment of individual risk, and thus improve the personalized management of CINV

Study of charm hadronization and in-medium modification at the Electron-ion Collider in China

Charm quark production and its hadronization in ep and eA collisions at the future Electron-Ion Collider in China (EicC) will help us understand the quark/gluon fragmentation processes and the hadronization mechanisms in the nuclear medium, especially within a poorly constrained kinematic region ($x<0.1$). In this paper, we report a study on the production of charmed hadrons, $D^0$ and $\Lambda_c^+$, reconstructed with a dedicated GEANT4 simulation of vertex$\,\&\,$tracking detectors designed for EicC. The $\Lambda_c^+$/$D^0$ ratios as functions of multiplicity and $p_T$, as well as the $D^0$ double ratio are presented with projected statistical precision.Comment: 9 pages, 12 figure

PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Images

We present PyMAF-X, a regression-based approach to recovering a full-body parametric model from a single image. This task is very challenging since minor parametric deviation may lead to noticeable misalignment between the estimated mesh and the input image. Moreover, when integrating part-specific estimations to the full-body model, existing solutions tend to either degrade the alignment or produce unnatural wrist poses. To address these issues, we propose a Pyramidal Mesh Alignment Feedback (PyMAF) loop in our regression network for well-aligned human mesh recovery and extend it as PyMAF-X for the recovery of expressive full-body models. The core idea of PyMAF is to leverage a feature pyramid and rectify the predicted parameters explicitly based on the mesh-image alignment status. Specifically, given the currently predicted parameters, mesh-aligned evidence will be extracted from finer-resolution features accordingly and fed back for parameter rectification. To enhance the alignment perception, an auxiliary dense supervision is employed to provide mesh-image correspondence guidance while spatial alignment attention is introduced to enable the awareness of the global contexts for our network. When extending PyMAF for full-body mesh recovery, an adaptive integration strategy is proposed in PyMAF-X to produce natural wrist poses while maintaining the well-aligned performance of the part-specific estimations. The efficacy of our approach is validated on several benchmark datasets for body-only and full-body mesh recovery, where PyMAF and PyMAF-X effectively improve the mesh-image alignment and achieve new state-of-the-art results. The project page with code and video results can be found at https://www.liuyebin.com/pymaf-x.Comment: An eXpressive extension of PyMAF [arXiv:2103.16507], Supporting SMPL-X, Project page: https://www.liuyebin.com/pymaf-