A quantile‐slicing approach for sufficient dimension reduction with censored responses

Sufficient dimension reduction (SDR) that effectively reduces the predictor dimension in regression has been popular in high‐dimensional data analysis. Under the presence of censoring, however, most existing SDR methods suffer. In this article, we propose a new algorithm to perform SDR with censored responses based on the quantile‐slicing scheme recently proposed by Kim et al. First, we estimate the conditional quantile function of the true survival time via the censored kernel quantile regression (Shin et al.) and then slice the data based on the estimated censored regression quantiles instead of the responses. Both simulated and real data analysis demonstrate promising performance of the proposed method.     

Soil moisture determines the recovery time of ecosystems from drought

Recovery time, the time it takes for ecosystems to return to normal states after experiencing droughts, is critical for assessing the response of ecosystems to droughts; however, the spatial dominant factors determining recovery time are poorly understood. We identify the global patterns of terrestrial ecosystem recovery time based on remote sensed vegetation indices, analyse the affecting factors of recovery time using random forest regression model, and determine the spatial distribution of the dominant factors of recovery time based on partial correlation. The results show that the global average recovery time is approximately 3.3 months, and that the longest recovery time occurs in mid-latitude drylands. Analysis of affecting factors of recovery time suggests that the most important environmental factor affecting recovery time is soil moisture during the recovery period, followed by temperature and vapour pressure deficit (VPD). Recovery time shortens with increasing soil moisture and prolongs with increasing VPD; however, the response of recovery time to temperature is nonmonotonic, with colder or hotter temperatures leading to longer recovery time. Soil moisture dominates the drought recovery time over 58.4% of the assessed land area, mostly in the mid-latitudes. The concern is that soil moisture is projected to decline in more than 65% regions in the future, which will lengthen the drought recovery time and exacerbate drought impacts on terrestrial ecosystems, especially in southwestern United States, the Mediterranean region and southern Africa. Our research provides methodological insights for quantifying recovery time and spatially identifies dominant factors of recovery time, improving our understanding of ecosystem response to drought.     

Surface-enhanced Raman scattering integrating with machine learning for green tea storage time identification

The rapid and accurate identification of complex samples still remains a great challenge, especially for those with similar compositions. In this work, we report an integration strategy consisting of surface-enhanced Raman scattering (SERS) and machine learning to discriminate complex and similar analytes, in this case green tea products with different storage times. Surface-functionalized Ag nanoparticles (NPs) were used as a SERS substrate to reveal the changes in the sensory components of green tea with variable storage time. Principal components analysis (PCA)-based support vector machine (SVM) classification was used to extract the key spectral features and identify green tea with different storage times. The results showed that such an integration strategy achieved high predictive accuracy on time tag discrimination for green tea. The multiclass SVM classifier successfully recognized green tea with different storage times at a prediction accuracy of 95.9%, sensitivity of 96.6%, and specificity of 98.8%. Therefore, this work illustrates that the SERS-based PCA-SVM platform might be a facile and reliable tool for the identification of complex matrices with subtle differentiations.     

Weak seed banks influence the signature and detectability of selective sweeps

Seed banking (or dormancy) is a widespread bet-hedging strategy, generating a form of population overlap, which decreases the magnitude of genetic drift. The methodological complexity of integrating this trait implies it is ignored when developing tools to detect selective sweeps. But, as dormancy lengthens the ancestral recombination graph (ARG), increasing times to fixation, it can change the genomic signatures of selection. To detect genes under positive selection in seed banking species it is important to (1) determine whether the efficacy of selection is affected, and (2) predict the patterns of nucleotide diversity at and around positively selected alleles. We present the first tree sequence-based simulation program integrating a weak seed bank to examine the dynamics and genomic footprints of beneficial alleles in a finite population. We find that seed banking does not affect the probability of fixation and confirm expectations of increased times to fixation. We also confirm earlier findings that, for strong selection, the times to fixation are not scaled by the inbreeding effective population size in the presence of seed banks, but are shorter than would be expected. As seed banking increases the effective recombination rate, footprints of sweeps appear narrower around the selected sites and due to the scaling of the ARG are detectable for longer periods of time. The developed simulation tool can be used to predict the footprints of selection and draw statistical inference of past evolutionary events in plants, invertebrates, or fungi with seed banks.     

Effects of various straw incorporation strategies on soil phosphorus fractions and transformations

Returning straw to the field is an effective method for optimizing the soil phosphorus (P) availability, in which bacteria play an important role. However, the effects of various straw incorporation strategies on P transformation between different soil P pools remain unclear. In this study, variations in soil P fractions, phosphatase activities and the abundance of phosphatase genes (phoD, phoX and phoC) as well as a P-solubilizing gene (pqqC) at DNA (total) and cDNA (transcribed) levels were analysed in three straw incorporation treatments, including chopped straw (StrawD), straw compost (Compost) and straw-derived biochar (Biochar), and control (no straw, CK). Compared with the CK, the moderately labile inorganic P (NaOH I-P_i) content significantly decreased and the non-available P (Residual P) content significantly increased in the StrawD treatment. At the same time, phosphodiesterase (PD) activity and the transcribed phoC and phoX genes as well as total pqqC gene abundance significantly increased in the StrawD treatment, suggesting that the input of chopped straw stimulated P transformations from both organic and inorganic P pools. In addition, the stable P_i (NaOH II-P_i) content and total pqqC gene abundance in the Biochar treatment were significantly higher than that in the CK, indicating that the input of biochar increased the NaOH II-P_i that could release available P by Pi-solubilizing bacteria. In comparison to the CK, the Compost input significantly decreased one labile Pi (resin-P_i) only. However, its P fractions were significantly different from that of CK, Biochar and StrawD treatments, suggesting that the effects of compost input on P should not be ignored. In conclusion, chopped straw input increased soil P transformation but not available P, biochar input may promote inorganic P transformation, and compost input has a latent effect on P transformation. The study provided a comprehensive understanding of straw incorporation strategies for regulating soil P availability.     

Changes in colorectal cancer treatment during the COVID-19 pandemic in Japan: Interrupted time-series analysis using the National Database of Japan

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic forced us to accept changes in our usual diagnostic procedures and treatments for colorectal cancer. This study aimed to determine the impact of the pandemic on colorectal cancer treatment in Japan.MethodsThe number of colorectal surgeries, stoma constructions, stent placements or long tube insertions, and neoadjuvant chemoradiotherapies were determined each month using sampling datasets from the National Database of Health Insurance Claims and Specific Health Checkups of Japan. The observation periods before and during the pandemic were January 2015 to January 2020 and April 2020 to January 2021, respectively. An interrupted time-series analysis was used to estimate the changes in the number of procedures during the pandemic.ResultsThe number of endoscopic surgeries for colon cancer significantly decreased in April and July 2020 and for rectal cancer in April 2020. Additionally, the number of laparoscopic and open surgeries for colon cancer significantly decreased in July 2020 and October 2020, respectively. The number of stoma constructions and stent placements or long tube insertions did not increase during the observation period. Neoadjuvant chemoradiotherapy for rectal cancer significantly increased in April 2020 but levels returned shortly thereafter. These results suggest that the recommendations to overcome the pandemic proposed by expert committees, including the replacement of laparoscopic surgery with open surgery, stoma construction to avoid anastomotic leak, and replacement of surgery on the ileus with stent placement, were not widely implemented in Japan. However, as an exception, neoadjuvant chemoradiotherapy for rectal cancer was performed as an alternative treatment to delay surgery in small quantities.ConclusionA declining number of surgeries raises concerns about cancer stage progression; however, we found no evidence to suggest cancer progression from the trajectory of the number of stoma constructions and stent placements. In Japan, even during the pandemic, conventional treatments were performed.