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"Ge, Yuan"
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Redox-switchable breathing behavior in tetrathiafulvalene-based metal–organic frameworks
Metal–organic frameworks (MOFs) that respond to external stimuli such as guest molecules, temperature, or redox conditions are highly desirable. Herein, we coupled redox-switchable properties with breathing behavior induced by guest molecules in a single framework. Guided by topology, two flexible isomeric MOFs, compounds
1
and
2
, with a formula of In(Me
2
NH
2
)(TTFTB), were constructed via a combination of [In(COO)
4
]
−
metal nodes and tetratopic tetrathiafulvalene-based linkers (TTFTB). The two compounds show different breathing behaviors upon the introduction of N
2
. Single-crystal X-ray diffraction, accompanied by molecular simulations, reveals that the breathing mechanism of
1
involves the bending of metal–ligand bonds and the sliding of interpenetrated frameworks, while
2
undergoes simple distortion of linkers. Reversible oxidation and reduction of TTF moieties changes the linker flexibility, which in turn switches the breathing behavior of
2
. The redox-switchable breathing behavior can potentially be applied to the design of stimuli-responsive MOFs.
Modulating the adsorption behaviours of metal-organic frameworks using external stimuli is desirable, but challenging to achieve. Here, Zhou and colleagues design an indium-based MOF in which tetrathiafulvalene ligands undergo reversible redox reactions that alter the framework breathing behaviour.
Journal Article
Triticum population sequencing provides insights into wheat adaptation
Bread wheat expanded its habitat from a core area of the Fertile Crescent to global environments within ~10,000 years. The genetic mechanisms of this remarkable evolutionary success are not well understood. By whole-genome sequencing of populations from 25 subspecies within the genera
Triticum
and
Aegilops
, we identified composite introgression from wild populations contributing to a substantial portion (4–32%) of the bread wheat genome, which increased the genetic diversity of bread wheat and allowed its divergent adaptation. Meanwhile, convergent adaptation to human selection showed 2- to 16-fold enrichment relative to random expectation—a certain set of genes were repeatedly selected in
Triticum
species despite their drastic differences in ploidy levels and growing zones, indicating the important role of evolutionary constraints in shaping the adaptive landscape of bread wheat. These results showed the genetic necessities of wheat as a global crop and provided new perspectives on transferring adaptive success across species for crop improvement.
Whole-genome sequencing of wheat populations from 25 subspecies within the genera
Triticum
and
Aegilops
provides insights into the role of evolutionary constraints in shaping the adaptive landscape of bread wheat.
Journal Article
Pyropia yezoensis genome reveals diverse mechanisms of carbon acquisition in the intertidal environment
Changes in atmospheric CO
2
concentration have played a central role in algal and plant adaptation and evolution. The commercially important red algal genus,
Pyropia
(Bangiales) appears to have responded to inorganic carbon (C
i
) availability by evolving alternating heteromorphic generations that occupy distinct habitats. The leafy gametophyte inhabits the intertidal zone that undergoes frequent emersion, whereas the sporophyte conchocelis bores into mollusk shells. Here, we analyze a high-quality genome assembly of
Pyropia yezoensis
to elucidate the interplay between C
i
availability and life cycle evolution. We find horizontal gene transfers from bacteria and expansion of gene families (e.g. carbonic anhydrase, anti-oxidative related genes), many of which show gametophyte-specific expression or significant up-regulation in gametophyte in response to dehydration. In conchocelis, the release of HCO
3
-
from shell promoted by carbonic anhydrase provides a source of C
i
. This hypothesis is supported by the incorporation of
13
C isotope by conchocelis when co-cultured with
13
C-labeled CaCO
3
.
The nori producing seaweed
Pyropia yezoensis
has heteromorphic generations that occupy distinct habitats. Here, via genome assembly, transcriptome analysis, and 13 C isotope labeling, the authors show the interplay between inorganic carbon availability and life cycle evolution in the intertidal environment.
Journal Article
The Effect of 2016 Chinese second-child policy and different maternal age on pregnancy outcomes in Hebei Province, China
Objective
To explore the effect of the 2016 Chinese second child policy and different maternal ages on adverse perinatal outcomes.
Methods
Clinical data were collected from 22 monitoring hospitals in Hebei Province from January 1, 2013, to December 31, 2021. A total of 413,892 parturient were divided into 3 groups based on delivery age: 20–34, 35–39, and 40–55 years old. The clinical data were analyzed to explore the relationship among the 2016 Chinese second-child policy, maternal age, and various pregnancy risks.
Results
Pregnancy complications showed an upward trend from 2013 to 2021.The top 10 incidences of pregnancy complications in Hebei Province were anemia, small for gestational age (SGA), large for gestational age (LGA), macrosomia, gestational diabetes mellitus (GDM), premature delivery, preeclampsia (PE), postpartum hemorrhage (PPH), placenta previa, and placental abruption. The two-child policy was implemented in 2016. The incidence of pregnancy complications, anemia, GDM, PE, placental abruption, cesarean delivery, premature delivery, SGA, LGA, macrosomia in 2016–2021 was significantly higher than that in 2013–2015 (
P
<0.05), and the proportion of women of advanced maternal age (AMA, ≥ 35 years old) increased from 2013 to 2021. Advanced maternal age was a risk factor for most assessed adverse pregnancy outcomes, including GDM, PE, placenta previa, placenta abruption, cesarean delivery, PPH, premature delivery, SGA, LGA and macrosomia.
Conclusion
After the adjustment of the “second-child” policy, the incidence of pregnancy complications increased. Moreover, the risk of adverse pregnancy outcomes in AMA has increased. Early prevention and intervention should be implemented to cope with the occurrence of adverse perinatal outcomes.
Journal Article
Analysis of Antidepressant Activity of Huang-Lian Jie-Du Decoction Through Network Pharmacology and Metabolomics
Depressive disorder is a common mental disorder characterized by depressed mood and loss of interest or pleasure. As the Herbal medicines are mainly used as complementary and alternative therapy for depression. This study aimed at exploring antidepressant activity of Huang-lian Jie-du Decoction (HLJDD), and evaluating active components and potential depression-associated targets. HLJDD was administered on chronic unpredictable mild stress-induced (CUMS) depressive mice. Behavior evaluation was performed through force swimming test (FST), novelty-suppressed feeding test (NSF), and open field test (OFT). Active components of HLJDD, potential targets, and metabolic pathways involved in depression were explored through systemic biology-based network pharmacology assay, molecular docking and metabonomics. FST assay showed that CUMS mice administered with HLJDD had significantly shorter immobility time compared with control mice. Further, HLJDD alleviated feeding latency of CUMS mice in NSFand increased moving distance and duration in OFT. In the following network pharmacology assay, thirty-eight active compounds in HLJDD were identified based on drug-like characteristics, and pharmacokinetics and pharmacodynamics profiles. Moreover, forty-eight molecular targets and ten biochemical pathways were uncovered through molecular docking and metabonomics. GRIN2B, DRD, PRKCA, HTR, MAOA, SLC6A4, GRIN2A, and CACNA1A are implicated in inhibition of depressive symptoms through modulating tryptophan metabolism, serotonergic and dopaminergic synaptic activities, cAMP signaling pathway, and calcium signaling pathway. Further network pharmacology-based analysis showed a correlation between HLJDD and tryptophan metabolism. A total of thirty-seven active compounds, seventy-six targets, and sixteen biochemical pathways were involved in tryptophan metabolism. These findings show that HLJDD acts on potential targets such as SLC6A4, HTR, INS, MAO, CAT, and FoxO, PI3K/Akt, calcium, HIF-1, and mTOR signaling pathways, and modulates serotoninergic and dopaminergic synaptic functions. In addition, metabonomics showed that tryptophan metabolism is the primary target for HLJDD in CUMS mice. The findings of the study show that HLJDD exhibited antidepressant effects. SLC6A4 and MAOA in tryptophan metabolism were modulated by berberine, baicalein, tetrahydroberberine, candicine and may be the main antidepressant targets for HLJDD.
Journal Article
Integrative genomic study of Chinese clear cell renal cell carcinoma reveals features associated with thrombus
Clear cell renal cell carcinoma (ccRCC) is a heterogeneous disease with features that vary by ethnicity. A systematic characterization of the genomic landscape of Chinese ccRCC is lacking, and features of ccRCC associated with tumor thrombus (ccRCC-TT) remain poorly understood. Here, we applied whole-exome sequencing on 110 normal-tumor pairs and 42 normal-tumor-thrombus triples, and transcriptome sequencing on 61 tumor-normal pairs and 30 primary-thrombus pairs from 152 Chinese patients with ccRCC. Our analysis reveals that a mutational signature associated with aristolochic acid (AA) exposure is widespread in Chinese ccRCC. Tumors from patients with ccRCC-TT show a higher mutational burden and genomic instability; in addition, mutations in
BAP1
and
SETD2
are highly enriched in patients with ccRCC-TT. Moreover, patients with/without TT show distinct molecular characteristics. We reported the integrative genomic sequencing of Chinese ccRCC and identified the features associated with tumor thrombus, which may facilitate ccRCC diagnosis, prognosis and treatment.
The genomic heterogeneity of clear cell renal cell carcinoma (ccRCC) across populations is poorly understood. Here, the authors analyse a cohort of Chinese ccRCC cases revealing a mutational signature associated with aristolochic acid exposure, and higher mutational burden and enrichment for
BAP1
and
SETD2
mutations in ccRCC cases associated with tumor thrombus.
Journal Article
Development and evaluation of a multimodal feature-based predictive model for radiotherapy-induced oral mucositis in nasopharyngeal carcinoma
Accurate prediction of radiation-induced oral mucositis is crucial for personalized treatment in head and neck cancer. However, developing robust predictive models utilizing high-dimensional multimodal data (CT imaging, dose distribution, and clinical features) remains challenging, particularly in cohorts with limited sample sizes.
This study aimed to rigorously evaluate and compare the multi-class predictive performance of traditional machine learning algorithms and deep learning architectures under a small-cohort setting.
Multimodal data from 108 patients were collected. A comprehensive evaluation framework incorporating nine traditional machine learning algorithms and two deep learning models (a dimensionality-reduced 1D-CNN and a multimodal 3D-CNN) was established. To ensure robust evaluation, a stratified 5-fold cross-validation was employed. Model performance was comprehensively quantified using mean ± standard deviation (SD) across multiple metrics, including the Area Under the Curve (AUC), accuracy, and Matthews Correlation Coefficient (MCC).
Inter-rater reliability for RIOM grading was excellent (Cohen's kappa = 0.82, 95% CI: 0.73-0.91). Among traditional machine learning approaches, the Extra Trees (ET) algorithm achieved the highest discriminative capacity (AUC: 0.956 ± 0.046), while Logistic Regression (LR) demonstrated optimal overall accuracy (0.832 ± 0.155) and stability. Regarding deep learning, the lightweight 1D-CNN utilizing fused low-dimensional features exhibited highly competitive and robust performance (AUC: 0.900 ± 0.072; Accuracy: 0.732 ± 0.140). In stark contrast, the high-dimensional multimodal 3D-CNN suffered from severe overfitting and mode collapse phenomenon, yielding significantly inferior results (AUC: 0.568 ± 0.090; MCC: -0.025 ± 0.031).
For small-cohort radiomics and dosimetric analyses, ensemble learning models (e.g., ET) and appropriately regularized linear models (e.g., LR) remain highly effective. While deep learning holds promise, high-dimensional architectures like 3D-CNNs are highly susceptible to mode collapse without massive datasets. Instead, employing feature dimensionality reduction combined with lightweight networks (1D-CNN) is a vastly superior strategy to extract reliable predictive patterns from limited clinical data.
Journal Article
MYB promotes the growth and metastasis of salivary adenoid cystic carcinoma
The incidence of recurrent t(6;9) translocation of the MYB proto-oncogene to NFIB (the gene that encodes nuclear factor 1 B-type) in adenoid cystic carcinoma (ACC) tumour tissues is high. However, MYB [the gene that encodes transcriptional activator Myb (MYB)] overexpression is more common, indicating that MYB serves a key role in ACC. The current study aimed to investigate the role of MYB in salivary (S)ACC growth and metastasis. A total of 50 fresh-frozen SACC tissues and 41 fresh-frozen normal submandibular gland (SMG) tissues were collected to measure MYB mRNA expression, and to analyse the associations between MYB and epithelial-mesenchymal transition (EMT) markers. Compared with normal SMG tissue, SACC tissues demonstrated significantly increased MYB expression, with a high expression rate of 90%. Interestingly, MYB tended to be negatively correlated with CDH1 [the gene that encodes cadherin-1 (E-cadherin)] and positively correlated with VIM (the gene that encodes vimentin), suggesting that MYB is associated with SACC metastasis. To explore the role of MYB in SACC, the authors stably overexpressed and knocked down MYB in SACC cells. The authors of the current study demonstrated that MYB overexpression promoted SACC cell proliferation, migration and invasion, whereas its knockdown inhibited these activities. Additionally, when MYB was overexpressed, CDH1 expression was downregulated, and CDH2 (the gene that encodes cadherin-2), VIM and ACTA2 (the gene that encodes actin, aortic smooth muscle) expression was upregulated. Then, the effect of MYB on lung tumour metastasis was investigated in vivo in non-obese diabetic/severe combined immunodeficiency mice. MYB overexpressing and control cells were injected into the mice through the tail vein. The results revealed that MYB promoted SACC lung metastasis. Collectively, these results demonstrated that MYB is aberrantly overexpressed in SACC tissues, and promotes SACC cell proliferation and metastasis, indicating that MYB may be a novel therapeutic target for SACC.
Journal Article
Relative importance of soil properties and heavy metals/metalloids to modulate microbial community and activity at a smelting site
PurposeHeavy metals/metalloids have adverse effects on soil microorganisms, but the underlying environmental controls remain unclear. This study aims to investigate the influences of multiple heavy metal/metalloid contaminations on soil microbial communities, as well as the effects of soil properties.Materials and methodsSoil samples were collected from a typical Pb/Zn smelter in China. Ecological drivers including soil properties and heavy metal/metalloid contents were determined to evaluate their effects on soil microbial biomass, activity, and community.Results and discussionheavy metals/metalloids had adverse effects on soil microorganisms, as reflected by significant decreases of soil microbial biomass, activity, and bacterial α-diversity with increased contamination levels. The Mantel test and variation partition analysis (VPA) revealed that heavy metals/metalloids strongly affected the bacterial community structure, while soil properties contribute mostly to the variation of microbial activity. Additionally, the influences of soil properties (e.g., total nitrogen, available phosphorus, pH) on microbial biomass, activity, and α-diversity were significant, and stronger than the effects of heavy metals/metalloids. Notably, the interactions between heavy metals/metalloids and soil properties were significant and could explain 61.08% and 33.05% variation of the bacterial community structure and microbial activity, respectively.ConclusionsThese findings demonstrate that the overall effects across soil properties and heavy metals/metalloids are interactive, suggesting that evaluation of the effects of heavy metals/metalloids should also take into account the soil properties.
Journal Article