Long non-coding RNA PFI inhibits apoptosis of alveolar epithelial cells to alleviate lung injury via miR-328-3p/Creb1 axis.

Acute lung injury (ALI), a common clinical type of critical illness, is an acute hypoxic respiratory insufficiency caused by the damage of alveolar epithelial cells and capillary endothelial cells. In a previous study, we reported a novel lncRNA, lncRNA PFI, which could protect against pulmonary fibrosis in pulmonary fibroblasts. The present study demonstrated that lncRNA PFI was downregulated in alveolar epithelial cell of mice injury lung tissues, and further investigated the role of lncRNA PFI in regulating inflammation-induced alveolar epithelial cell apoptosis. Overexpression of lncRNA PFI could partially abrogated bleomycin induced type II AECs injured. Subsequently, bioinformatic prediction revealed that lncRNA PFI might directly bind to miR-328-3p, and further AGO-2 RNA binding protein immunoprecipitation (RIP) assay confirmed their binding relationship. Furthermore, miR-328-3p promoted apoptosis in MLE-12 cells by limiting the activation of the Creb1, a protein correlated with cell apoptosis, whereas AMO-328-3p ablated the pro-apoptosis effect of silencing lncRNA PFI in MLE-12 cells. While miR-328-3p could also ablate the function of lncRNA PFI in bleomycin treated human lung epithelial cells. Enhanced expression of lncRNA PFI reversed the LPS-induced lung injury in mice. Overall, these data reveal that lncRNA PFI mitigated acute lung injury through miR-328-3p/Creb1 pathway in alveolar epithelial cells.

Dendrobine regulates STAT3 to attenuate mitochondrial dysfunction and senescence in vascular endothelial cells triggered by oxidized low-density lipoprotein.

Our previous studies have highlighted the potential therapeutic efficacy of dendrobine, an alkaloid, in atherosclerosis (AS), nevertheless, the underlying mechanism remains unclear. This study employs a combination of network pharmacology and in vitro experiments to explore the regulatory pathways involved. Through network pharmacology, the biological function for intersection targets between dendrobine and AS were identified. Molecular docking was conducted to investigate the interaction between the dominant target and dendrobine. Human umbilical vein endothelial cells (HUVECs) were treated with oxidized low-density lipoprotein (ox-LDL) to mimic AS, and the effects of dendrobine on cell viability, lipid deposition, mitochondrial function, and cellular senescence were evaluated. Subsequently, cells were treated with the mitophagy inhibitor Mdivi-1 and the STAT3 agonist colivelin to assess the role of mitophagy and STAT3 signaling in dendrobine regulation. Intersection targets were associated with biological processes, including reactive oxygen species production. Dendrobine attenuated the effects of ox-LDL treatment on HUVECs, mitigating changes in cell activity, lipid deposition, mitochondrial function, and cellular senescence. Both Mdivi-1 and colivelin treatments resulted in decreased cell viability and increased cellular senescence, with colivelin suppressing mitophagy. Cotreatment with Mdivi-1 and colivelin further aggravated cellular senescence and inhibited FoxO signaling. Together, this study indicated that dendrobine regulated the STAT3/FoxO signaling pathway, alleviating mitochondrial dysfunction and cellular senescence. This study contributes valuable insights to the potential clinical application of dendrobine.

Angelica sinensis polysaccharides prevents hematopoietic regression in D-Galactose-Induced aging model via attenuation of oxidative stress in hematopoietic microenvironment.

BACKGROUND: Extrinsic molecular mechanisms that regulate hematopoietic stem/progenitor cell (HSPC) aging are still poorly understood, and a potential protective medication needs to be explored. MATERIALS AND METHODS: The senescent parameters of hematopoietic cells and bone marrow stromal cells (BMSCs) including cell cycle analysis, senescence-associated SA-ß-gal staining and signals, hematopoietic factors and cellular junction were analyzed in femur and tibia of rats. Furthermore, Sca-1+ HSPCs and BMSCs co-culture system was established to evaluate the direct effects of BMSC feeder layer to HSPCs. Oxidative DNA damage indicators in Sca-1+ HSCs and senescence-associated secretory phenotype (SASP) of BMSCs, gap junction intercellular communication between BMSCs, osteogenesis/adipogenisis differentiation balance of BMSCs were detected. RESULTS: In the D-gal pre-administrated rats, ASP treatment rescued senescence of hematopoietic cells and BMSCs, reserved CFU-GEMM; also, ASP treatment attenuated stromal oxidative load, ameliorated SCF, CXCL12, and GM-CSF production, increased Connexin-43 (Cx43) expression. BMSCs and Sca-1+ HSPCs co-cultivation demonstrated that ASP treatment prevented oxidative DNA damage response in co-cultured Sca-1+ HSPCs induced by D-gal pre-administration of feeder layer and the underlying mechanism may be related to ASP ameliorating feeder layer dysfunction due to D-gal induced senescence via inhibiting secretion of IL-1, IL-6, TNF-α, and RANTES, enhancing Cx43-mediated intercellular communication, improving Runx2 expression whereas decreasing PPARγ expression in BMSCs. CONCLUSION: The antioxidant property of ASP may provide a stroma-mediated potential therapeutic strategy for HSPC aging.

Genome evolution of blind subterranean mole rats: Adaptive peripatric versus sympatric speciation.

Speciation mechanisms remain controversial. Two speciation models occur in Israeli subterranean mole rats, genus Spalax: a regional speciation cline southward of four peripatric climatic chromosomal species and a local, geologic-edaphic, genic, and sympatric speciation. Here we highlight their genome evolution. The five species were separated into five genetic clusters by single nucleotide polymorphisms, copy number variations (CNVs), repeatome, and methylome in sympatry. The regional interspecific divergence correspond to Pleistocene climatic cycles. Climate warmings caused chromosomal speciation. Triple effective population size, Ne , declines match glacial cold cycles. Adaptive genes evolved under positive selection to underground stresses and to divergent climates, involving interspecies reproductive isolation. Genomic islands evolved mainly due to adaptive evolution involving ancient polymorphisms. Repeatome, including both CNV and LINE1 repetitive elements, separated the five species. Methylation in sympatry identified geologically chalk-basalt species that differentially affect thermoregulation, hypoxia, DNA repair, P53, and other pathways. Genome adaptive evolution highlights climatic and geologic-edaphic stress evolution and the two speciation models, peripatric and sympatric.

Critical role of PAFR/YAP1 positive feedback loop in cardiac fibrosis.

Aberrant activation of cardiac fibroblasts is the main cause and character of cardiac fibrosis, and inhibition of cardiac fibrosis becomes a promising treatment for cardiac diseases. Platelet-activating factor (PAF) and Hippo pathway is recently recognized as key signaling mechanisms in cardiovascular diseases. In this study we explored the potential roles of PAF and Hippo signaling pathway in cardiac fibrosis. Myocardial infarction (MI) was induced in mice by left anterior descending artery ligation. After 28 days, the mice were sacrificed, and the hearts were collected for analyses. We showed that PAF receptor (PAFR) and yes-associated protein 1 (YAP1, a key effector in the Hippo pathway) were significantly increased in the heart of MI mice. Increased expression of PAFR and YAP1 was also observed in angiotensin II (Ang II)-treated mouse cardiac fibroblasts. In mouse cardiac fibroblasts, forced expression of YAP1 increased cell viability, resulted in collagen deposition and promoted fibroblast-myofibroblast transition. We showed that PAF induced fibrogenesis through activation of YAP1 and promoted its nuclear translocation via interacting with PAFR, while YAP1 promoted the expression of PAFR by binding to and activating transcription factor TEAD1. More importantly, silencing PAFR or YAP1 by shRNA, or using transgenic mice to induce the conditional deletion of YAP1 in cardiac fibroblasts, impeded cardiac fibrosis and improved cardiac function in MI mice. Taken together, this study elucidates the role and mechanisms of PAFR/YAP1 positive feedback loop in cardiac fibrosis, suggesting a potential role of this pathway as novel therapeutic targets in cardiac fibrosis.

Graph-Based Motion Artifacts Detection Method from Head Computed Tomography Images.

Computed tomography (CT) images play an important role due to effectiveness and accessibility, however, motion artifacts may obscure or simulate pathology and dramatically degrade the diagnosis accuracy. In recent years, convolutional neural networks (CNNs) have achieved state-of-the-art performance in medical imaging due to the powerful learning ability with the help of the advanced hardware technology. Unfortunately, CNNs have significant overhead on memory usage and computational resources and are labeled 'black-box' by scholars for their complex underlying structures. To this end, an interpretable graph-based method has been proposed for motion artifacts detection from head CT images in this paper. From a topological perspective, the artifacts detection problem has been reformulated as a complex network classification problem based on the network topological characteristics of the corresponding complex networks. A motion artifacts detection method based on complex networks (MADM-CN) has been proposed. Firstly, the graph of each CT image is constructed based on the theory of complex networks. Secondly, slice-to-slice relationship has been explored by multiple graph construction. In addition, network topological characteristics are investigated locally and globally, consistent topological characteristics including average degree, average clustering coefficient have been utilized for classification. The experimental results have demonstrated that the proposed MADM-CN has achieved better performance over conventional machine learning and deep learning methods on a real CT dataset, reaching up to 98% of the accuracy and 97% of the sensitivity.

[Spectrum-effect relationship between UPLC fingerprint of Smilax china and anti-pelvic inflammation in rats].

To study the correlation between ultra high performance liquid chromatography( UPLC) fingerprint of Smilax china and its anti-pelvic inflammatory effect,and to explore the pharmacodynamic material basis of S. china against pelvic inflammatory disease.UPLC fingerprints of 10 batches of S. china from different habitats were established,and the values of SOD,MDA,TNF-α,and IL-6 in rats with pelvic inflammation were measured. The weight of each single pharmacodynamics index to the total efficacy was determined by analytic hierarchy process,and the contribution of each peak in fingerprints to the each single pharmacodynamics index and total efficacy was analyzed by the grey relational analysis. Then the structures of chemical constituents at the identified peaks were confirmed by comparing with the reference substance. The 27 common characteristic peaks of UPLC fingerprints were all related to the anti-pelvic inflammation effect of S. china,of which 13 peaks were identified as peak 2( 3,5-dihydroxy-2-methylbenzoic acid-3-O-glucoside),peak 3( chlorogenic acid),peak 5( 2,7,4-trihydroxydihydroflavone-5-O-glucoside),peak 6( 7,4-dihydroxydihydroflavonol-5-O-glucoside),peak 7( taxifolin-7-O-glucoside),peak 9( taxifolin),peak 10( polydatin),peak 11( oxyresveratrol),peak 12( astilbin),peak15( resveratrol),peak 16( quercitrin),peak 18( engeletin) and peak 24( kaempferol). The correlation degree of 21 peaks and the total efficacy was greater than 0. 8,and the top 10 ranked by correlation degree were as follows: peak 1,3,7,19,18,17,4,11,16,and 21. The results showed that the anti-pelvic inflammation effect of S. china was achieved by the combined action of pharmacodynamic substances. In order to control the quality of S. china and its prepared slices more effectively,the index components of content detection should be selected reasonably.

Angelica sinensis Polysaccharides Ameliorate Stress-Induced Premature Senescence of Hematopoietic Cell via Protecting Bone Marrow Stromal Cells from Oxidative Injuries Caused by 5-Fluorouracil.

Myelosuppression is the most common complication of chemotherapy. Decline of self-renewal capacity and stress-induced premature senescence (SIPS) of hematopoietic stem cells (HSCs) induced by chemotherapeutic agents may be the cause of long-term myelosuppression after chemotherapy. Whether the mechanism of SIPS of hematopoietic cells relates to chemotherapeutic injury occurred in hematopoietic microenvironment (HM) is still not well elucidated. This study explored the protective effect of Angelica sinensis polysaccharide (ASP), an acetone extract polysaccharide found as the major effective ingredients of a traditional Chinese medicinal herb named Chinese Angelica (Dong Quai), on oxidative damage of homo sapiens bone marrow/stroma cell line (HS-5) caused by 5-fluorouracil (5-FU), and the effect of ASP relieving oxidative stress in HM on SIPS of hematopoietic cells. Tumor-suppressive doses of 5-FU inhibited the growth of HS-5 in a dose-dependent and time-dependent manner. 5-FU induced HS-5 apoptosis and also accumulated cellular hallmarks of senescence including cell cycle arrest and typical senescence-associated ß-galactosidase positive staining. The intracellular reactive oxygen species (ROS) was increased in 5-FU treated HS-5 cells and coinstantaneous with attenuated antioxidant capacity marked by superoxide dismutase and glutathione peroxidase. Oxidative stress initiated DNA damage indicated by increased γH2AX and 8-OHdG. Oxidative damage of HS-5 cells resulted in declined hematopoietic stimulating factors including stem cell factor (SCF), stromal cell-derived factor (SDF), and granulocyte-macrophage colony-stimulating factor (GM-CSF), however, elevated inflammatory chemokines such as RANTES. In addition, gap junction channel protein expression and mediated intercellular communications were attenuated after 5-FU treatment. Significantly, co-culture on 5-FU treated HS-5 feeder layer resulted in less quantity of human umbilical cord blood-derived hematopoietic cells and CD34⁺ hematopoietic stem/progenitor cells (HSPCs), and SIPS of hematopoietic cells. However, it is noteworthy that ASP ameliorated SIPS of hematopoietic cells by the mechanism of protecting bone marrow stromal cells from chemotherapeutic injury via mitigating oxidative damage of stromal cells and improving their hematopoietic function. This study provides a new strategy to alleviate the complication of conventional cancer therapy using chemotherapeutic agents.

Novel Near-Lossless Compression Algorithm for Medical Sequence Images with Adaptive Block-Based Spatial Prediction.

To address the low compression efficiency of lossless compression and the low image quality of general near-lossless compression, a novel near-lossless compression algorithm based on adaptive spatial prediction is proposed for medical sequence images for possible diagnostic use in this paper. The proposed method employs adaptive block size-based spatial prediction to predict blocks directly in the spatial domain and Lossless Hadamard Transform before quantization to improve the quality of reconstructed images. The block-based prediction breaks the pixel neighborhood constraint and takes full advantage of the local spatial correlations found in medical images. The adaptive block size guarantees a more rational division of images and the improved use of the local structure. The results indicate that the proposed algorithm can efficiently compress medical images and produces a better peak signal-to-noise ratio (PSNR) under the same pre-defined distortion than other near-lossless methods.

Coptisine prevents angiotensin II­induced endothelial cell injury and senescence via the lncRNA SNHG12/miR­603/NAMPT pathway.

Atherosclerosis (AS) is a major health problem and targeting the associated molecular pathways is critical for developing therapies. The present study investigated the effect of coptisine on human umbilical vein endothelial cells (HUVECs) in response to angiotensin II (Ang II) induction by focusing on cellular senescence, apoptosis and inflammation. HUVECs were treated with different Ang II concentrations and long non-coding RNA small nucleolar RNA host gene 12 (SNHG12), microRNA (miRNA/miR)-603 and nicotinamide phosphoribosyltransferase (NAMPT) expressions were assessed. Cell viability, nicotinamide adenine dinucleotide (NAD+) levels, senescence, apoptosis and inflammation were assessed. The interactions among SNHG12, miR-603 and NAMPT were investigated using dual-luciferase reporter gene assays and RNA pull-down experiments. Coptisine treatment increased SNHG12 expression and attenuated Ang II-induced adverse effects in HUVECs. SNHG12 silencing abrogated coptisine's protective effects, indicating that SNHG12 is a key mediator. SNHG12 targets miR-603, which then directly targets NAMPT, an age-related gene involved in NAD(+) regulation. Coptisine modulated the SNHG12/miR-603/NAMPT pathway and miR-603 inhibition enhanced the protective effects of coptisine. NAMPT overexpression reversed the negative effects of miR-603 and enhanced the protective effect of the miR-603 inhibitor. Finally, the protective mechanism of coptisine is linked to the regulation of NAD(+), sirtuin 3 (SIRT3) and p53. Coptisine treatment counteracted the AngII-induced increase in SIRT3 and p53 protein levels, whereas the miR-603 inhibitor potentiated the effect of coptisine. SNHG12 knockdown partially abolished these effects, which were reversed by NAMPT overexpression. In conclusion, the present study revealed a novel protective mechanism involving the SNHG12/miR-603/NAMPT pathway in HUVECs exposed to Ang II, highlighting the potential therapeutic application of coptisine in treating atherosclerosis. These results suggested that coptisine exerts its protective effects by modulating the SNHG12/miR-603/NAMPT axis, which ultimately affects the regulation of NAD(+), SIRT3 and p53. Future studies should explore the potential of the SNHG12/miR-603/NAMPT pathway as a target for developing novel AS therapies.

Fabrication of resveratrol-loaded soy protein isolate-glycyrrhizin nanocomplex for improving bioavailability via pH-responsive hydrogel properties.

Resveratrol (RES) is a functional polyphenol that suffers from low water solubility and poor bioavailability. A novel RES-loaded soy protein isolate-dipotassium glycyrrhizinate (SPI-DG) nanocomplex (RES@SPI-DG) was designed and evaluated in this study. RES@SPI-DG was prepared using a simple but novel self-assembly ultrasonic-assisted pH-driven method. The interactions between RES and SPI-DG were non-covalent bonds, including hydrophobic interactions, hydrogen bonds, and van der Waals interactions. RES@SPI-DG exhibited high encapsulation efficiency (97.60 ± 0.38 %) and loading capacity (8.74 ± 0.03 %) of RES with a uniform small size (68.39 ± 1.10 nm). RES in RES@SPI-DG was in an amorphous state and demonstrated a 24-h apparent solubility 482.53-fold higher than bare RES. RES@SPI-DG also showed strong in vitro antioxidant properties. The pH-responsive hydrogel character of SPI-DG makes it an effective intestine-targeted delivery system that could retard the release of RES in a simulated stomach and accelerate it in a simulated intestine. In animal experiments, the bioavailability of RES@SPI-DG was 5.17 times higher than that of bare RES, and the biodistribution was also significantly improved. RES@SPI-DG demonstrated a strong hepatoprotective effect against overdose acetaminophen-induced liver injury. The SPI-DG complex might be a promising nano-platform for enhancing the bioavailability and efficacy of hydrophobic polyphenols such as RES.

Cystatin C is a predictor for long-term All-Cause and Cardiovascular Mortality in US Adults with Metabolic Syndrome.

OBJECTIVE: This study examined the relationship between Cystatin C (CysC) levels and all-cause, CVD, and cancer mortality in US metabolic syndrome (MetS) patients. METHODS: The 1999-2002 National Health and Nutrition Examination Survey (NHANES) prospective cohort research included 1,980 MetS participants. To assess CysC levels and all-cause, CVD, and cancer mortality, fitted curves, Kaplan-Meier survival curves, cox regression analysis, and ROC curves were performed. RESULTS: During a mean follow-up of 15.3 ± 5.4 years, a total of 819 deaths occurred. The fitted and Kaplan-Meier survival curves revealed that greater CysC levels were linked to higher all-cause, CVD, and cancer mortality rates (P<0.05). After adjusting for variables, CysC level was associated with all-cause, CVD, and cancer mortality at 1.63 (1.42-1.88), 1.53 (1.19-1.95), and 1.53 (1∼2.32), respectively (P<0.05). Later tertile models showed consistent results. High CysC tertile participants showed higher risk of all-cause mortality (HR 1.87; 1.43-2.45), CVD mortality (HR 1.97, 1.15∼3.38), and cancer mortality (HR 1.72, 1.01∼2.91) compared to those in the lowest tertile (P<0.05). Subgroup studies by sex and other characteristics confirmed the findings. CysC demonstrated the higher predictive efficacy across mortality outcomes, followed by eGFR, outperforming Urea nitrogen, Creatinine, Uric acid, and CRP. CysC alone exhibited substantial predictive value for all-cause (AUC 0.773; P<0.05) and CVD mortality (AUC 0.726; P<0.05). Combining CysC with age enhanced the predictive value for all-cause mortality to 0.861 and CVD mortality to 0.771 (P<0.05). CONCLUSION: MetS patients with elevated CysC levels have a higher risk of all-cause, CVD, and cancer death. CysC may predict MetS all-cause and CVD mortality.

Transoceanic ships as a source of alien dinoflagellate invasions of inland freshwater ecosystems.

Ships' ballast water and sediments have long been linked to the global transport and expansion of invasive species and thus have become a hot research topic and administrative challenge in the past decades. The relevant concerns, however, have been mainly about the ocean-to-ocean invasion and sampling practices have been almost exclusively conducted onboard. We examined and compared the dinoflagellate cysts assemblages in 49 sediment samples collected from ballast tanks of international and domestic routes ships, washing basins associated with a ship-repair yard, Jiangyin Port (PS), and the nearby area of Yangtze River (YR) during 2017-2018. A total of 43 dinoflagellates were fully identified to species level by metabarcoding, single-cyst PCR-based sequencing, cyst germination and phylogenetic analyses, including 12 species never reported from waters of China, 14 HABs-causing, 9 toxic, and 10 not strictly marine species. Our metabarcoding and single-cyst sequencing also detected many OTUs and cysts of dinoflagellates that could not be fully identified, indicating ballast tank sediments being a risky repository of currently unrecognizable invasive species. Particularly important, 10 brackish and fresh water species of dinoflagellate cysts (such as Tyrannodinium edax) were detected from the transoceanic ships, indicating these species may function as alien species potentially invading the inland rivers and adjacent lakes if these ships conduct deballast and other practices in fresh waterbodies. Significantly higher numbers of reads and OTUs of dinoflagellates in the ballast tanks and washing basins than that in PS and YR indicate a risk of releasing cysts by ships and the associated ship-repair yards to the surrounding waters. Phylogenetic analyses revealed high intra-species genetic diversity for multiple cyst species from different ballast tanks. Our work provides novel insights into the risk of bio-invasion to fresh waters conveyed in ship's ballast tank sediments and washing basins of shipyards.

Graph Signal Smoothness Based Feature Learning of Brain Functional Networks in Schizophrenia.

In this paper we study the brain functional network of schizophrenic patients based on resting-state fMRI data. Different from the region of interest (ROI)-level brain networks that describe the connectivity between brain regions, this paper constructs a subject-level brain functional network that describes the similarity between subjects from a graph signal processing (GSP) perspective. Based on the subject graph, we introduce the concept of graph signal smoothness to analyze the abnormal brain regions (feature brain regions) in which schizophrenic patients produce abnormal functional connections and to quantitatively rank the degree of abnormality of brain regions. We find that in the patients' brain networks, many new connections appear and some common connections are strengthened. The feature brain regions can be easily found according to the value of connection differences. Finally, we validate the learned feature brain regions by the results of two types of statistical analyses (ROI-to-ROI analysis and seed-to-voxel analysis), and the feature brain regions derived from graph signal smoothness are indeed the brain regions with significant differences in the statistical analysis, which illustrates the potential of graph signal smoothness for use in quantitative analysis of brain networks.

Brain Network Analysis of Schizophrenia Patients Based on Hypergraph Signal Processing.

Since high-order relationships among multiple brain regions-of-interests (ROIs) are helpful to explore the pathogenesis of neurological diseases more deeply, hypergraph-based brain networks are more suitable for brain science research. Unlike the existing hypergraph based brain network (brain hypernetwork), where hyperedges containing the same number of ROIs are assumed to have equal weights (to some extent, the network is unweighted), and the underlying structure is described only by an incidence/adjacency matrix, in this paper, we propose a framework for constructing a truly weighted brain hypernetwork described by an adjacency tensor. Considering the relationships among vertices within a hyperedge, we propose a novel hyperedge weight estimation method and convert the incidence matrix into a weighted adjacency tensor. On the basis of tensor decomposition, we apply hypergraph signal processing tools, such as hypergraph Fourier transform, to analyze and compare the spectrum between schizophrenia patients and normal controls. It is found that there are more high frequency components in the spectrum of patients than controls, and the average amplitude is significantly greater than that of controls. Instead of extracting some simple topological features from brain hypernetworks for classification, we innovatively use the hypergraph spectrum and the spectral signal as classification features, and the classification results on two public datasets demonstrate the effectiveness of our proposed method.

A study on the long-term effects and mechanisms of internet information behavior on poverty alleviation among smallholder farmers: Evidence from China.

China has historically accomplished the task of eradicating absolute poverty, however, as a result of multiple external constraints and a lack of their own endogenous motivation, there is a general lack of viability among farmers who have been lifted out of poverty, with some of those who have been lifted out of poverty at risk of returning to poverty and marginalized populations at risk of becoming poor, and there are certain challenges to the longevity and stability of the poverty eradication of smallholder farmers. In the era of rapid development of information technology, the use of Internet information has become an important way to change the information asymmetry in rural areas, narrow the urban-rural digital divide and reduce the vulnerability of poverty at present. Based on this, this paper puts forward the corresponding research hypotheses on the theoretical basis of how Internet information behavior affects the long-term effects of poverty alleviation of smallholder farmers, and this paper is based on the empirical analysis of the household survey data of 240 smallholder farmers in 3 cities and 3 counties of H Province, in an attempt to explore empirical testing of the impact of Internet information behavior on the long-term effects of poverty alleviation of smallholder farmers, and to further reveal the intrinsic mechanism of the role of the internal mechanism of the transformation between the smallholder farmers' Internet information behavior and poverty alleviation of the long-term effects of poverty alleviation. This study found that (1) Internet information usage would be positively related to the long-term poverty alleviation of smallholder farmers; (2) Among the mechanisms of Internet information usage on the long-term poverty alleviation of smallholder farmers, agricultural income opportunities, employment opportunities and entrepreneurial business opportunities have significant mediating effects; (3) Formal social support and informal social support, all play a significant positive moderating role in the process of transformation of development opportunities carried out by smallholder farmers. The findings of the study have important practical implications for accelerating the poverty alleviation effect of the Internet and achieving sustainable poverty alleviation among small farmers to promote common prosperity.

Multi-omics integration analysis unveils heterogeneity in breast cancer at the individual level.

Identifying robust breast cancer subtypes will help to reveal the cancer heterogeneity. However, previous breast cancer subtypes were based on population-level quantitative gene expression, which is affected by batch effects and cannot be applied to individuals. We detected differential gene expression, genomic, and epigenomic alterations to identify driver differential expression at the individual level. The individual driver differential expression reflected the breast cancer patients' heterogeneity and revealed four subtypes. Mesenchymal subtype as the most aggressive subtype harbored deletion and downregulated expression of genes in chromosome 11q23 region. Specifically, silencing of the SDHD gene in 11q23 promoted the invasion and migration of breast cancer cells in vitro by the epithelial-mesenchymal transition. The immunologically hot subtype displayed an immune-hot microenvironment, including high T-cell infiltration and upregulated PD-1 and CTLA4. Luminal and genomic-unstable subtypes showed opposite macrophage polarization, which may be regulated by the ligand-receptor pairs of CD99. The integration of multi-omics data at the individual level provides a powerful framework for elucidating the heterogeneity of breast cancer.

Discovery of Type II Interlayer Trions.

In terms of interlayer trions, electronic excitations in van der Waals heterostructures (vdWHs) can be classified into Type I (i.e., two identical charges in the same layer) and Type II (i.e., two identical charges in the different layers). Type I interlayer trions are investigated theoretically and experimentally. By contrast, Type II interlayer trions remain elusive in vdWHs, due to inadequate free charges, unsuitable band alignment, reduced Coulomb interactions, poor interface quality, etc. Here, the first observation of Type II interlayer trions is reported by exploring band alignments and choosing an atomically thin organic-inorganic system-monolayer WSe2 /bilayer pentacene heterostructure (1L + 2L HS). Both positive and negative Type II interlayer trions are electrically tuned and observed via PL spectroscopy. In particular, Type II interlayer trions exhibit in-plane anisotropic emission, possibly caused by their unique spatial structure and anisotropic charge interactions, which is highly correlated with the transition dipole moment of pentacene. The results pave the way to develop excitonic devices and all-optical circuits using atomically thin organic-inorganic bilayers.

Graph Signal Processing Approach to QSAR/QSPR Model Learning of Compounds.

Quantitative relationship between the activity/property and the structure of compound is critical in chemical applications. To learn this quantitative relationship, hundreds of molecular descriptors have been designed to describe the structure, mainly based on the properties of vertices and edges of molecular graph. However, many descriptors degenerate to the same values for different compounds with the same molecular graph, resulting in model failure. In this paper, we design a multidimensional signal for each vertex of the molecular graph to derive new descriptors with higher discriminability. We treat the new and traditional descriptors as the signals on the descriptor graph learned from the descriptor data, and enhance descriptor dissimilarity using the Laplacian filter derived from the descriptor graph. Combining these with model learning techniques, we propose a graph signal processing based approach to obtain reliable new models for learning the quantitative relationship and predicting the properties of compounds. We also provide insights from chemistry for the boiling point model. Several experiments are presented to demonstrate the validity, effectiveness and advantages of the proposed approach.