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Deep learning with Convolutional Neural Networks has shown great promise in image-based classification and enhancement but is often unsuitable for predictive modeling using features without spatial correlations. We present a feature representation approach termed REFINED (REpresentation of Features as Images with NEighborhood Dependencies) to arrange high-dimensional vectors in a compact image form conducible for CNN-based deep learning. We consider the similarities between features to generate a concise feature map in the form of a two-dimensional image by minimizing the pairwise distance values following a Bayesian Metric Multidimensional Scaling Approach. We hypothesize that this approach enables embedded feature extraction and, integrated with CNN-based deep learning, can boost the predictive accuracy. We illustrate the superior predictive capabilities of the proposed framework as compared to state-of-the-art methodologies in drug sensitivity prediction scenarios using synthetic datasets, drug chemical descriptors as predictors from NCI60, and both transcriptomic information and drug descriptors as predictors from GDSC. Convolutional Neural Networks (CNN) are often unsuitable for predictive modeling involving nonimage based biological features. Here, the authors present a mapping termed REFINED to represent high dimensional vectors as compact images with spatial correlation that makes it compatible with CNN based learning.

Quantitative structure-activity relationship (QSAR) modeling is a powerful tool for drug discovery, yet the lack of interpretability of commonly used QSAR models hinders their application in molecular design. We propose a similarity-based regression framework, topological regression (TR), that offers a statistically grounded, computationally fast, and interpretable technique to predict drug responses. We compare the predictive performance of TR on 530 ChEMBL human target activity datasets against the predictive performance of deep-learning-based QSAR models. Our results suggest that our sparse TR model can achieve equal, if not better, performance than the deep learning-based QSAR models and provide better intuitive interpretation by extracting an approximate isometry between the chemical space of the drugs and their activity space. Quantitative structure-activity relationships (QSAR) models are widely used in drug discovery, but have limitations in their interpretability and accuracy near activity cliffs. Here the authors use a topological regression framework to increase QSAR interpretability and efficiency.

Climatic change is exhibiting significant effects on the ecosystem of the Tibetan Plateau (TP), a climate-sensitive area. In particularly, winter frost, freezing events and snow avalanche frequently causing severe effects on ecosystem and social economy, however, few long-term winter temperature records or reconstructions hinder a better understanding on variations in winter temperature in the vast area of the TP. In this paper, we present a minimum winter (November–February) temperature reconstruction for the past 668 years based on a tree-ring network (12 new tree-ring chronologies) on the southeastern TP. The reconstruction exhibits decadal to inter-decadal temperature variability, with cold periods occurring in 1423–1508, 1592–1651, 1729–1768, 1798–1847, 1892–1927, and 1958–1981, and warm periods in 1340–1422, 1509–1570, 1652–1728, 1769–1797, 1848–1891, 1928–1957, and 1982–2007. As suggested by the comparisons with existing winter temperature series and spatial correlations with Climatic Research Unit gridded data, our reconstruction is reliable and indicative, and it can represent large-scale winter temperature variability on the southeastern TP. Furthermore, it shows an overall agreement with winter temperature from the northeastern TP on decadal to inter-decadal timescales. It also shows the possible effects of volcanic eruption and reducing solar activity on the winter temperature variability for the past six centuries on the southeastern TP.

The rapid and accurate identification of rail surface defects is critical to the maintenance and operational safety of the rail. For the problems of large-scale differences in rail surface defects and many small-scale defects, this paper proposes a rail surface defect detection algorithm, RSDNet (Rail Surface Defect Detection Net), with YOLOv8n as the baseline model. Firstly, the CDConv (Cascade Dilated Convolution) module is designed to realize multi-scale convolution by cascading the cavity convolution with different cavity rates. The CDConv is embedded into the backbone network to gather earlier defect local characteristics and contextual data. Secondly, the feature fusion method of Head is optimized based on BiFPN (Bi-directional Feature Pyramids Network) to fuse more layers of feature information and improve the utilization of original information. Finally, the EMA (Efficient Multi-Scale Attention) attention module is introduced to enhance the network’s attention to defect information. The experiments are conducted on the RSDDs dataset, and the experimental results show that the RSDNet algorithm achieves a mAP of 95.4% for rail surface defect detection, which is 4.6% higher than the original YOLOv8n. This study provides an effective technical means for rail surface defect detection that has certain engineering applications.

Understanding changes in water availability is critical for Central Asia; however, long streamflow reconstructions extending beyond the period of instrumental gauge measurements are largely missing. Here, we present a 785-year-long streamflow reconstruction from spruce tree rings from the Tien Shan Mountains. Although an absolute causal relationship can not be established, relatively high streamflow rates coincided roughly with the period of Mongol expansion from 1225 to 1260 CE and the rise of the Timurid Empire from 1361 to 1400 CE. Since overall wetter conditions were further found during the Zunghar Khanate period 1693–1705 CE, we argue that phases of streamflow surplus likely promoted oasis and grassland productivity, which was an important factor for the rise of inner Eurasian steppe empires. Moreover, we suggest that the streamflow variation might be critical for plague outbreaks in Central Asia, and propose several explanations for possible links with Europe’s repeated Black Death pandemics. We demonstrate that 20th-century low streamflow is unprecedented in the past eight centuries and exacerbated the Aral Sea crisis, which is one of the most staggering ecological disasters of the twentieth century.

Acute lymphoblastic leukaemia (ALL) is a highly aggressive hematological malignancy that necessitates safer, more effective therapies. This study applied a multi-parametric computational approach to identify KRAS (G12C) inhibitors from African natural product databases. Six lead compounds (NA/EA-1 to NA/EA-6) were identified via virtual screening, molecular docking, and induced-fit docking, all showing stronger binding affinities (-14.50 to -10.53 kcal/mol) than the reference inhibitor Sotorasib (-8.34 kcal/mol). These candidates exhibited favorable pharmacokinetic and physicochemical properties, minimal Lipinski's rule violations, and non-toxic ADMET profiles. Four top hits were subjected to 200 ns molecular dynamics simulations, with NA/EA-3 demonstrating the greatest stability, lowest RMSD, and strongest hydrogen bonding. MM/GBSA analysis confirmed NA/EA-3 as the most promising compound (ΔG -54.42 kcal/mol), outperforming Sotorasib (-32.88 kcal/mol). These findings highlight NA/EA-3 as a potential KRAS(G12C) inhibitor for ALL therapy, warranting experimental validation.

Tree radial growth can have significantly different responses to climate change depending on the environment. To elucidate the effects of climate on radial growth and stable carbon isotope (δ 13 C) fractionation of Qinghai spruce ( Picea crassifolia ), a widely distributed native conifer in northwestern China in different environments, we developed chronologies for tree-ring widths and δ 13 C in trees on the southern and northern slopes of the Qilian Mountains, and analysed the relationship between these tree-ring variables and major climatic factors. Tree-ring widths were strongly influenced by climatic factors early in the growing season, and the radial growth in trees on the northern slopes was more sensitive to climate than in trees on the southern. Tree-ring δ 13 C was more sensitive to climate than radial growth. δ 13 C fractionation was mainly influenced by summer temperature and precipitation early in the growing season. Stomatal conductance more strongly limited stable carbon isotope fractionation in tree rings than photosynthetic rate did. The response between tree rings and climate in mountains gradually weakened as climate warmed. Changes in radial growth and stable carbon isotope fractionation of P. crassifolia in response to climate in the Qilian Mountains may be further complicated by continued climate change.

Background Cerebral palsy (CP) is a syndrome of childhood movement and posture disorders. Clinical evidence is still limited and sometimes inconclusive about the benefits of human umbilical cord mesenchymal stem cells (hUC-MSCs) for CP. We conducted a randomized trial to evaluate the safety and efficacy of hUC-MSC transplantation concomitant with rehabilitation in patients with CP. Methods Eligible patients were allocated into the hUC-MSC group and control group. In addition to rehabilitation, the patients in the hUC-MSC group received four transfusions of hUC-MSCs intravenously, while the control group received a placebo. Adverse events (AEs) were collected for safety evaluation in the 12-month follow-up phase. Primary endpoints were assessed as activities of daily living (ADL), comprehensive function assessment (CFA), and gross motor function measure (GMFM) scales. In addition, cerebral metabolic activity was detected by 18 F-FDG-PET/CT to explore the possible mechanism of the therapeutic effects. Primary endpoint data were analyzed by ANOVA using SPSS version 20.0. Results Forty patients were enrolled, and 1 patient withdrew informed consent. Therefore, 39 patients received treatments and completed the scheduled assessments. No significant difference was shown between the 2 groups in AE incidence. Additionally, significant improvements in ADL, CFA, and GMFM were observed in the hUC-MSC group compared with the control group. In addition, the standard uptake value of 18 F-FDG was markedly increased in 3 out of 5 patients from the hUC-MSC group at 12 months after transplantation. Conclusions Our clinical data showed that hUC-MSC transplantation was safe and effective at improving the gross motor and comprehensive function of children with CP when combined with rehabilitation. Recovery of cerebral metabolic activity might play an essential role in the improvements in brain function in patients with CP. The therapeutic window, transfusion route, and dosage in our study were considerable for reference in clinical application. Trial registration Chictr.org.cn, ChiCTR1800016554 . Registered 08 June 2018—retrospectively registered. The public title was “Randomized trial of umbilical cord-derived mesenchymal stem cells for cerebral palsy.”

Originating in the Tianshan Mountains in arid Central Asia, the natural discharge change of the Naryn River is strongly affected by climate change. As the main source of water for the region, this river is crucial to both the natural environment and the socio-economic development. To extend the discharge record and better understand past and future changes in Naryn River discharge, we developed four tree-ring width chronologies and analyzed the relationship between tree growth and discharge. The resulting reconstruction dates back to 1753 and has an R 2 of 0.374 (1939–2017). Interannual discharge variations of the Naryn River indicate that 1917 was the driest year of the past 265 years, while 1956 was the wettest. The record also indicates that the majority of extreme flood years occurred in the past century; prior to about 1900 C.E., the discharge of the Naryn River was relatively stable. Since 1900 C.E., discharge volume has gradually increased, as has discharge variability. At decadal time scales, the 2010s are notable for the frequency of major floods, whereas the 1910s were the driest. Between the 1870s and the 1910s, the Naryn River experienced a period of low discharge that continued for nearly half a century. The discharge of the Naryn River over the past 265 years appears to vary over quasi-periods of 60, 21, 11, and 2-4 years, which are driven by large-scale climate systems.

Key messageWhile radial growth patterns at different stem heights were similar, tree-ring samples collected at breast height showed diminishing chronology strength for detecting climatic signals because of differences in climate responses.In this study, basal area increments (BAI) and tree-ring chronologies for different heights of Schrenk spruce (Picea schrenkiana) in the western Tianshan Mountains were calculated and used to assess the radial growth pattern along the stem. The mean BAI for different stem heights gradually decreased with increasing stem height (1.3 m > 5 m > 10 m > 15 m > 20 m). The five mean BAI series all showed a significant increasing trend since 1961. The mean BAI for the 10 m height showed the fastest increase among the five series. The significant correlations in the original, high-, and low-frequency domains, and the high Gleichläufigkeit index, indicate coherence among the radial growth patterns for different heights along the stem. A correlation analysis revealed that for three periods (July–September of the previous year, November–December of the previous year, and May–October of the current year) the mean minimum temperature mainly affected the radial growth at the upper positions of the bole, while the relationship between the ring width at breast height and climatic values was clearly weak. The results support the hypothesis that traditional tree-ring sampling at breast height may diminish the strength of tree-ring width chronologies in detecting climatic signals to some extent.