Gastric cancer is one of the most common malignant tumors worldwide. The number of gastric cancer cases and related deaths in China accounts for almost half of the global data. The survival prognosis ...of advanced gastric cancer is poor. With the development of individualized precision therapy, targeted therapy and immunotherapy have become the focus of comprehensive therapy. This paper reviews the latest research progress of chemotherapy, targeted therapy, and immunotherapy for advanced gastric cancer.
Different cultivars of pear trees are often planted in one orchard to enhance yield for its gametophytic self-incompatibility. Therefore, an accurate and robust modelling method is needed for the ...non-destructive determination of leaf nitrogen (N) concentration in pear orchards with mixed cultivars. This study proposes a new technique based on in-field visible-near infrared (VIS-NIR) spectroscopy and the Adaboost algorithm initiated with machine learning methods. The performance was evaluated by estimating leaf N concentration for a total of 1285 samples from different cultivars, growth regions, and tree ages and compared with traditional techniques, including vegetation indices, partial least squares regression, singular support vector regression (SVR) and neural networks (NN). The results demonstrated that the leaf reflectance responded to the leaf nitrogen concentration were more sensitive to the types of cultivars than to the different growing regions and tree ages. Moreover, the AdaBoost.RT-BP had the best accuracy in both the training (R
= 0.96, root mean relative error (RMSE) = 1.03 g kg
) and the test datasets (R
= 0.91, RMSE = 1.29 g kg
), and was the most robust in repeated experiments. This study provides a new insight for monitoring the status of pear trees by the in-field VIS-NIR spectroscopy for better N managements in heterogeneous pear orchards.
Background and aims
It has been confirmed that the declines in arbuscular mycorrhizal fungi (AMF) populations and agroecosystem diversity are largely due to nutrient enrichment caused by ...fertilization. Replacing chemical-only fertilization with organic fertilization is widely considered a possible approach for maintaining soil biodiversity and a healthy functioning ecosystem. Here we aim to examine the effects of organic fertilizer on AMF occurrence.
Methods
We conducted a meta-analysis of 162 field experiments from 54 published studies conducted over the last 20 years. Our dataset included two groups: organic fertilization (OF)
vs
chemical-only fertilization (CF) and OF
vs
no fertilization (NF).
Results
We found that organic fertilizer increased AM fungal biomass and was less detrimental to AMF richness than mineral-only fertilization. AMF responses to organic fertilizer were generally positive when AMF and host plants had a strong mutualistic symbiosis such as in phosphorus-deficient soil, drought and semi-drought areas, at low latitudes, and at testing sites that contained two or more plant species or included legume. In conditions other than these, the responses were generally negative. Organic carbon input, increased soil phosphorus and the ratio of fertilizer N and P jointly explain the effects of organic fertilizer on AMF occurrence.
Conclusions
Our analysis indicates that, although some limiting factors exist, application of organic fertilizer can be an effective practice to protect AM symbiosis from the negative effects of nutrient enrichment in current cropping systems.
Due to the urgency caused by the COVID-19 pandemic worldwide, vaccine manufacturers have to shorten and parallel the development steps to accelerate COVID-19 vaccine production. Although all usual ...safety and efficacy monitoring mechanisms remain in place, varied attitudes toward the new vaccines have arisen among different population groups.
This study aimed to discern the evolution and disparities of attitudes toward COVID-19 vaccines among various population groups through the study of large-scale tweets spanning over a whole year.
We collected over 1.4 billion tweets from June 2020 to July 2021, which cover some critical phases concerning the development and inoculation of COVID-19 vaccines worldwide. We first developed a data mining model that incorporates a series of deep learning algorithms for inferring a range of individual characteristics, both in reality and in cyberspace, as well as sentiments and emotions expressed in tweets. We further conducted an observational study, including an overall analysis, a longitudinal study, and a cross-sectional study, to collectively explore the attitudes of major population groups.
Our study derived 3 main findings. First, the whole population's attentiveness toward vaccines was strongly correlated (Pearson r=0.9512) with official COVID-19 statistics, including confirmed cases and deaths. Such attentiveness was also noticeably influenced by major vaccine-related events. Second, after the beginning of large-scale vaccine inoculation, the sentiments of all population groups stabilized, followed by a considerably pessimistic trend after June 2021. Third, attitude disparities toward vaccines existed among population groups defined by 8 different demographic characteristics. By crossing the 2 dimensions of attitude, we found that among population groups carrying low sentiments, some had high attentiveness ratios, such as males and individuals aged ≥40 years, while some had low attentiveness ratios, such as individuals aged ≤18 years, those with occupations of the 3rd category, those with account age <5 years, and those with follower number <500. These findings can be used as a guide in deciding who should be given more attention and what kinds of help to give to alleviate the concerns about vaccines.
This study tracked the year-long evolution of attitudes toward COVID-19 vaccines among various population groups defined by 8 demographic characteristics, through which significant disparities in attitudes along multiple dimensions were revealed. According to these findings, it is suggested that governments and public health organizations should provide targeted interventions to address different concerns, especially among males, older people, and other individuals with low levels of education, low awareness of news, low income, and light use of social media. Moreover, public health authorities may consider cooperating with Twitter users having high levels of social influence to promote the acceptance of COVID-19 vaccines among all population groups.
Non-destructive and timely determination of leaf nitrogen (N) concentration is urgently needed for N management in pear orchards. A two-year field experiment was conducted in a commercial pear ...orchard with five N application rates: 0 (N0), 165 (N1), 330 (N2), 660 (N3), and 990 (N4) kg·N·ha
. The mid-portion leaves on the year's shoot were selected for the spectral measurement first and then N concentration determination in the laboratory at 50 and 80 days after full bloom (DAB). Three methods of in-field spectral measurement (25° bare fibre under solar conditions, black background attached to plant probe, and white background attached to plant probe) were compared. We also investigated the modelling performances of four chemometric techniques (principal components regression, PCR; partial least squares regression, PLSR; stepwise multiple linear regression, SMLR; and back propagation neural network, BPNN) and three vegetation indices (difference spectral index, normalized difference spectral index, and ratio spectral index). Due to the low correlation of reflectance obtained by the 25° field of view method, all of the modelling was performed on two spectral datasets-both acquired by a plant probe. Results showed that the best modelling and prediction accuracy were found in the model established by PLSR and spectra measured with a black background. The randomly-separated subsets of calibration (
= 1000) and validation (
= 420) of this model resulted in high R² values of 0.86 and 0.85, respectively, as well as a low mean relative error (<6%). Furthermore, a higher coefficient of determination between the leaf N concentration and fruit yield was found at 50 DAB samplings in both 2015 (R² = 0.77) and 2014 (R² = 0.59). Thus, the leaf N concentration was suggested to be determined at 50 DAB by visible/near-infrared spectroscopy and the threshold should be 24-27 g/kg.
In recent years, heatwaves have been reported frequently by literature and the media on the Tibetan Plateau. However, it is unclear how alpine vegetation responds to the heatwaves on the Tibetan ...Plateau. This study aimed to identify the heatwaves using long-term meteorological data and examine the impact of heatwaves on vegetation growth rate with remote sensing data. The results indicated that heatwaves frequently occur in June, July, and August on the Tibetan Plateau. The average frequency of heatwaves had no statistically significant trends from 2000 to 2020 for the entire Tibetan Plateau. On a monthly scale, the average frequency of heatwaves increased significantly (p < 0.1) in August, while no significant trends were in June and July. The intensity of heatwaves indicated a negative correlation with the vegetation growth rate anomaly (ΔVGR) calculated from the normalized difference vegetation index (NDVI) (r = −0.74, p < 0.05) and the enhanced vegetation index (EVI) (r = −0.61, p < 0.1) on the Tibetan Plateau, respectively. Both NDVI and EVI consistently demonstrate that the heatwaves slow the vegetation growth rate. This study outlines the importance of heatwaves to vegetation growth to enrich our understanding of alpine vegetation response to increasing extreme weather events under the background of climate change.
We have carried out a global search of systematic isomers for the lowest energy of neutral and Zintl anionic Zr-doped Si clusters ZrSin0/-/2- (n = 6–16) by employing the ABCluster global search ...method combined with the mPW2PLYP double-hybrid density functional. In terms of the evaluated energies, adiabatic electron affinities, vertical detachment energies, and agreement between simulated and experimental photoelectron spectroscopy, the true global minimal structures are confirmed. The results reveal that structural evolution patterns for neutral ZrSin clusters prefer the attaching type (n = 6–9) to the half-cage motif (n = 10–13), and finally to a Zr-encapsulated configuration with a Zr atom centered in a Si cage (n = 14–16). For Zintl mono- and di-anionic ZrSin-/2-, their growth patterns adopt the attaching configuration (n = 6–11) to encapsulated shape (n = 12–16). The further analyses of stability and chemical bonding make it known that two extra electrons not only perfect the structure of ZrSi15 but also improve its chemical and thermodynamic stability, making it the most suitable building block for novel multi-functional nanomaterials.
The timely estimation of nitrogen (N) requirements is essential for managing N fertilizer application in pear orchards. Visible/near infrared spectroscopy is a non-destructive and effective technique ...for real-time assessment of leaf N concentration, but its utility for decisions about fertilizer application in the pear orchards remains to be determined. In this study, we used leaf spectroscopy to determine leaf N concentration, used this value to calculate the amounts of N required for supplementary fertilization, and then evaluated the effects of the application. Over the two-year study, Cuiguan pear trees were treated with N at the following rates: 0 (N0), 100 (N1), 200 (N2), 300 (N3), and 400 (N4) g N per tree, regarded as five “controlled” N application rates. Another four “regulatory” treatments (Nr1-4) were fertilized as the “controlled” N application rates the first year, then given adjusted N application by topdressing as calculated using the N concentrations inferred from visible/near infrared spectroscopy data the second year. A model (R2 = 0.82) was established the first year to relate leaf spectra and N concentration using a partial least squares regression with full bands (350–2500 nm). The amount of N in the topdressing for the supplemental treatments was determined using the predicted leaf N concentration and the topdressing calculation method adapted from the N balance formula. Results showed that adjusted N applications of the Nr1 and Nr2 increased yield by 26% and 23%, respectively, over the controlled treatments N1 and N2. Although treatments Nr3 and Nr4 did not increase yield significantly over N3 and N4, the partial factor productivity of nitrogen in Nr4 was higher than the N4. The transverse diameter of fruit from Nr1 trees was significantly higher than from N1 trees, while the longitudinal diameter of fruit from Nr1, Nr2, and Nr3 trees was significantly higher than from N1, N2 and N3 trees, suggesting that fruit longitudinal growth and single-fruit weight is stimulated by adjusted N applications. However, the soluble solids in fruit from trees receiving adjusted N were not significantly greater than in fruit from non-supplemented trees. In conclusion, our results illustrate that regulatory N management contributes to fruit yield and quality especially in the nitrogen deficiency condition and improves the nitrogen use efficiency in nitrogen surplus. The N prediction model established using the nondestructive visible/near infrared spectroscopy is convenient and economical.
Equilibrium geometries, thermodynamic stabilities, chemical reactivities, and electronic properties of neutral, mono-, and di-anionic Hf-doped silicon nanoclusters HfSi
n
0/−2-
(
n
= 6–16) are ...calculated by employing an ABCluster global search technique combined with mPW2PLYP scheme. Based on the concordance between simulated and experimental PES, the true global minima are confirmed for
n
= 6, 9, and 12–16. Optimized geometries for neutral HfSi
n
nanoclusters can be divided into three stages: first, Hf atom prefers locating on the surface site of the cluster for
n
= 6–9, which can be obtained by adding one, two, three, and four Si atoms to HfSi
5
tetragonal bipyramid, respectively (denoted as additive type); then, Hf atom is surrounded by Si atoms with half-cage configuration for
n
= 10–13; finally, Hf atom is encapsulated into Si cage pattern for
n
= 14–16. For mono-anions, it is from additive type (
n
= 6–11) to the cagelike configuration with Hf atom resided in silicon clusters (
n
= 12–16). For di-anions, it is additive type (
n
= 6–9) to the Hf-linked configuration (
n
= 10–11), and in the end to the Hf-encapsulated cagelike motif (
n
= 12–16). The thorough analysis of stability and chemical bonding revealed that the neutral HfSi
16
and di-anionic HfSi
15
2−
are magic nanoclusters with good thermodynamic and chemical stability, which may make them as the most suitable building block for new functional materials. We suggest that the experimental PES of HfSi
n
−
with
n
= 7, 8, 10, and 11 should be further examined due to the lack of comparably low electron binding energy peaks.
The adenomatous polyposis coli (
) gene, known as tumor suppressor gene, has the two promoters 1A and 1B. Researches on
have usually focused on its loss-of-function variants causing familial ...adenomatous polyposis. Hypermethylation, however, which is one of the key epigenetic alterations of the
CpG sequence, is also associated with carcinogenesis in various cancers. Accumulating studies have successively explored the role of
hypermethylation in gastrointestinal (GI) tumors, such as in esophageal, colorectal, gastric, pancreatic, and hepatic cancer. In sporadic colorectal cancer, the hypermethylation of CpG island in
is even considered as one of the primary causative factors. In this review, we systematically summarized the distribution of
gene methylation in various GI tumors, and attempted to provide an improved general understanding of DNA methylation in GI tumors. In addition, we included a robust overview of demethylating agents available for both basic and clinical researches. Finally, we elaborated our findings and perspectives on the overall situation of
gene methylation in GI tumors, aiming to explore the potential research directions and clinical values.
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