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Regional land use change is the main cause of carbon storage changes in ecosystems. Predicting the impact of future land use changes on carbon storage is of great significance for the sustainable development of carbon storage functions. In recent years, under the combined action of natural and human factors, the land use in the source region of the Yellow River has changed significantly, and its carbon storage function has also changed accordingly. This study combined InVEST and GeoSoS-FLUS models to evaluate land use change and its impact on carbon storage in the source region of the Yellow River from 2000 to 2020 and from 2020 to 2040 under different scenarios. The results showed that:① from 2000 to 2020, the carbon storage in the source region of the Yellow River showed an overall upward trend, with a total increase of 11.59×10

Neurotransmitters are important in the maintenance of phase transformation of Locusta migratoria (Arthropoda: Orthoptera). Here, the effects of the entomopathogen Paranosema locustae on the neurotransmitter taurine in migratory locusts were studied using biochemical methods. After inoculation with P. locustae, the taurine content of infected locusts significantly declined, but F/C values (ratio between the length of hind femur and the width of the head of locust) increased significantly, compared to healthy locusts. Meanwhile, F/C values of infected locusts that were injected with 2 µg of taurine showed no significant differences from those of healthy locusts, demonstrating that supplemental taurine inhibited the changes in morphological phase caused by P. locustae. Paranosema locustae infection also caused longer developmental durations and lower body weights of locusts, but these changes were unaffected after injection with taurine. These results provided new insights into the mechanisms by which microsporidian parasites affected their locust hosts.

High-velocity compaction is an advanced compaction technique to obtain high-density compacts at a compaction velocity of ≤10 m/s. It was applied to various metallic powders and was verified to achieve a density greater than 7.5 g/cm3 for the Fe-based powders. The ability to rapidly and accurately predict the green density of compacts is important, especially as an alternative to costly and time-consuming materials design by trial and error. In this paper, we propose a machine-learning approach based on materials informatics to predict the green density of compacts using relevant material descriptors, including chemical composition, powder properties, and compaction energy. We investigated four models using an experimental dataset for appropriate model selection and found the multilayer perceptron model worked well, providing distinguished prediction performance, with a high correlation coefficient and low error values. Applying this model, we predicted the green density of nine materials on the basis of specific processing parameters. The predicted green density agreed very well with the experimental results for each material, with an inaccuracy less than 2%. The prediction accuracy of the developed method was thus confirmed by comparison with experimental results.

The mechanical properties of powder metallurgy (PM) materials are closely related to their density. In this case we demonstrate an approach of utilizing machine-learning algorithms trained on experimental data to predict the sintered density of PM materials. Descriptors were selected from the features including processing parameters, chemical composition, property of raw materials and so on. And the training data are collected by the experimental setup in our lab and the literatures on five kinds of P/M alloys. The multilayer perceptron model (MLP) outperformed other four regression and neutral network models with high coefficient of correlation and low error. The sintered density predicted by MLP model agreed well with the experimental data with a tolerable error less than 0.028, which confirms its capability over P/M materials design procedures. Then the obtained MLP model is used for Cu-9Al P/M alloy to guide selecting the processing parameters to reach the expected sintered density of 0.88. The Cu-9Al powders were fabricated with the predicted parameters including the specific shape factor, particle size, pressing pressure and sintering temperature, and the obtained relative sintered density is 0.885.

This thesis is aimed at shedding light on the effects of the Zhenwu decoction (ZWD) on the activities and mRNA expressions of seven CYP450 isoenzymes. In the first step, we determined the main chemical compounds of ZWD by high-performance liquid chromatography (HPLC). Next, 48 male (SD) rats were randomly divided into the normal saline (NS) group and the ZWD low- (2.1875 g/kg), medium- (4.375 g/kg), and high- (8.75 g/kg) dose groups (12 per group). All rats were gavaged once daily for 28 consecutive days. A mixed solution of seven probe drugs was injected into 24 rats through the caudal vein after the last intragastric administration. Lastly, a validated cocktail method and real-time quantitative reverse-transcription polymerase chain reaction (RT-qPCR) were used to detect pharmacokinetic parameters and mRNA expressions, respectively. Compared with the NS group, ZWD at medium- and high-dose groups could significantly induce CYP2C6 (P<0.05) activity, while the mRNA expression (P<0.05) increased only in the high-dose group. Additionally, CYP2C11 activity was induced and consistent with mRNA expression (P<0.05). Moreover, ZWD could induce the activity of CYP3A1 (P<0.05), but the mRNA expression showed no significant differences except in high-dose groups. Additionally, ZWD has no effects on CYP1A2, CYP2B1, CYP2C7, and CYP2D2. In conclusion, the significant inductive effects of ZWD on three CYP450 isoenzymes indicated that when ZWD was coadministrated with drugs mediated by these enzymes, not only should the potential herb-drug interactions (HDIs) be observed, but the dosage adjustment and tissue drug concentration should also be considered. Furthermore, the approach described in this article can be applied to study the importance of gender, age, and disease factors to HDI prediction.

The lattice misfit between γ and γ′ phase in Ni-based single crystal superalloys plays a critical role for microstructural stability and high-temperature creep and fatigue resistance. Making predictions of the lattice misfit rapidly and accurately is therefore of much practical importance, especially for costly and time-consuming material design by trial and error. In this study, we provide a machine learning approach to predict misfit using relevant material descriptors including the chemical composition, dendrite information and measurement temperature and so on. We perform support vector regression, sequential minimal optimization regression and multilayer perceptron algorithms with linear and poly kernels on experimental dataset for appropriate model selecting, and multilayer perceptron model works well for its distinguished prediction performance with high correlation coefficient and low error values. The approach is validated by comparing the predicted lattice misfit with a widely used empirical formula and experimental observation with respect to prediction accuracy.

Semiconductor detector is widely used in energy dispersive X-ray fluorescence measurements due to its excellent performance. In this paper, Si-PIN and CdTe semiconductor detectors were studied, performances of the two detectors were compared in material properties, detection efficiency, energy resolution and other aspects. Focused on the performance of the detectors influenced by the thickness of detector sensitive area, energy of incident X-ray, shaping time of post-stage circuit, and analyzed the differences of energy spectrum caused by escape peaks and hole trailing. Aiming at the problem of incomplete hole collection in detector, a digital multi-channel analyzer (DMCA) based on FPGA with rise-time discriminator was designed, it could reduce the influence of hole trailing effectively and improve energy resolution. The experimentation results indicate that the detection efficiency of Si-PIN and CdTe is roughly equal when energy is below 15 keV while CdTe has much higher detection efficiency than Si-PIN when energy is above 15 keV. The optimum forming time of the Si-PIN detector is about 10 μs, and the CdTe detector is about 2.6 μs, so the CdTe detector is more suitable for the high count rate condition. Si-PIN detector has better energy resolution than CdTe detector for different energy incident X-ray. CdTe detector has obvious hole tailing effect and the energy resolution of CdTe detector is significantly improved by using DMCA with rise-time discrimination.

Graphene quantum dot-covalently appended terpyridine, GQDs–tpy, was synthesized and characterized by X-ray photoelectron spectroscopy, FTIR spectroscopy and transmission electron microscopy. GQDs–tpy was found to act as multifunctional chemosensors: a highly selective colorimetric chemosensor for Fe2+ as evidenced by an obvious color change from colorless to pink, and a typical fluorescence enhanced probe for Zn2+ over 13 metal cations even in practical water samples. Moreover, two-input XOR, INHIBIT and IMPICATION logic gates as well as four-input OR and NOR logic gates were constructed according to the characteristic responses of GQDs-tpy to a sequence of cations.

Pulse shaping, which improves signal-to-noise ratio excellently, has been extensively used in nuclear signal processing. This paper presents a cusp-like pulse-shaping technique developed through the recursive difference equation in time domain. It can be implemented in field programmable gate array hardware system. Another flat-topped cusp-like shaper is developed to optimize the time constant of pulse shaping and reduce the influence of ballistic deficit. The methods of both baseline restoration and pile-up rejection are described. The 137Cs energy spectra measured with the digital cusp-like shaper are 6.6% energy resolution, while those by traditional analog pulse shaper are 7.2% energy resolution, under the same conditions. This technique offers flexibility, too, in adjusting the pulse shaper parameters.

The ability of parasites to modify the behaviour of their hosts is a wide spread phenomenon, but the effects of microsporidian parasites on locust behaviour remain unexplored. Here the frequencies of directional changes (ND) and jumping (NJ) per minute of gregarious locusts infected with 2000 spores of the microsporidian parasite Paranosema locustae were significantly different from those of untreated locusts 10 and 16 days after infection, being similar to values for solitary nymphs. In contrast, the behaviour of locusts inoculated with the lower doses of 200 spores/locust was sometimes like that of solitary nymphs. At other times, behaviour was intermediate between solitary and gregarious, i.e. transitional. The rearing density did not affect the turning and jumping behaviour of infected locusts, and their behaviours were similar to those of solitary locusts at 10–16 days after infection. Our study demonstrates that infection with P. locustae may lead gregarious locusts to change some of their behaviour...

Locusts aggregate into bands of nymphs and swarms of adults that can pose a major threat to crop. Previous studies have shown that infection by the microsporidian parasite Paranosema locustae prevents locust aggregation behavior and we show that gut bacteria, which produce components of locust aggregation pheromones, are substantially reduced in locusts infected with P. locustae. We found that P. locustae could reduce the diversity, abundance and community composition of Locusta migratoria’s gut bacteria. The parasite infection was also shown to interrupt the peroxidase activity of locust hindgut. Genome-wide expression analysis showed that the parasite infection suppressed peroxidase mRNA relative expression of locust hindgut, but had no effects on attacin expression and superoxide dismutase at 16 d post-inoculation with 20,000 P. locustae spores. Our findings reveal the mechanisms by which P. locustae impairs bacterial diversity and community structure of Locusta migratoria’s gut bacteria.

Prostate cancer is the most frequently diagnosed visceral cancer of men, responsible for approximately 40,000 deaths in adult males per year. To identify the genetic causes of prostate cancer, we performed a whole genome scan of affected sib pairs, using DNA markers spaced evenly across the human genome. We demonstrated that regions on chromosomes 1, 4, 5, 7, 8, 11, 16 and 19 might harbor genes that predispose individuals to prostate cancer and may affect tumor growth rate and tumor aggressiveness. Here we present DNA sequence analysis of KIAA 0872 and 17-beta hydroxysteroid dehydrogenase that are located on chromosome 16 within the mapped region, and we demonstrate that neither of these genes carries mutations in the protein coding region or their splice junction sites. These results suggest that these genes are less likely to be associated with the cause of familial prostate cancer.

Transforming growth factor-beta (TGF-beta) is a multifunctional growth and differentiation factor that affects almost all cells. Although equipotent in many cases, the three isoforms of TGF-beta (-beta1, -beta2, -beta3) have several important isoform specific activities. For example, TGF-beta2 binds with higher affinity to a 60 kDa cell-surface glycosyl phosphatidylinositol (GPI)-linked protein, expressed on vascular endothelial cells. We used chimeric TGF-beta proteins, in which selected regions of TGF-beta1 had been exchanged for the corresponding region of TGF-beta2, to demonstrate that amino acids 67 and 68 regulate binding of TGF-beta to this protein. Exchange of amino acids 67 and 68 of TGF-beta1 into TGF-beta2 resulted in a protein similar in affinity to TGF-beta1 for binding to the GPI-linked protein. In contrast, exchange of only amino acid 67 of TGF-beta1 into TGF-beta2, or exchange of only amino acid 68 of TGF-beta1 into TGF-beta2, resulted in a protein with affinity similar to that of TGF-beta2. This suggests that the coordinated change of Gln and His of TGF-beta1 to Thr and Ile at positions 67 and 68 alters the specificity of TGF-beta. Amino acids 67 and 68 are part of a surface-exposed alpha-helix that forms a projection away from the center of the TGF-beta molecule and is accessible for receptor binding.

To overcome the problem of pulse pile-up at high count rates, a digital deconvolution algorithm is used to remove the exponential current tails of NaI(Tl) detectors, so as to obtain a current unit impulse. Then a narrow pulse can be obtained through pulse shaping. The pulse deconvolution technique can thoroughly eliminate the influences of ballistic deficit and improve traditional pulse shaping systems in both pulse throughput and energy resolution. To demonstrate this method, the energy spectrum of a 137Cs radioactive source was measured. When the shaping time constant is 1.5μs, traditional pulse shaping systems yielded a 6.99% energy resolution and 68 kcps count rate, while the new pulse deconvolution technique, used to improve traditional pulse shaping systems, yielded a 6.37% energy resolution and 102 kcps count rate.

Warfarin is an effective, commonly prescribed anticoagulant used to treat and prevent thrombotic events. Because of historically high rates of drug-associated adverse events, warfarin remains underprescribed. Further, interindividual variability in therapeutic dose mandates frequent monitoring until target anticoagulation is achieved. Genetic polymorphisms involved in warfarin metabolism and sensitivity have been implicated in variability of dose. Here, we describe a novel variant that influences warfarin requirements. To identify additional genetic variants that contribute to warfarin requirements, screening of DNA variants in additional genes that code for drug-metabolizing enzymes and drug transport proteins was undertaken using the Affymetrix drug-metabolizing enzymes and transporters panel. A DNA variant (rs2108622; V433M) in cytochrome P450 4F2 (CYP4F2) was associated with warfarin dose in 3 independent white cohorts of patients stabilized on warfarin representing diverse geographic regions in the United States and accounted for a difference in warfarin dose of approximately 1 mg/day between CC and TT subjects. Genetic variation of CYP4F2 was associated with a clinically relevant effect on warfarin requirement.

Objectives: Warfarin is a commonly prescribed anticoagulant drug used to prevent thromboses that may arise as a consequence of orthopedic and vascular surgery or underlying cardiovascular disease. Warfarin is associated with a notoriously narrow therapeutic window where small variations in dosing may result in hemorrhagic or thrombotic complications. To ultimately improve dosing of warfarin, we evaluated models for stable maintenance dose that incorporated both clinical and genetic factors. Method: A model was constructed by evaluating the contribution to dosing variability of the following clinical factors: age, gender, body surface area, and presence or absence of prosthetic heart valves or diabetes. The model was then sequentially expanded by incorporating polymorphisms of cytochrome P450 (CYP) 2C9; vitamin K 2,3 epoxide reductase complex, subunit 1 (VKORC1); gamma carboxylase; factor VII; and apolipoprotein (Apo) E genes. Results: Of genetic factors evaluated in the model, CYP2C9 and VKORC1 each contributed substantially to dose variability, and together with clinical factors explained 56% of the individual variability in stable warfarin dose. In contrast, gamma carboxylase, factor VII and Apo E polymorphisms contributed little to dose variability. Conclusion: The importance of CYP2C9 and VKORC1 to patient-specific dose of warfarin has been confirmed, while polymorphisms of gamma carboxylase, factor VII and Apo E genes did not substantially contribute to predictive models for stable warfarin dose.

Excessive and inappropriate action of transforming growth factor (TGF)-beta has been implicated in the pathogenesis of several disease processes, especially cancer and fibrosis. To identify antagonists of the TGF- beta ligand-binding domain that may have therapeutic potential, we screened the National Cancer Institute open access chemical repository for molecules that inhibited binding of TGF-beta to the type II receptor (TbetaRII). About 30,000 molecules were screened resulting in the identification of five structurally related molecules that reduced binding of TGF-beta1 to soluble TbetaRII with an ED50 of approx 10 microM. The chemicals blocked inhibition of Mv1Lu cell growth by TGF-beta, TGF-beta - induced expression of luciferase driven by the TGF-beta response element, and induction of plasminogen inhibitor mRNA detected by Northern blot. In contrast, the chemicals did not block activin-induced inhibition of cell growth. Our results identify a novel chemical group that blocks binding of TGF-beta to its receptor and may result in novel treatment for disease.

Considerable evidence demonstrates that genetic factors are important in the development and aggressiveness of prostate cancer. To identify genetic variants that predispose to prostate cancer we tested candidate SNPs from genomic regions that show linkage to prostate cancer susceptibility and/or aggressiveness, as well as genes that show a significant difference in mRNA expression level between tumor and normal tissue. Cases had histologically verified prostate cancer. Controls were at least 65 years old, never registered a PSA above 2.5 ng/ml, always had digital rectal examinations that were not suspicious for cancer, and have no known family history of prostate cancer. Thirty-nine coding SNPs and nine non-coding SNPs were tested in up to 590 cases and 556 controls resulting in over 40,000 SNP genotypes. Significant differences in allele frequencies between cases and controls were observed for ID3 (inhibitor of DNA binding), p = 0.05, HPN (hepsin), p = 0.009, BCAS1 (breast carcinoma amplified sequence 1), p = 0.007, CAV2 (caveolin 2), p = 0.007, EMP3 (epithelial membrane protein 3), p < 0.0001, and MLH1 (mutL homolog 1), p < 0.0001. SNPs in three of these genes (BCAS1, EMP3 and MLH1) remained significant in an age-matched subsample.

Prostate cancer is the most frequently diagnosed neoplasia in men and one of the leading causes of cancer-related deaths in men over 60. In an effort to understand the molecular events leading to prostate cancer, we have identified PCAN1 (prostate cancer gene 1) (also known as GDEP), a gene that is highly expressed in prostate epithelial tissue and frequently mutated in prostate tumors. Here we demonstrate its expression in neural retina, and retinoblastoma cell culture but not retinal pigment epithelial cell culture. We further characterize PCAN1 expression in the prostate cell lines RWPE1, RWPE2, and LnCAP PGC. We demonstrate an increase in expression when the cells are grown in the presence of Matrigel, an artificial extracellular basement membrane. Expression was time dependent, with expression observed on d 6 and little or no expression on d 12. Testosterone was not found to increase PCAN1 expression in this culture system. In addition, normal prostate epithelial cells co-cultured with normal prostate stromal cells did not exhibit PCAN1 expression at any time. To definitively locate the transcription initiation sites, we performed restriction-ligase-mediated 5′ RACE, to selectively amplify only mRNA with a 5′ cap. An initial characterization of the sequence upstream of the initiation sites determined six possible binding sites for the prostate specific regulatory protein NKX3. 1 and four potential binding sites for the PPAR/RXR heterodimer that is involved in the control of cell differentiation and apoptosis.