Development and experimental validation of a machine learning-based disulfidptosis-related ferroptosis score for hepatocellular carcinoma.

Disulfidoptosis and ferroptosis are two distinct programmed cell death pathways that have garnered considerable attention due to their potential as therapeutic targets. However, despite their significance of these pathways, the role of disulfidoptosis-related ferroptosis genes in hepatocellular carcinoma (HCC) remains unclear. In this study, we employed a comprehensive approach that utilized various sophisticated techniques such as Pearson analysis, differential analysis, uniCox regression, lasso, ranger, and multivariable Cox regression to develop the disulfidoptosis-related ferroptosis (DRF) score. We then classified patients with HCC into high- and low-score groups to examine the association between the DRF score and various outcomes, including prognosis, functional enrichment, immune infiltration, immunotherapy, TACE sensitivity, drug sensitivity, and single-cell level function. Finally, we conducted in vitro experiments to validate the function of KIF20A. Our analysis revealed that KIF20A, G6PD, SLC7A11, and SLC2A1 were integral to constructing the DRF score. Our findings showed that patients with low DRF scores had significantly better prognoses and were more responsive to immunotherapy, TACE, and chemotherapy than those with high DRF scores. Based on our results obtained from bulk RNA-seq, single-cell RNA-seq, and in vitro experiments, we identified the cell cycle pathway as the primary distinguished factor between high-score and low-score groups. This study sheds light on the contribution of disulfidoptosis-related ferroptosis genes to the development and progression of HCC. The information gleaned from this study can be leveraged to improve our understanding of their potential as therapeutic targets for HCC treatment.

HCRNet: high-throughput circRNA-binding event identification from CLIP-seq data using deep temporal convolutional network.

Identifying genome-wide binding events between circular RNAs (circRNAs) and RNA-binding proteins (RBPs) can greatly facilitate our understanding of functional mechanisms within circRNAs. Thanks to the development of cross-linked immunoprecipitation sequencing technology, large amounts of genome-wide circRNA binding event data have accumulated, providing opportunities for designing high-performance computational models to discriminate RBP interaction sites and thus to interpret the biological significance of circRNAs. Unfortunately, there are still no computational models sufficiently flexible to accommodate circRNAs from different data scales and with various degrees of feature representation. Here, we present HCRNet, a novel end-to-end framework for identification of circRNA-RBP binding events. To capture the hierarchical relationships, the multi-source biological information is fused to represent circRNAs, including various natural language sequence features. Furthermore, a deep temporal convolutional network incorporating global expectation pooling was developed to exploit the latent nucleotide dependencies in an exhaustive manner. We benchmarked HCRNet on 37 circRNA datasets and 31 linear RNA datasets to demonstrate the effectiveness of our proposed method. To evaluate further the model's robustness, we performed HCRNet on a full-length dataset containing 740 circRNAs. Results indicate that HCRNet generally outperforms existing methods. In addition, motif analyses were conducted to exhibit the interpretability of HCRNet on circRNAs. All supporting source code and data can be downloaded from https://github.com/yangyn533/HCRNet and https://doi.org/10.6084/m9.figshare.16943722.v1. And the web server of HCRNet is publicly accessible at http://39.104.118.143:5001/.

Are 4f-Orbitals Engaged in Covalent Bonding Between Lanthanides and Triphenylphosphine Oxide? An Oxygen K-Edge X-ray Absorption Spectroscopy and Density Functional Theory Study.

The bonding covalency between trivalent lanthanides (Ln = La, Pr, Nd, Eu, Gd) and triphenylphosphine oxide (TPPO) is studied by X-ray absorption spectra (XAS) and density functional theory (DFT) calculations on the LnCl3(TPPO)3 complexes. The O, P, and Cl K-edge XAS for the single crystals of LnCl3(TPPO)3 were collected, and the spectra were interpreted based on DFT calculations. The O and P K-edge XAS spectra showed no significant change across the Ln series in the LnCl3(TPPO)3 complexes, unlike the Cl K-edge XAS spectra. The experimental O K-edge XAS spectra suggest no mixing between the Ln 4f- and the O 2p-orbitals in the LnCl3(TPPO)3 complexes. DFT calculations indicate that the amount of the O 2p character per Ln-O bond is less than 0.1% in the Ln 4f-based orbitals in all of the LnCl3(TPPO)3 complexes. The experimental spectra and theoretical calculations demonstrate that Ln 4f-orbitals are not engaged in the covalent bonding of lanthanides with TPPO, which contrasts the involvement of U 5f-orbitals in covalent bonding in the UO2Cl2(TPPO)2 complex. Results in this work reinforce our previous speculation that bonding covalency is potentially responsible for the extractability of monodentate organophosphorus ligands toward metal ions.

Maternal anaemia prevention and control in China: A policy review.

Maternal anaemia is a major public health problem. Developing maternal anaemia prevention and control policies is an important prerequisite for carrying out evidence-based interventions. This article reviews maternal anaemia prevention and control policies in China, identifies gaps, and provides references for other countries. We examined policies concerning maternal nutrition and other related literature in China, identified through key databases and government websites, and conducted a narrative review of the relevant documentations guided by the Smith Policy-Implementing-Process framework. A total of 65 articles and documents were identified for analysis. We found that Chinese government has committed to reducing maternal anaemia at the policy level, with established objectives and a clear time frame. However, most of policies were not accompanied by operational guidelines, standardized interventions, and vigorous monitoring and evaluation mechanisms, and 85% of the policies don't have quantifiable objectives on anaemia. Maternal anaemia prevention and control services offered in clinical settings were primarily nutrition education and anaemia screening. Population-based interventions such as iron fortification have yet to be scaled up. Furthermore, medical insurance schemes in some regions do not cover anaemia prevention and treatment, and in other regions that offer coverage, the reimbursement rate is low. The number and capacity of health professionals is also limited. Policy changes should focus on the integration of evidence-based interventions into routine antenatal care services and public health service packages, standardization of dosages and provision of iron supplementation, streamline of reimbursement for outpatient expenses, and capacity building of health professionals.

iDeepSubMito: identification of protein submitochondrial localization with deep learning.

Mitochondria are membrane-bound organelles containing over 1000 different proteins involved in mitochondrial function, gene expression and metabolic processes. Accurate localization of those proteins in the mitochondrial compartments is critical to their operation. A few computational methods have been developed for predicting submitochondrial localization from the protein sequences. Unfortunately, most of these computational methods focus on employing biological features or evolutionary information to extract sequence features, which greatly limits the performance of subsequent identification. Moreover, the efficiency of most computational models is still under explored, especially the deep learning feature, which is promising but requires improvement. To address these limitations, we propose a novel computational method called iDeepSubMito to predict the location of mitochondrial proteins to the submitochondrial compartments. First, we adopted a coding scheme using the ProteinELMo to model the probability distribution over the protein sequences and then represent the protein sequences as continuous vectors. Then, we proposed and implemented convolutional neural network architecture based on the bidirectional LSTM with self-attention mechanism, to effectively explore the contextual information and protein sequence semantic features. To demonstrate the effectiveness of our proposed iDeepSubMito, we performed cross-validation on two datasets containing 424 proteins and 570 proteins respectively, and consisting of four different mitochondrial compartments (matrix, inner membrane, outer membrane and intermembrane regions). Experimental results revealed that our method outperformed other computational methods. In addition, we tested iDeepSubMito on the M187, M983 and MitoCarta3.0 to further verify the efficiency of our method. Finally, the motif analysis and the interpretability analysis were conducted to reveal novel insights into subcellular biological functions of mitochondrial proteins. iDeepSubMito source code is available on GitHub at https://github.com/houzl3416/iDeepSubMito.

iCircRBP-DHN: identification of circRNA-RBP interaction sites using deep hierarchical network.

Circular RNAs (circRNAs) are widely expressed in eukaryotes. The genome-wide interactions between circRNAs and RNA-binding proteins (RBPs) can be probed from cross-linking immunoprecipitation with sequencing data. Therefore, computational methods have been developed for identifying RBP binding sites on circRNAs. Unfortunately, those computational methods often suffer from the low discriminative power of feature representations, numerical instability and poor scalability. To address those limitations, we propose a novel computational method called iCircRBP-DHN using deep hierarchical network for discriminating circRNA-RBP binding sites. The network architecture can be regarded as a deep multi-scale residual network followed by bidirectional gated recurrent units (BiGRUs) with the self-attention mechanism, which can simultaneously extract local and global contextual information. Meanwhile, we propose novel encoding schemes by integrating CircRNA2Vec and the K-tuple nucleotide frequency pattern to represent different degrees of nucleotide dependencies. To validate the effectiveness of our proposed iCircRBP-DHN, we compared its performance with other computational methods on 37 circRNAs datasets and 31 linear RNAs datasets, respectively. The experimental results reveal that iCircRBP-DHN can achieve superior performance over those state-of-the-art algorithms. Moreover, we perform motif analysis on circRNAs bound by those different RBPs, demonstrating that our proposed CircRNA2Vec encoding scheme can be promising. The iCircRBP-DHN method is made available at https://github.com/houzl3416/iCircRBP-DHN.

Identification of haploinsufficient genes from epigenomic data using deep forest.

Haploinsufficiency, wherein a single allele is not enough to maintain normal functions, can lead to many diseases including cancers and neurodevelopmental disorders. Recently, computational methods for identifying haploinsufficiency have been developed. However, most of those computational methods suffer from study bias, experimental noise and instability, resulting in unsatisfactory identification of haploinsufficient genes. To address those challenges, we propose a deep forest model, called HaForest, to identify haploinsufficient genes. The multiscale scanning is proposed to extract local contextual representations from input features under Linear Discriminant Analysis. After that, the cascade forest structure is applied to obtain the concatenated features directly by integrating decision-tree-based forests. Meanwhile, to exploit the complex dependency structure among haploinsufficient genes, the LightGBM library is embedded into HaForest to reveal the highly expressive features. To validate the effectiveness of our method, we compared it to several computational methods and four deep learning algorithms on five epigenomic data sets. The results reveal that HaForest achieves superior performance over the other algorithms, demonstrating its unique and complementary performance in identifying haploinsufficient genes. The standalone tool is available at https://github.com/yangyn533/HaForest.

EDCNN: identification of genome-wide RNA-binding proteins using evolutionary deep convolutional neural network.

MOTIVATION: RNA-binding proteins (RBPs) are a group of proteins associated with RNA regulation and metabolism, and play an essential role in mediating the maturation, transport, localization and translation of RNA. Recently, Genome-wide RNA-binding event detection methods have been developed to predict RBPs. Unfortunately, the existing computational methods usually suffer some limitations, such as high-dimensionality, data sparsity and low model performance. RESULTS: Deep convolution neural network has a useful advantage for solving high-dimensional and sparse data. To improve further the performance of deep convolution neural network, we propose evolutionary deep convolutional neural network (EDCNN) to identify protein-RNA interactions by synergizing evolutionary optimization with gradient descent to enhance deep conventional neural network. In particular, EDCNN combines evolutionary algorithms and different gradient descent models in a complementary algorithm, where the gradient descent and evolution steps can alternately optimize the RNA-binding event search. To validate the performance of EDCNN, an experiment is conducted on two large-scale CLIP-seq datasets, and results reveal that EDCNN provides superior performance to other state-of-the-art methods. Furthermore, time complexity analysis, parameter analysis and motif analysis are conducted to demonstrate the effectiveness of our proposed algorithm from several perspectives. AVAILABILITY AND IMPLEMENTATION: The EDCNN algorithm is available at GitHub: https://github.com/yaweiwang1232/EDCNN. Both the software and the supporting data can be downloaded from: https://figshare.com/articles/software/EDCNN/16803217. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Harmonic Suppression Induced by Three-Electron Dynamics of Li in Strong Laser Fields.

We build a model to elucidate the high harmonic generation in combined EUV and midinfrared laser fields by embodying the spin-resolved three-electron dynamics. The EUV pulse ionizes an inner-shell electron, and the midinfrared laser drives the photoelectron and steers the electron-ion rescattering. Depending on the spin of the photoelectron, the residual ion including two bound electrons can be either in a single spin configuration or in a coherent superposition of different spin configurations. In the latter case, the two electrons in the ion swap their orbits, leading to a deep valley in the harmonic spectrum. The model results agree with the time-dependent Schrödinger equation simulations including three active electrons. The intriguing picture explored in this work is fundamentally distinguished from all reported scenarios relied on spin-orbit coupling, but originates from the exchanges asymmetry of two-electron wave functions.

Genome-wide identification and characterization of DNA enhancers with a stacked multivariate fusion framework.

Enhancers are short non-coding DNA sequences outside of the target promoter regions that can be bound by specific proteins to increase a gene's transcriptional activity, which has a crucial role in the spatiotemporal and quantitative regulation of gene expression. However, enhancers do not have a specific sequence motifs or structures, and their scattered distribution in the genome makes the identification of enhancers from human cell lines particularly challenging. Here we present a novel, stacked multivariate fusion framework called SMFM, which enables a comprehensive identification and analysis of enhancers from regulatory DNA sequences as well as their interpretation. Specifically, to characterize the hierarchical relationships of enhancer sequences, multi-source biological information and dynamic semantic information are fused to represent regulatory DNA enhancer sequences. Then, we implement a deep learning-based sequence network to learn the feature representation of the enhancer sequences comprehensively and to extract the implicit relationships in the dynamic semantic information. Ultimately, an ensemble machine learning classifier is trained based on the refined multi-source features and dynamic implicit relations obtained from the deep learning-based sequence network. Benchmarking experiments demonstrated that SMFM significantly outperforms other existing methods using several evaluation metrics. In addition, an independent test set was used to validate the generalization performance of SMFM by comparing it to other state-of-the-art enhancer identification methods. Moreover, we performed motif analysis based on the contribution scores of different bases of enhancer sequences to the final identification results. Besides, we conducted interpretability analysis of the identified enhancer sequences based on attention weights of EnhancerBERT, a fine-tuned BERT model that provides new insights into exploring the gene semantic information likely to underlie the discovered enhancers in an interpretable manner. Finally, in a human placenta study with 4,562 active distal gene regulatory enhancers, SMFM successfully exposed tissue-related placental development and the differential mechanism, demonstrating the generalizability and stability of our proposed framework.

Synthesis, Structure, and Theoretical Calculations on NpO2Br42.

The actinide-halogen complexes (AnO2X42-, X = Cl, Br, and I) are the simplest and most representative compounds for studying the bonding nature of actinides with ligands. In this work, we attempted to synthesize the crystals of NpO2X42- (X = Cl, Br, and I). The crystals of NpO2Cl42- and NpO2Br42- were successfully synthesized, in which the structure of NpO2Br42- was obtained for the first time. The crystal of NpO2I42- could not be obtained due to the rapid reduction of Np(VI) to Np(V) by I-. The molecular structures of NpO2Cl42- and NpO2Br42- were characterized by single-crystal X-ray diffraction and infrared, Raman, and UV-Vis-NIR absorption spectroscopy. The complexes of NpO2X42- (X = Cl, Br, and I) were also investigated by density functional theory calculations, and the calculated vibration frequencies and absorption features were comparable to the experimental results. Both the experimental results and theoretical calculations demonstrate the strengthened Np-O bonds and the weakened Np-X bonds across the NpO2X42- series; however, the population analysis on the frontier molecular orbitals (MOs) of NpO2X42- indicates a slight reduction in the Np-O bonding covalency and an enhancement in the Np-X bonding covalency from NpO2Cl42- to NpO2I42-. Results in this work have enriched the crystal database of the AnO2X42- family and provided insights into the bonding nature in the actinide complexes with soft- and hard-donor ligands.

The relationship between the local environment, N-type, spin state and catalytic functionality of carbon-hosted FeII/III-N4 for the conversion of CO2 to CO.

Iron and nitrogen codoped carbon (Fe-N-C) materials are promising alternatives to precious metal catalysts for the carbon dioxide electrochemical reduction reaction (CO2RR); however, the influence of the oxidation state, spin state, N-type and local environment of Fe-N on its catalytic activity remains poorly understood. In this study, we employed density functional theory (DFT) calculations to evaluate the catalytic activity of the pyridine-type FeIII/IIN4 motifs at the armchair and zigzag edges, the activity of the pyrrole-type FeIII/IIN4 sites in the bulk plane of carbon-based materials for the two-electron CO2RR by analyzing the stability of initial reactants, free-energy evolutions and energy barriers for the possible elementary reactions in the different spin states. The Fe ions in the armchair-edge pyridine-type FeN4 are mainly in the +2 oxidation state, and use the high spin state in the spin uncoupling manner to achieve the most efficient CO2-COOH-CO conversion. In contrast, the zigzag-edge pyridine-type FeIIN4 employs the medium spin state in the spin uncoupling manner to achieve the highest catalytic activity in the two-electron CO2RR. However, the Fe ions in the pyrrole-type bulk-hosted FeN4 mainly remain in the +3 valence state during the conversion process of CO2 to CO and utilize the medium spin state with spin coupling to obtain the highest catalytic activity. The corresponding kinetic analyses show that the armchair-edge pyridine-type FeIIN4 catalyst exhibited the best catalytic performance among the three cases. Consequently, these findings present significant insights into the design of Fe single-atom catalysts for enhancing CO2RR catalytic activity by producing more armchair-edge pyridine-type FeN4 sites, which may be constructed by introducing micropores in the carbon materials.

Biological interactions of polystyrene nanoplastics: Their cytotoxic and immunotoxic effects on the hepatic and enteric systems.

As emerging pollutants in the environment, nanoplastics (NPs) can cross biological barriers and be enriched in organisms, posing a greatest threat to the health of livestock and humans. However, the size-dependent toxic effects of NPs in higher mammals remain largely unknown. To determine the size-dependent potential toxicities of NPs, we exposed mouse (AML-12) and human (L02) liver cell lines in vitro, and 6-week-old C57BL/6 mice (well-known preclinical model) in vivo to five different sizes of polystyrene NPs (PS-NPs) (20, 50, 100, 200 and 500 nm). We found that ultra-small NPs (20 nm) induced the highest cytotoxicity in mouse and human liver cell lines, causing oxidative stress and mitochondrial membrane potential loss on AML-12 cells. Unexpectedly in vivo, after long-term oral exposure to PS-NPs (75 mg/kg), medium NPs (200 nm) and large NPs (500 nm) induced significant hepatotoxicity, evidenced by increased oxidative stress, liver dysfunction, and lipid metabolism disorders. Most importantly, medium or large NPs generated local immunotoxic effects via recruiting and activating more numbers of neutrophils and monocytes in the liver or intestine, which potentially resulted in increased proinflammatory cytokine secretion and the tissue damage. The discrepancy in in vitro-in vivo toxic results might be attributed to the different properties of biodistribution and tissue accumulation of different sized NPs in vivo. Our study provides new insights regarding the hepatotoxicity and immunotoxicity of NPs on human and livestock health, warranting us to take immense measures to prevent these NPs-associated health damage.

Involvement of 5f Orbitals in the Covalent Bonding between the Uranyl Ion and Trialkyl Phosphine Oxide: Unraveled by Oxygen K-Edge X-ray Absorption Spectroscopy and Density Functional Theory.

Monodentate organophosphorus ligands have been used for the extraction of the uranyl ion (UO22+) for over half a century and have exhibited exceptional extractability and selectivity toward the uranyl ion due to the presence of the phosphoryl group (O═P). Tributyl phosphate (TBP) is the extractant of the world-renowned PUREX process, which selectively recovers uranium from spent nuclear fuel. Trialkyl phosphine oxide (TRPO) shows extractability toward the uranyl ion that far exceeds that for other metal ions, and it has been used in the TRPO process. To date, however, the mechanism of the high affinity of the phosphoryl group for UO22+ remains elusive. We herein investigate the bonding covalency in a series of complexes of UO22+ with TRPO by oxygen K-edge X-ray absorption spectroscopy (XAS) in combination with density functional theory (DFT) calculations. Four TRPO ligands with different R substituents are examined in this work, for which both the ligands and their uranyl complexes are crystallized and investigated. The study of the electronic structure of the TRPO ligands reveals that the two TRPO molecules, irrespective of their substituents, can engage in σ- and π-type interactions with U 5f and 6d orbitals in the UO2Cl2(TRPO)2 complexes. Although both the axial (Oyl) and equatorial (Oeq) oxygen atoms in the UO2Cl2(TRPO)2 complexes contribute to the X-ray absorption, the first pre-edge feature in the O K-edge XAS with a small intensity is exclusively contributed by Oeq and is assigned to the transition from Oeq 1s orbitals to the unoccupied molecular orbitals of 1b1u + 1b2u + 1b3u symmetries resulting from the σ- and π-type mixing between U 5f and Oeq 2p orbitals. The small intensity in the experimental spectra is consistent with the small amount of Oeq 2p character in these orbitals for the four UO2Cl2(TRPO)2 complexes as obtained by Mulliken population analysis. The DFT calculations demonstrate that the U 6d orbitals are also involved in the U-TRPO bonding interactions in the UO2Cl2(TRPO)2 complexes. The covalent bonding interactions between TRPO and UO22+, especially the contributions from U 5f orbitals, while appearing to be small, are sufficiently responsible for the exceptional extractability and selectivity of monodentate organophosphorus ligands for the uranyl ion. Our results provide valuable insight into the fundamental actinide chemistry and are expected to directly guide actinide separation schemes needed for the development of advanced nuclear fuel cycle technologies.

Regulation of different protonated states of two intimate histidine residues on the reductive half-reaction of glucose oxidase.

Glucose oxidase (GOx) can catalyze the oxidation of ß-D-glucose under mild conditions to directly convert biological energy into electrical energy, which has great potential for applications in the fields of enzyme biofuel cells and glucose biosensors. In enzymatic biofuel cells, GOx is often used as an anodic catalyst to improve the performance. The important role of two intimate histidine residues, His505 and His548 (PDB code 4YNU), in the GOx active center has been highlighted in the catalytic oxidation of ß-D-glucose, but there is still a lack of systematic examination on the influence of different protonated states of His505 and His548 on the catalytic oxidation of ß-D-glucose in GOx. Therefore, in the present work, the GOx active center under the possible protonated states of His548 and His505 is systematically examined by using ONIOM calculations, as well as the influence of remote Arg210 is considered. The calculations reveal that the intimate His505 and His548 can modulate the interaction of the ß-D-glucose substrate with isoalloxazine and then control the deprotonization of the hydroxyl group bound to the anomeric carbon of ß-D-glucose like controllers. The remote Arg210 provides the driving force for the transfer of two electrons from ß-D-glucose to isoalloxazine of FAD via the long-range electrostatic attraction like a horse. Specially, the protonated His505 can serve as a good helper of Arg210 to promote the occurring of the two-proton-coupled two-electron transfer from ß-D-glucose to isoalloxazine and His548 in the active center of GOx. These findings provide much insight into the catalytic reactions of GOx in a low pH environment, which may be beneficial to expand the applications of GOx.

Relationship between moderate to late preterm, diet types and developmental delay in less-developed rural China.

Aim: To measure the development of moderate to late preterm children by Ages and Stages Questionnaires (ASQ) and explore the relationship between moderate to late preterm, diet types and development delay in less-developed rural China.Methods: Data were collected from a cross-sectional community-based survey, which recruited 1748 children aged 1-59 months in eight counties of China. Caregivers of these children completed the Chinese version of ASQ-3 (ASQ-C) while physical examination and questionnaires on socio-demographic characteristics were conducted. Multivariate logistic regressions were used to analyze the association between moderate to late preterm and suspected developmental delay, as well as the association between diet types and suspected developmental delay. Consumption of certain food types was compared between moderate to late preterm and full-term children.Results: The prevalence of suspected overall developmental delay was 31.3% in the moderate to the late preterm group, compared with 21.6% in the full-term group. Moderate to late preterm birth was not associated with total suspected developmental delay and developmental delay in all the domains of ASQ, except for fine motor (OR = 2.43 95% C.I.: 1.04-5.56). The intake of vegetables and fruits had a protective influence on developmental delay in fine motor function, and moderate to late preterm children had lower relative consumption of fruits and vegetables than full-term children.Conclusion: Moderate to late preterm children in rural China showed an increased likelihood of developmental delay in fine motor function. Future interventions to improve the intake of vegetables and fruits in moderate to late preterm children are recommended.

Bufalin Inhibits Tumorigenesis, Stemness, and Epithelial-Mesenchymal Transition in Colorectal Cancer through a C-Kit/Slug Signaling Axis.

Colorectal cancer (CRC) is a major source of morbidity and mortality, characterized by intratumoral heterogeneity and the presence of cancer stem cells (CSCs). Bufalin has potent activity against many tumors, but studies of its effect on CRC stemness are limited. We explored bufalin's function and mechanism using CRC patient-derived organoids (PDOs) and cell lines. In CRC cells, bufalin prevented nuclear translocation of ß-catenin and down-regulated CSC markers (CD44, CD133, LGR5), pluripotency factors, and epithelial-mesenchymal transition (EMT) markers (N-Cadherin, Slug, ZEB1). Functionally, bufalin inhibited CRC spheroid formation, aldehyde dehydrogenase activity, migration, and invasion. Network analysis identified a C-Kit/Slug signaling axis accounting for bufalin's anti-stemness activity. Bufalin treatment significantly downregulated C-Kit, as predicted. Furthermore, overexpression of C-Kit induced Slug expression, spheroid formation, and bufalin resistance. Similarly, overexpression of Slug resulted in increased expression of C-Kit and identical functional effects, demonstrating a pro-stemness feedback loop. For further study, we established PDOs from diagnostic colonoscopy. Bufalin differentially inhibited PDO growth and proliferation, induced apoptosis, restored E-cadherin, and downregulated CSC markers CD133 and C-Myc, dependent on C-Kit/Slug. These findings suggest that the C-Kit/Slug axis plays a pivotal role in regulating CRC stemness, and reveal that targeting this axis can inhibit CRC growth and progression.

Breastfeeding Practices and Overweight/Obesity Among Children Under 5 Years of Age: A Multistage Random Sampling Survey in Central and Western China.

OBJECTIVES: To describe the prevalence of overweight and obesity among children under 5 years old, assess the indicators of breastfeeding practices, and explore the associations between breastfeeding practices and early childhood overweight/obesity. METHODS: The survey was conducted in 20 counties in central and western China in 2016. All children under 5 years old were physically measured for anthropometric data and their breastfeeding practices were obtained through a face-to-face questionnaire interview. We performed logistic regressions to assess the associations of different breastfeeding practices with overweight/obesity. RESULTS: The prevalence of overweight and obesity among children under 5 years old were 8.7% and 2.6%, respectively. Overall, 93.6% of children were breastfed, while only 20.7% had exclusive breastfeeding under 6 months of age and about half of the children under 5 years old were weaned at 12 months. Compared with children with a duration of breastfeeding ≥ 12 months, children who have been breastfed for < 6 months were significantly associated with a 97% increased risk of overweight/obesity (OR 1.97, 95% CI 1.34-2.88, P = 0.001). CONCLUSIONS FOR PRACTICE: The present study showed that overweight and obesity among children under 5 years old in central and western China remained an important childhood health concern. The rates of most indicators of breastfeeding practices were low, which needed more public attention. Moreover, we found that a shorter duration of breastfeeding was associated with an increased risk of overweight/obesity among children in central and western China.

Quality of care and suspected developmental delay among children aged 1-59 months: a cross-sectional study in 8 counties of rural China.

BACKGROUND: The data about quality of care of more than 70 countries were available from UNICEF but little was known about China. We examined the status about quality of care and explored its associations with developmental outcomes in Chinese children. METHODS: A cross-sectional study with probability proportional to size sampling method was conducted in 8 counties of rural China. A total 1927 children were assessed on development status using Ages and Stages Questionnaires-Chinese (ASQ-C) based on Chinese normative data. Nutritional status was derived from the anthropometric method following WHO guidelines. Caregivers were interviewed through household questionnaires from UNICEF's 5th Multiple Indicator Cluster Survey to understand the quality of care, including the status of availability of children's books, availability of playthings, support for learning, fathers' support for learning and inadequate care. Moreover, quality of care was explored to be categorized into three levels (poor, medium and good) for overall assessment. Multivariable logistic regression model was applied to estimate the odds ratios and 95% confidence intervals between quality of care and suspected developmental delay (SDD) after adjustment for potential confounding variables. RESULTS: The proportions of availability of children's books, playthings, support for learning, fathers' support for learning and inadequate care were 36.8, 91.3, 83.1, 16.4 and 4.9%, respectively. When compared to available data of more than 70 countries and areas, the quality of care in rural China was in the middle to upper level. After adjustment for potential confounding variables, multivariable analysis showed that SDD in overall ASQ remained negatively associated with availability of children's books (odds ratio [OR] and 95% confidence interval [CI]: 1.64 [1.27-2.12]), playthings (OR and 95% CI: 2.23 [1.52-3.27]) and support for learning (OR and 95% CI: 1.81 [1.06-3.10]). When compared with children under good quality of care, children under medium and poor quality of care had higher prevalence of SDD in overall ASQ (OR and 95% CI: 1.59 [1.21-2.07]; 3.05 [1.96-4.74]). CONCLUSIONS: Quality of care in rural China still had scope for improvement. Better quality of care had negative associations with SDD.

Correntropy Based Matrix Completion.

This paper studies the matrix completion problems when the entries are contaminated by non-Gaussian noise or outliers. The proposed approach employs a nonconvex loss function induced by the maximum correntropy criterion. With the help of this loss function, we develop a rank constrained, as well as a nuclear norm regularized model, which is resistant to non-Gaussian noise and outliers. However, its non-convexity also leads to certain difficulties. To tackle this problem, we use the simple iterative soft and hard thresholding strategies. We show that when extending to the general affine rank minimization problems, under proper conditions, certain recoverability results can be obtained for the proposed algorithms. Numerical experiments indicate the improved performance of our proposed approach.