We have reconstructed the Palmer Drought Severity Index (PDSI) from 1580 to 2005 for Western Tian Shan, Central Asia, using tree rings of Picea schrenkiana. The reconstruction explains 35% of the actual January–May PDSI variance during the common period 1925–2005. Split-sample validation supports our use of the reconstruction model based on the full period of reliable observational data (1925–2005). Spatial climate correlation analyses with gridded PDSI data revealed that our PDSI reconstruction represents a strong regional drought signal for Western Tian Shan. Dry periods occurred during ad 1614–1628, 1700–1722, 1758–1790, 1806–1833, 1873–1898, 1908–1936, 1943–1951, 1960–1966 and 1973–1988; while the periods of ad 1580–1613, 1629–1699, 1723–1757, 1791–1805, 1834–1872, 1899–1907, 1937–1942, 1952–1959, 1967–1972 and 1989–present were relatively wet. Our reconstruction agrees reasonably well with the dry and wet periods previously estimated from tree rings in Tian Shan. Significant spectral peaks are identified at 2–5, 60.2 and 213 years. Our reconstructed drought is significantly correlated with sea surface temperature in the North Atlantic and Indo–West Pacific Oceans. The linkages to the North Atlantic and Indo–West Pacific Oceans suggest the connection of moisture variations of Central Asia to the westerly circulation and tropical ocean–atmosphere systems.
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 highdimensional 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.
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."
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