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To develop and validate a nomogram to predict 1-, 2-, and 5-year survival in patients with non-small-cell lung cancer (NSCLC) by combining optimised radiomics features, clinicopathological factors, and conventional image features extracted from three-dimensional (3D) computed tomography (CT) images.A total of 172 patients with NSCLC were selected to construct the model, and 74 and 72 patients were selected for internal validation and external testing, respectively. A total of 828 radiomics features were extracted from each patient's 3D CT images. Univariable Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to select features and generate a radiomics signature (radscore). The performance of the nomogram was evaluated by calibration curves, clinical practicability, and the c-index. Kaplan-Meier (KM) analysis was used to compare the overall survival (OS) between the two subgroups.The radiomics features of the NSCLC patients correlated significantly with survival time. The c-indexes of the nomogram in the training cohort, internal validation cohort, and external test cohort were 0.670, 0.658, and 0.660, respectively. The calibration curves showed that the predicted survival time was close to the actual survival time. Decision curve analysis shows that the nomogram could be useful in the clinic. According to KM analysis, the 1-, 2- and 5-year survival rates of the low-risk group were higher than those of the high-risk group.The nomogram, combining the radscore, clinicopathological factors, and conventional CT parameters, can improve the accuracy of survival prediction in patients with NSCLC.

A search for exotic dark matter (DM) in the sub-GeV mass range has been conducted using 205 kg$\cdot$day data taken from a p-type point contact germanium detector of CDEX-10 experiment at China Jinping underground laboratory. New low-mass dark matter searching channels, neutral current fermionic DM absorption ($\chi+A\rightarrow \nu+A$) and DM-nucleus 3$\rightarrow$2 scattering ($\chi+\chi+A\rightarrow \phi+A$), have been analyzed with an energy threshold of 160 eVee. No significant signal was found. Thus new limits on the DM-nucleon interaction cross section are set for both models at sub-GeV DM mass region. A cross section limit for the fermionic DM absorption is set to be $\rm 2.5\times 10^{-46} cm^2$(90\% C.L.) at DM mass of 10 MeV/c$^2$. For the DM-nucleus 3$\rightarrow$2 scattering scenario, limits are extended to DM mass of 5 MeV/c$^2$ and 14 MeV/c$^2$ for the massless dark photon and bound DM final state, respectively., Comment: 5 pages, 7 figures

(-)-epigallocatechin-3-O-gallate (EGCG) is the most abundant polyphenol in green tea, which has shown anti-oxidant, anti-inflammatory, anti-thrombotic, anti-radiation, anti-mutant, anti-cancer and anti-fibrotic actions, and has shown improvements of diabetes, obesity, asthma, cancer, cardiovascular diseases and central nervous system disorders. In addition, EGCG is reported to enhance the human immunity. Recently, EGCG has been found to play a vital role in infectious diseases caused by pathogenic microorganisms, including bacteria, fungi, viruses and parasites. The review summarizes the progress of researches on anti-infective properties of EGCG, so as to elucidate the potential role of EGCG in the prevention and treatment of infectious diseases.

Isochrysis galbana is considered an ideal bait for functional foods and nutraceuticals in humans because of its high fucoxanthin (Fx) content. However, multi-omics analysis of the regulation networks for Fx biosynthesis in I. galbana has not been reported. In this study, we report a high-quality genome sequence of I. galbana LG007, which has a 92.73 Mb genome size, with a contig N50 of 6.99 Mb and 14,900 protein-coding genes. Phylogenomic inferences confirmed the monophyly of Haptophyta, with I. galbana sister to Emiliania huxleyi and Chrysochromulina tobinii. Evolutionary analysis revealed an estimated divergence time between I. galbana and E. huxleyi of ~ 133 million years ago (Mya). Gene family analysis indicated that lipid metabolism-related genes exhibited significant expansion, including IgPLMT, IgOAR1 and Δ-4 desaturase. Metabolome analysis showed that the content of carotenoid in I. galbana cultured under green light for 7 days was higher than that of white light, and β-carotene was the main carotenoids, accounting for 79.09% of the total carotenoids. Comprehensive analysis of multi-omics analysis revealed that β-carotene, antheraxanthin, zeaxanthin, and Fx content was increased by green light induction, which was significantly correlated with the expression of IgMYB98, IgZDS, IgPDS, IgLHCX2, IgZEP, IgLCYb, and IgNSY. These findings contribute to understanding Fx biosynthesis and its regulation, providing a valuable reference for food and pharmaceutical applications.

The main objective of the present study is to develop a model for the prediction of the extreme events of air pollution in megacities using the concept of so-called “natural time” instead of the "conventional clock time". In particular, we develop a new nowcasting technique based on a statistically significant fit to the law of Gutenberg-Richter of the surface concentration of ozone (O3), particles of the size fraction less than 10 μm (PM-10) and nitrogen dioxide (NO2). Studying the air pollution over Athens, Greece during the period 2000–2018, we found that the average waiting time between successive extreme concentrations values varied between different atmospheric parameters accounted as 17 days in case of O3, 29 days in case of PM-10 and 28 days in case of NO2. This average waiting time depends on the upper threshold of the maximum extreme concentrations of air pollutants considered. For instance, considering the NO2 concentrations over Athens it was found that the average waiting time is 13 days for 130 μg/m3 and 2.4 years for 200 μg/m3. Remarkably, the same behaviour of obedience to the Guttenberg-Richter law characterizing the extreme values of the air pollution of a megacity was found earlier in other long-term ecological and paleoclimatic variables. It is a sign of self-similarity that is often observed in nature, which can be used in the development of more reliable nowcasting models of extreme events. © 2021 Turkish National Committee for Air Pollution Research and Control

Charge distribution on every atom of carbon matter in four dimension forms (cluster, fullerene, atomistic carbon chain, nanotube, graphene, surface and solid) was investigated by the first-principles calculation. It is found that the charge distribution in most of these materials is inhomogeneous, even in one certain solid phase. We found that if one atom in carbon has different surrounding environment from another one nearby, they always have electron transfer, that is, they have different charge. In round C10 ring, C24 and C60 fullerenes, charge is zero, while charge is not zero in pentagon C10 ring, C30 and C70 fullerenes. At the ends of atomistic chains, nanotube or on the edges of graphenes, carbon atoms have larger positive or negative charge, while almost zero in the central parts. Charge is zero in diamond and graphite, while it is not zero in the high pressure solid phase hexagonite or on some carbon surfaces. The non-zero charge in carbon possibly means its non-zero valence.

The decay ψ′→π+π−π0 is analyzed using a sample of 14 million ψ′ events taken with the BESII detector at the BEPC, and the branching fraction is measured to be B(ψ′→π+π−π0)=(18.1±1.8±1.9)×10−5. A partial wave analysis is carried out using the helicity amplitude method. ψ′→ρ(770)π is observed, and the branching fraction is measured to be B(ψ′→ρ(770)π)=(5.1±0.7±1.1)×10−5, where the first error is statistical and the second one is systematic. A high mass enhancement with mass around 2.15 GeV/c2 is also observed. Attributing this enhancement to the ρ(2150) resonance, the branching fraction is measured to be B(ψ′→ρ(2150)π→π+π−π0)=(19.4±2.5−3.4+11.5)×10−5. The results will help in the understanding of the longstanding “ρπ puzzle” between J/ψ and ψ′ hadronic decays.

Wheel hub bearing not only bears axial load but also radial load, and then its running status directly affects the performance and safety of the automobile. In particular, complicated and variable driving conditions of the automobile are not only liable to aggravate the occurrence of mechanical fault such as localized wear, but also often cause powerful intermittent interference noise. It is difficult to extract the vibration characteristics of the transient impact and harmonic components of the wheel bearings in the event of a local fault. An extraction method of fault feature based on ration of smooth and kurtosis (RSK) index and resonance-based signal sparse de-composition (RSSD) is proposed for automobile wheel hub bearings, which aims at the minimum value of RSK index, sequentially optimizes the Q-factor of the resonance sparse decomposition, and obtains its optimal value adaptively to achieve the decomposition of low resonance components with transient impact components and high resonance components with harmonic components. The effect of the method has been verified by powerful intermittent interference simulation signals and experiment signals from local fault of wheel hub bearing with periodic dynamic radial loading.

The cereal endosperm provides nutrients for seedling growth. The effects of seed components in seedling establishments under salt stress are, however, not yet fully explored. In this study, 60 barley recombinant inbred lines derived from Lewis × Karl cross were grown in four different environments, and the seed contents of starch, total soluble protein, phytate, total phenolics, total flavonoids and total inorganic phosphorus were determined in the harvested grains. Seeds of each line from the four environments were also assayed for seedling growth under saline treatments from 0 to 400 mM NaCl. Root and shoot lengths after 7 days decreased with increasing salt concentration. Correlations between seed components and either root or shoot length were established across the four seed sources. ANOVA showed a significant environment/source effect for both seed components and seedling growth, although the latter was less affected by the seed-production environment. Modeling seedling length across multiple salinities for each seed source showed that the environment with the most saline-tolerant root-growth curve was that associated the highest seed phosphorus content. Correlations between seed components and seedling growth traits highlighted phytate and total inorganic phosphorus as key components for seedling growth under moderate salinities. Seed phytate contents benefited seedling growth, even at high salinities, suggesting an additional role for this seed component under stressful growth conditions, possibly linked to its potential function as an osmolyte source.

Variation in LINE composition is one of the major determinants for the substantial size and structural differences among vertebrate genomes. In particular, the larger genomes of mammals are characterized by hundreds of thousands of copies from a single LINE clade, L1, whereas nonmammalian vertebrates possess a much greater diversity of LINEs, yet with orders of magnitude less in copy number. It has been proposed that such variation in copy number among vertebrates is due to differential effect of LINE insertions on host fitness. To investigate LINE selection, we deployed a framework of demographic modeling, coalescent simulations, and probabilistic inference against population-level whole-genome data sets for four model species: one population each of threespine stickleback, green anole, and house mouse, as well as three human populations. Specifically, we inferred a null demographic background utilizing SNP data, which was then exploited to simulate a putative null distribution of summary statistics that was compared with LINE data. Subsequently, we applied the inferred null demographic model with an additional exponential size change parameter, coupled with model selection, to test for neutrality as well as estimate the strength of either negative or positive selection. We found a robust signal for purifying selection in anole and mouse, but a lack of clear evidence for selection in stickleback and human. Overall, we demonstrated LINE insertion dynamics that are not in accordance to a mammalian versus nonmammalian dichotomy, and instead the degree of existing LINE activity together with host-specific demographic history may be the main determinants of LINE abundance.

Tropical mountains are areas of high species richness and endemism. Two historical phenomena may have contributed to this: (i) fragmentation and isolation of habitats may have promoted the genetic differentiation of populations and increased the possibility of allopatric divergence and speciation and (ii) the mountain areas may have allowed long-term population persistence during global climate fluctuations. These two phenomena have been studied using either species occurrence data or estimating species divergence times. However, only few studies have used intraspecific genetic data to analyse the mechanisms by which endemism may emerge at the microevolutionary scale. Here, we use landscape analysis of genomic SNP data sampled from two high-elevation plant species from an archipelago of tropical sky islands (the Trans-Mexican Volcanic Belt) to test for population genetic differentiation, synchronous demographic changes and habitat persistence. We show that genetic differentiation can be explained by the degree of glacial habitat connectivity among mountains and that mountains have facilitated the persistence of populations throughout glacial/interglacial cycles. Our results support the ongoing role of tropical mountains as cradles for biodiversity by uncovering cryptic differentiation and limits to gene flow., Part of the analyses were carried out on the High Performance Computing Cluster supported by the Research and Specialist Computing Support service at UEA and at the City University of New York High Performance Computing Center, with support from the National Science Foundation (CNS‐0855217 and CNS‐0958379). This work was supported by Consejo Nacional de Ciencia y Tecnología (grant number CONACYT 213538 to AMY and CONACYT 178245 to DP), by Rosemary Grant Award for Graduate Student Research from the Society for the Study of Evolution granted to AMY, by grants from National Science Foundation (DEB‐1253710 to M.J.H.; DEB‐1343578 to Ana C. Carnaval, M.J.H., and Kyle C. McDonald); FAPESP (BIOTA, 2013/50297‐0 to A.C.C., M.J.H., and K.C.M.); and NASA through the Dimensions of Biodiversity Program.

Spatial responses of species to past climate change depend on both intrinsic traits (climatic niche breadth, dispersal rates) and the scale of climatic fluctuations across the landscape. New capabilities in generating and analysing population genomic data, along with spatial modelling, have unleashed our capacity to infer how past climate changes have shaped populations, and by extension, complex communities. Combining these approaches, we uncover lineage diversity across four codistributed lizards from the Australian Monsoonal Tropics and explore how varying climatic tolerances interact with regional climate history to generate common vs. disparate responses to late Pleistocene change. We find more divergent spatial structuring and temporal demographic responses in the drier Kimberley region compared to the more mesic and consistently suitable Top End. We hypothesize that, in general, the effects of species' traits on sensitivity to climate fluctuation will be more evident in climatically marginal regions. If true, this points to the need in climatically marginal areas to craft more species-(or trait)-specific strategies for persistence under future climate change.

The endocarp of pecan is hard to split before the seed germinates. Little is known about the tissue involved in splitting and if seed germination and dormancy affect the process. The endocarp usually splits along the suture when the seed germinates, but may split in other places when dry seeds are pressured. Regardless of the loading direction and the strength, the endocarp does not crack along the suture. We investigated the structure of the suture region of the endocarp using scanning electron microscopy (SEM), and evaluated whether water in the endocarp affects the bonding force of the suture and germination. Six main types of cells were identified. The endocarp consists of isodiametric sclereids, flat sclereids and crenated oblatoid cork cells. Vascular bundles, ellipsoidal sclereids and dumbbell- or kidney-shaped sclereids are found close to the suture. Ellipsoidal sclereids arranged alternately strengthen the region adjacent to the suture, and ensure that the endocarp cracks precisely along ...

In order to establish high-precision models of sedimentary microfacies and provide better supports for reservoir exploitation, the Chang 4 + 51 sub-layer in Hancha Block of Chang Guanmiao Oilfield is taken as an example to carry out uncertainty analysis of sedimentary microfacies modeling. Firstly, uncertainty of sedimentary microfacies models caused by different scaling methods and modeling methods is described separately. Then the effects of different variogram variation ranges on modeling results of sedimentary microfacies are studied. Finally, uncertainty of sedimentary microfacies models caused by different random seeds is discussed. By analyzing the effects of different scaling methods, different modeling methods, different variogram variation ranges and random seeds on the modeling results of sedimentary microfacies, it is concluded that in the process of sedimentary microfacies modeling on Hancha Block of Chang Guanmiao Oilfield, when establishing sedimentary microfacies models for the same sub-layer, the randomness of sedimentary microfacies models generated by different modeling methods is the largest, while the randomness generated by different random seeds is the smallest, and the randomness generated by different variogram variation ranges and scaling methods is between the above two. Uncertainty analysis of sedimentary microfacies modeling can help geologists select the appropriate modeling method and modeling parameters and establish high-precision 3-D models of sedimentary microfacies for enhancing oil recovery finally.

This Letter reports the first extraction of individual antineutrino spectra from ^{235}U and ^{239}Pu fission and an improved measurement of the prompt energy spectrum of reactor antineutrinos at Daya Bay. The analysis uses 3.5×10^{6} inverse beta-decay candidates in four near antineutrino detectors in 1958 days. The individual antineutrino spectra of the two dominant isotopes, ^{235}U and ^{239}Pu, are extracted using the evolution of the prompt spectrum as a function of the isotope fission fractions. In the energy window of 4-6 MeV, a 7% (9%) excess of events is observed for the ^{235}U (^{239}Pu) spectrum compared with the normalized Huber-Mueller model prediction. The significance of discrepancy is 4.0σ for ^{235}U spectral shape compared with the Huber-Mueller model prediction. The shape of the measured inverse beta-decay prompt energy spectrum disagrees with the prediction of the Huber-Mueller model at 5.3σ. In the energy range of 4-6 MeV, a maximal local discrepancy of 6.3σ is observed.

Aging is now considered as an independent risk factor for cardiac fibrosis. However, the mechanisms underlying aging-related cardiac fibrosis remain unknown. Here, we examine the role of serum exosomes in this process.Experiments were conducted using 6-week-old or 24-week-old male Sprague-Dawley (SD) rats. Cardiac sections were treated with Masson's trichrome stain to evaluate fibrosis. Exosomes were isolated from the serum, characterized and quantified using Western blot, electron microscopy, and qNano analysis, and co-cultured with transforming growth factor-β1 (TGF-β1)-induced primary cardiac fibroblasts (CF). Co-cultures were also carried out in the presence of a hot shock protein 70 (HSP70) inhibitor (gefitinib) or inducer (geranylgeranylacetone) to evaluate the role of HSP70 in cardiac fibrosis.Cardiac fibrosis as well as serum exosomes levels were increased during senescence. We observed an increase in fibroblast proliferation and myofibroblast differentiation when CF were co-cultured with exosomes from old rats, compared to those from young mice. Observing a decrease in surface HSP70 expression on the exosomes derived from old rats, we tested the effects of HSP70 inhibition or overexpression on the CF co-cultures. HSP70 inhibition increased fibroblast proliferation and myofibroblast differentiation in CF co-cultures containing exosomes from the young rats, while HSP70 overexpression attenuated fibroblast proliferation and myofibroblast differentiation in CF co-cultures containing exosomes from the old rats.Using an animal model of cardiac fibrosis, we show a decrease in HSP70 expression on the exosomal surface with aging, which may contribute to cardiac fibrosis.

Identification of partial sweeps, which include both hard and soft sweeps that have not currently reached fixation, provides crucial information about ongoing evolutionary responses. To this end, we introduce a deep learning approach that uses a convolutional neural network for image processing, which is trained with coalescent simulations incorporating population-specific history, to discover selective sweeps from population genomic data. This approach distinguishes between completed versus partial sweeps, hard versus soft sweeps, and regions directly affected by selection versus those merely linked to nearby selective sweeps. We perform several simulation experiments under various demographic scenarios to demonstrate the performance of our deep learning classifier partialS/HIC , which exhibits unprecedented resolution for detecting partial sweeps. We also apply our method to whole genomes from eight mosquito populations sampled across sub-Saharan Africa by the Anopheles gambiae 1000 Genomes Consortium, elucidating both continent-wide patterns as well as sweeps unique to specific geographic regions. These populations have experienced intense insecticide exposure over the past two decades, and we observe a strong overrepresentation of sweeps at insecticide resistance loci. Our analysis thus provides a catalog of candidate adaptive loci that may aid mosquito control efforts. More broadly, the success of our supervised machine learning approach introduces a powerful method to distinguish between completed and partial sweeps, as well as between hard and soft sweeps, under a variety of demographic scenarios. As whole-genome data rapidly accumulate for a greater diversity of organisms, partialS/HIC addresses an increasing demand for useful selection scan tools that can track in-progress evolutionary dynamics. Author Summary Recent successful efforts to reduce malaria transmission are in danger of collapse due to evolving insecticide resistance in the mosquito vector Anopheles gambiae . We aim to understand the genetic basis of current adaptation to vector control efforts by deploying a novel method that can classify multiple categories of selective sweeps from population genomic data. In recent years, there has been great progress made in the identification of completed selective sweeps through the use of supervised machine learning (SML), but SML techniques have rarely been applied to partial or ongoing selective sweeps. Partial sweeps represent an important facet of evolution as they reflect present-day selection and thus may give insight into future dynamics. However, the genomic impact left by partial sweeps is more subtle than that left by completed sweeps, making such signatures more difficult to detect. To this end, we extend a recent SML method to partial sweep inference and apply it to elucidate ongoing selective sweeps from Anopheles population genomic samples.

Genetic structure can be influenced by local adaptation to environmental heterogeneity and biogeographic barriers, resulting in discrete population clusters. Geographic distance among populations, however, can result in continuous clines of genetic divergence that appear as structured populations. Here, we evaluate the relevant importance of these three factors over a landscape characterized by environmental heterogeneity and the presence of a hypothesized biogeographic barrier in producing population genetic structure within 13 codistributed snake species using a genomic data set. We demonstrate that geographic distance and environmental heterogeneity across western North America contribute to population genomic divergence. Surprisingly, landscape features long thought to contribute to biogeographic barriers play little role in divergence community wide. Our results suggest that isolation by environment is the most important contributor to genomic divergence. Furthermore, we show that models of population clustering that incorporate spatial information consistently outperform nonspatial models, demonstrating the importance of considering geographic distances in population clustering. We argue that environmental and geographic distances as drivers of community-wide divergence should be explored before assuming the role of biogeographic barriers.

The apple rootstock M26 (Malus domestica) was infected with a binary vector system of Agrobacterium tumefaciens carrying the neomycin phosphotransferase II and Arabidopsis phyB genes. Thirteen transformed clones were obtained from 329 infected leaves. Five of the clones had a single copy integration, six clones had two copies, one clone had five copies and one of the clones had eight copies of the phyB gene integrated. No differences in rooting were found between transformed and untransformed plants. The stem length was reduced in nine of the 13 transgenic clones, and shoot, root and plant dry weights were reduced in all transformed clones compared with untransformed control plants. Northern analysis showed that the Arabidopsis phyB gene was expressed in the transformed clones.