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A model for predicting slope stability is developed using Categorical Boosting (CatBoost), which incorporates 6 slope features to characterize the state of slope stability. The model is trained using a symmetric tree as the base model, utilizing ordered boosting to replace gradient estimation, which enhances prediction accuracy. Comparative models including Support Vector Machine (SVM), Light Gradient Boosting Machine (LGBM), Random Forest (RF), and Logistic Regression (LR) were introduced. Five performance evaluation metrics are utilized to assess the predictive capabilities of the CatBoost model. Based on CatBoost model, the predicted probability of slope instability is calculated, and the early warning model of slope instability is further established. The results suggest that the CatBoost model demonstrates a 6.25% disparity in accuracy between the training and testing sets, achieving a precision of 100% and an Area Under Curve (AUC) value of 0.95. This indicates a high level of predictive accuracy and robust ordering capabilities, effectively mitigating the problem of overfitting. The slope instability warning model offers reasonable classifications for warning levels, providing valuable insights for both research and practical applications in the prediction of slope stability and instability warning.

In phase I trials, effectively treating patients and minimizing the chance of exposing them to subtherapeutic and overly toxic doses are clinicians' top priority. Motived by this practical consideration, we propose Bayesian optimal interval (BOIN) designs to find the maximum tolerated dose and to minimize the probability of inappropriate dose assignments for patients. We show, both theoretically and numerically, that the BOIN design not only has superior finite and large sample properties but also can be easily implemented in a simple way similar to the traditional '3+3' design. Compared with the well-known continual reassessment method, the BOIN design yields comparable average performance to select the maximum tolerated dose but has a substantially lower risk of assigning patients to subtherapeutic and overly toxic doses. We apply the BOIN design to two cancer clinical trials.

Recent years have witnessed rapid progress in the field of epitranscriptomics. Functional interpretation of the epitranscriptome relies on sequencing technologies that determine the location and stoichiometry of various RNA modifications. However, contradictory results have been reported among studies, bringing the biological impacts of certain RNA modifications into doubt. Here, we develop a synthetic RNA library resembling the endogenous transcriptome but without any RNA modification. By incorporating this modification-free RNA library into established mapping techniques as a negative control, we reveal abundant false positives resulting from sequence bias or RNA structure. After calibration, precise and quantitative mapping expands the understanding of two representative modification types, N6-methyladenosine (m6A) and 5-methylcytosine (m5C). We propose that this approach provides a systematic solution for the calibration of various RNA-modification mappings and holds great promise in epitranscriptomic studies.This work describes the generation of a modification-free RNA library that resembles endogenous transcriptome sequence and expression level, which can be used as a negative control in epitranscriptomic sequencing methods to obtain high-confidence and quantitative maps of various RNA modifications.

Debugging a genome sequence is imperative for successfully building a synthetic genome. As part of the effort to build a designer eukaryotic genome, yeast synthetic chromosome X (synX), designed as 707,459 base pairs, was synthesized chemically. SynX exhibited good fitness under a wide variety of conditions. A highly efficient mapping strategy called pooled PCRTag mapping (PoPM), which can be generalized to any watermarked synthetic chromosome, was developed to identify genetic alterations that affect cell fitness (“bugs”). A series of bugs were corrected that included a large region bearing complex amplifications, a growth defect mapping to a recoded sequence in FIP1 , and a loxPsym site affecting promoter function of ATP2 . PoPM is a powerful tool for synthetic yeast genome debugging and an efficient strategy for phenotype-genotype mapping.

Background Mammography is not effective in detecting breast cancer in dense breasts. Methods A search in Medline, Cochrane, EMBASE and Google Scholar databases was conducted from January 1, 1980 to April 10, 2019 to identify women with dense breasts screened by mammography (M) and/or ultrasound (US). Meta-analysis was performed using the random-effect model. Results A total of 21 studies were included. The pooled sensitivity values of M alone and M + US in patients were 74% and 96%, while specificity of the two methods were 93% and 87%, respectively. Screening sensitivity was significantly higher in M + US than M alone (risk ratio: M alone vs. M + US = 0.699, P  < 0.001), but the slight difference in specificity was statistically significant (risk ratio = 1.060, P  = 0.001). Pooled diagnostic performance of follow-up US after initial negative mammography demonstrated a high pooled sensitivity (96%) and specificity (88%). The findings were supported by subgroup analysis stratified by study country, US method and timing of US. Conclusions Breast cancer screening by supplemental US among women with dense breasts shows added detection sensitivity compared with M alone. However, US slightly decreased the diagnostic specificity for breast cancer. The cost-effectiveness of supplemental US in detecting malignancy in dense breasts should be considered additionally.

The power of synthetic biology has enabled the expression of heterologous pathways in cells, as well as genome-scale synthesis projects. The complexity of biological networks makes rational de novo design a grand challenge. Introducing features that confer genetic flexibility is a powerful strategy for downstream engineering. Here we develop an in vitro method of DNA library construction based on structural variation to accomplish this goal. The “in vitro SCRaMbLE system” uses Cre recombinase mixed in a test tube with purified DNA encoding multiple loxPsym sites. Using a β-carotene pathway designed for expression in yeast as an example, we demonstrate top-down and bottom-up in vitro SCRaMbLE, enabling optimization of biosynthetic pathway flux via the rearrangement of relevant transcription units. We show that our system provides a straightforward way to correlate phenotype and genotype and is potentially amenable to biochemical optimization in ways that the in vivo system cannot achieve. SCRaMbLE allows for the rapid and large scale rearrangement of genetic data in yeast carrying synthetic chromosomes. Here the authors demonstrate an in vitro use of the method to generate DNA libraries for optimization of biochemical reactions.

Compatibility between host cells and heterologous pathways is a challenge for constructing organisms with high productivity or gain of function. Designer yeast cells incorporating the Synthetic Chromosome Rearrangement and Modification by LoxP-mediated Evolution (SCRaMbLE) system provide a platform for generating genotype diversity. Here we construct a genetic AND gate to enable precise control of the SCRaMbLE method to generate synthetic haploid and diploid yeast with desired phenotypes. The yield of carotenoids is increased to 1.5-fold by SCRaMbLEing haploid strains and we determine that the deletion of YEL013W is responsible for the increase. Based on the SCRaMbLEing in diploid strains, we develop a strategy called Multiplex SCRaMbLE Iterative Cycling (MuSIC) to increase the production of carotenoids up to 38.8-fold through 5 iterative cycles of SCRaMbLE. This strategy is potentially a powerful tool for increasing the production of bio-based chemicals and for mining deep knowledge. The SCRaMbLE system integrated into Sc2.0’s synthetic yeast chromosome project allows rapid strain evolution. Here the authors use a genetic logic gate to control induction of recombination in a haploid and diploid yeast carrying synthetic chromosomes.

Therapeutic options for advanced neuroendocrine tumours (NETs) are limited. We investigated the efficacy and safety of surufatinib (HMPL-012, sulfatinib) in patients with extrapancreatic NETs. SANET-ep was a randomised, double-blind, placebo-controlled, phase 3 trial undertaken at 24 hospitals across China. Patients (aged 18 years or older) with unresectable or metastatic, well differentiated, extrapancreatic NETs, with an Eastern Cooperative Oncology Group performance status of 0 or 1, and progression on no more than two types of previous systemic regimens were enrolled. Patients were centrally randomly assigned (2:1) using stratified block randomisation (block size 3) via an interactive web response system to receive oral surufatinib at 300 mg per day or matching placebo. Randomisation was stratified by tumour origin, pathological grade, and previous treatment. Patients, investigators, research staff and the sponsor study team were masked to treatment allocation. Crossover to the surufatinib group was allowed for patients in the placebo group at disease progression. The primary endpoint was investigator-assessed progression-free survival, which was analysed in the intention-to-treat population. A preplanned interim analysis was done at 70% of predicted progression-free survival events. This study was registered with ClinicalTrials.gov, NCT02588170. Follow-up is ongoing. Between Dec 9, 2015, and March 31, 2019, 198 patients were randomly assigned to surufatinib (n=129) or placebo (n=69). Median follow-up was 13·8 months (95% CI 11·1–16·7) in the surufatinib group and 16·6 months (9·2–not calculable) in the placebo group. Investigator-assessed median progression-free survival was 9·2 months (95% CI 7·4–11·1) in the surufatinib group versus 3·8 months (3·7–5·7) in the placebo group (hazard ratio 0·33; 95% CI 0·22–0·50; p<0·0001). As the trial met the predefined criteria for early discontinuation of the study at the interim analysis, the study was terminated early, as recommended by the independent data monitoring committee. The most common treatment-related adverse events of grade 3 or worse were hypertension (47 [36%] of 129 patients in the surufatinib group vs nine [13%] of 68 patients in the placebo group) and proteinuria (25 [19%] vs zero). Treatment-related serious adverse events were reported in 32 (25%) of 129 patients in the surufatinib group and nine (13%) of 68 patients in the placebo group. Treatment-related deaths occurred in three patients in the surufatinib group (disseminated intravascular coagulation and hepatic encephalopathy, liver injury, and death with unknown reason) and one patient in the placebo group (cachexia and respiratory failure). Progression-free survival was significantly longer in patients given surufatinib compared with patients given placebo, and surufatinib has a favourable benefit-to-risk profile in patients with progressive, advanced, well differentiated extrapancreatic NETs. Our results suggest that surufatinib might be a new treatment option for this population. Hutchison MediPharma.