SCRN: Single-cell Gene Regulatory Network Identification in Alzheimer's Disease.

Alzheimer's disease (AD) is the most common neurodegenerative disease, and it consumes considerable medical resources with increasing number of patients every year. Mounting evidence show that the regulatory disruptions altering the intrinsic activity of genes in brain cells contribute to AD pathogenesis. To gain insights into the underlying gene regulation in AD, we proposed a graph learning method, Single-Cell based Regulatory Network (SCRN), to identify the regulatory mechanisms based on single-cell data. SCRN implements the γ-decaying heuristic link prediction based on graph neural networks and can identify reliable gene regulatory networks using locally closed subgraphs. In this work, we first performed UMAP dimension reduction analysis on single-cell RNA sequencing (scRNA-seq) data of AD and normal samples. Then we used SCRN to construct the gene regulatory network based on three well-recognized AD genes (APOE, CX3CR1, and P2RY12). Enrichment analysis of the regulatory network revealed significant pathways including NGF signaling, ERBB2 signaling, and hemostasis. These findings demonstrate the feasibility of using SCRN to uncover potential biomarkers and therapeutic targets related to AD.

PCCA variant rs16957301 is a novel AKI risk genotype-specific for patients who receive ICI treatment: Real-world evidence from All of Us cohort.

Background: Immune checkpoint inhibitors (ICIs) enhance the immune system's ability to target and destroy cancer cells by blocking inhibitory pathways. Despite their efficacy, these treatments can trigger immune-related adverse events (irAEs), such as acute kidney injury (ICI-AKI), complicating patient management. The genetic predispositions to ICI-AKI are not well understood, necessitating comprehensive genomic studies to identify risk factors and improve therapeutic strategies. Objective: To identify genetic predispositions for ICI-AKI using large-scale real-world data. Methods: A systematic literature search led to 14 candidate variants related to irAEs. We performed a candidate variant association study with these 14 variants using the All of Us cohort (AoU, v7, cutoff date: 7/1/2022). A cohort for cancer patients receiving ICI and a general cohort were established to evaluate ICI-AKI risk. Logistic regression, adjusted for sex, was used to evaluate the impact of each candidate genotype, separately for self-reported and ancestry-estimated race. Kaplan-Meier survival analysis assessed the genetic effects on AKI-free survival. Results: The ICI cohort (n=414) showed a one-year AKI incidence rate of 23.2%, significantly higher than the general cohort (6.5%, n=213,282). The rs16957301 variant (chr13:100324308, T>C) in the PCCA gene was a significant risk genotype for ICI-AKI among self-reported Caucasians (Beta=0.93, Bonferroni-corrected P-value=0.047) and ancestry estimated Caucasians (Beta = 0.94, Bonferroni-corrected P-value=0.044). Self-reported Caucasians with the rs16957301 risk genotypes (TC/CC) developed AKI significantly earlier (3.6 months) compared to the reference genotype (TT, 7.0 months, log-rank P=0.04). Consistent results were found in ancestry-estimated Caucasians. This variant did not present significant AKI risks in the general cohort (Beta: -0.008-0.035, FDR: 0.75-0.99). Conclusion: Real-world evidence from the All of Us cohort suggests that, in Caucasians, PCCA variant rs16957301 is a novel AKI risk genotype specific to ICI treatment. Additional studies are warranted to validate rs16957301 as risk marker for AKI in Caucasian patients treated with ICIs and to assess its risk in other ancestral populations.

Preparation and characterization of fennel (Foeniculum vulgare miller) essential oil/hydroxypropyl-ß-cyclodextrin inclusion complex and its application for chilled pork preservation.

Fennel essential oil (FEO) a natural spice that has versatile biological activities. However, the direct use of FEO is limited due to its water insolubility and poor stability. Chilled pork is prone to spoilage during storage. To solve these problems, this study aimed to prepare an inclusion complex (IC) of FEO with hydroxypropyl-ß-cyclodextrin via co-precipitation and apply it to the preservation of chilled pork. Results indicated that the optimal parameters were encapsulating temperature 37 °C, wall-core ratio 14:1 g/mL, stirring speed 600 r/min, and encapsulating time 240 min, obtaining an encapsulation efficiency of 83.75%. The results of scanning electron microscopy, Fourier transform infra-red spectroscopy, and nuclear magnetic resonance demonstrated the successful preparation of IC. The release of FEO from IC was controllable through adjusting the different temperatures and relative humidities. Furthermore, IC effectively delayed the spoilage of chilled pork and extended its shelf life by 6 days at 4 °C.

3D genomic mapping reveals multifocality of human pancreatic precancers.

Pancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study1. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution. To elucidate genetic relationships between and within PanINs, we developed a workflow in which 3D modelling guides multi-region microdissection and targeted and whole-exome sequencing. From these samples, we calculated a mean burden of 13 PanINs per cm3 and extrapolated that the normal intact adult pancreas harbours hundreds of PanINs, almost all with oncogenic KRAS hotspot mutations. We found that most PanINs originate as independent clones with distinct somatic mutation profiles. Some spatially continuous PanINs were found to contain multiple KRAS mutations; computational and in situ analyses demonstrated that different KRAS mutations localize to distinct cell subpopulations within these neoplasms, indicating their polyclonal origins. The extensive multifocality and genetic heterogeneity of PanINs raises important questions about mechanisms that drive precancer initiation and confer differential progression risk in the human pancreas. This detailed 3D genomic mapping of molecular alterations in human PanINs provides an empirical foundation for early detection and rational interception of pancreatic cancer.

xSiGra: Explainable model for single-cell spatial data elucidation.

Recent advancements in spatial imaging technologies have revolutionized the acquisition of high-resolution multi-channel images, gene expressions, and spatial locations at the single-cell level. Our study introduces xSiGra, an interpretable graph-based AI model, designed to elucidate interpretable features of identified spatial cell types, by harnessing multi-modal features from spatial imaging technologies. By constructing a spatial cellular graph with immunohistology images and gene expression as node attributes, xSiGra employs hybrid graph transformer models to delineate spatial cell types. Additionally, xSiGra integrates a novel variant of Grad-CAM component to uncover interpretable features, including pivotal genes and cells for various cell types, thereby facilitating deeper biological insights from spatial data. Through rigorous benchmarking against existing methods, xSiGra demonstrates superior performance across diverse spatial imaging datasets. Application of xSiGra on a lung tumor slice unveils the importance score of cells, illustrating that cellular activity is not solely determined by itself but also impacted by neighboring cells. Moreover, leveraging the identified interpretable genes, xSiGra reveals endothelial cell subset interacting with tumor cells, indicating its heterogeneous underlying mechanisms within the complex cellular communications.

Physiological and molecular bases of the nickel toxicity responses in tomato.

Nickel (Ni), a component of urease, is a micronutrient essential for plant growth and development, but excess Ni is toxic to plants. Tomato (Solanum lycopersicum L.) is one of the important vegetables worldwide. Excessive use of fertilizers and pesticides led to Ni contamination in agricultural soils, thus reducing yield and quality of tomatoes. However, the molecular regulatory mechanisms of Ni toxicity responses in tomato plants have largely not been elucidated. Here, we investigated the molecular mechanisms underlying the Ni toxicity response in tomato plants by physio-biochemical, transcriptomic and molecular regulatory network analyses. Ni toxicity repressed photosynthesis, induced the formation of brush-like lateral roots and interfered with micronutrient accumulation in tomato seedlings. Ni toxicity also induced reactive oxygen species accumulation and oxidative stress responses in plants. Furthermore, Ni toxicity reduced the phytohormone concentrations, including auxin, cytokinin and gibberellic acid, thereby retarding plant growth. Transcriptome analysis revealed that Ni toxicity altered the expression of genes involved in carbon/nitrogen metabolism pathways. Taken together, these results provide a theoretical basis for identifying key genes that could reduce excess Ni accumulation in tomato plants and are helpful for ensuring food safety and sustainable agricultural development.

Identification of a marine-derived sesquiterpenoid, Compound-8, that inhibits tumour necrosis factor-induced cell death by blocking complex II assembly.

BACKGROUND AND PURPOSE: Tumour necrosis factor (TNF) is a pleiotropic inflammatory cytokine that not only directly induces inflammatory gene expression but also triggers apoptotic and necroptotic cell death, which leads to tissue damage and indirectly exacerbates inflammation. Thus, identification of inhibitors for TNF-induced cell death has broad therapeutic relevance for TNF-related inflammatory diseases. In the present study, we isolated and identified a marine fungus-derived sesquiterpenoid, 9α,14-dihydroxy-6ß-p-nitrobenzoylcinnamolide (named as Cpd-8), that inhibits TNF receptor superfamily-induced cell death by preventing the formation of cytosolic death complex II. EXPERIMENTAL APPROACH: Marine sponge-associated fungi were cultured and the secondary metabolites were extracted to yield pure compounds. Cell viability was measured by ATP-Glo cell viability assay. The effects of Cpd-8 on TNF signalling pathway were investigated by western blotting, immunoprecipitation, and immunofluorescence assays. A mouse model of acute liver injury (ALI) was employed to explore the protection effect of Cpd-8, in vivo. KEY RESULTS: Cpd-8 selectively inhibits TNF receptor superfamily-induced apoptosis and necroptosis. Cpd-8 prevents the formation of cytosolic death complex II and subsequent RIPK1-RIPK3 necrosome, while it has no effect on TNF receptor I (TNFR1) internalization and the formation of complex I in TNF signalling pathway. In vivo, Cpd-8 protects mice against TNF-α/D-GalN-induced ALI. CONCLUSION AND IMPLICATIONS: A marine fungus-derived sesquiterpenoid, Cpd-8, inhibits TNF receptor superfamily-induced cell death, both in vitro and in vivo. This study not only provides a useful research tool to investigate the regulatory mechanisms of TNF-induced cell death but also identifies a promising lead compound for future drug development.

Harnessing the potential of long non-coding RNAs in breast cancer: from etiology to treatment resistance and clinical applications.

Breast cancer (BC) is the most common malignancy among women and a leading cause of cancer-related deaths of females worldwide. It is a complex and molecularly heterogeneous disease, with various subtypes that require different treatment strategies. Despite advances in high-resolution single-cell and multinomial technologies, distant metastasis and therapeutic resistance remain major challenges for BC treatment. Long non-coding RNAs (lncRNAs) are non-coding RNAs with more than 200 nucleotides in length. They act as competing endogenous RNAs (ceRNAs) to regulate post-transcriptional gene stability and modulate protein-protein, protein-DNA, and protein-RNA interactions to regulate various biological processes. Emerging evidence suggests that lncRNAs play essential roles in human cancers, including BC. In this review, we focus on the roles and mechanisms of lncRNAs in BC progression, metastasis, and treatment resistance, and discuss their potential value as therapeutic targets. Specifically, we summarize how lncRNAs are involved in the initiation and progression of BC, as well as their roles in metastasis and the development of therapeutic resistance. We also recapitulate the potential of lncRNAs as diagnostic biomarkers and discuss their potential use in personalized medicine. Finally, we provide lncRNA-based strategies to promote the prognosis of breast cancer patients in clinical settings, including the development of novel lncRNA-targeted therapies.

Oxygen-Activated Boron Nitride for Selective Photocatalytic Coupling of Methanol to Ethylene Glycol.

The controllable photocatalytic C-C coupling of methanol to produce ethylene glycol (EG) is a highly desirable but challenging objective for replacing the current energy-intensive thermocatalytic process. Here, we develop a metal-free porous boron nitride catalyst that demonstrates exceptional selectivity in the photocatalytic production of EG from methanol under mild conditions. Comprehensive experiments and calculations are conducted to thoroughly investigate the reaction mechanism, revealing that the OB3 unit in the porous BN plays a critical role in the preferential activation of C-H bond in methanol to form ⋅CH2OH via a concerted proton-electron transfer mechanism. More prominent energy barriers are observed for the further dehydrogenation of the ⋅CH2OH intermediate on the OB3 unit, inhibiting the formation of some other by-products during the catalytic process. Additionally, a small downhill energy barrier for the coupling of ⋅CH2OH in the OB3 unit promotes the selective generation of EG. This study provides valuable insights into the underlying mechanisms and can serve as a guide for the design and optimization of photocatalysts for efficient and selective EG production under mild conditions.

Discovery of WS-384, a first-in-class dual LSD1 and DCN1-UBC12 protein-protein interaction inhibitor for the treatment of non-small cell lung cancer.

Abnormally high expression of lysine-specific demethylase 1 A (LSD1) and DCN1 plays a vital role in the occurrence, development, and poor prognosis of non-small cell lung cancer (NSCLC). Accumulating evidence has shown that the development of small-molecule inhibitors dually targeting LSD1 and the DCN1-UBC12 interaction probably have therapeutic promise for cancer therapy. This work reported that WS-384 dually targeted LSD1 and DCN1-UBC12 interactions and evaluated its antitumor effects in vitro and in vivo. Specifically, WS-384 inhibited A549 and H1975 cells viability and decreased colony formation and EdU incorporation. WS-384 could also trigger cell cycle arrest, DNA damage, and apoptosis. Moreover, WS-384 significantly decreased tumor weight and volume in A549 xenograft mice. Mechanistically, WS-384 increased the gene and protein level of p21 by suppressing the neddylation of cullin 1 and decreasing H3K4 demethylation at the CDKN1A promoter. The synergetic upregulation of p21 contributed to cell cycle arrest and the proapoptotic effect of WS-384 in NSCLC cells. Taken together, our proof of concept studies demonstrated the therapeutic potential of dual inhibition of LSD1 and the DCN1-UBC12 interaction for the treatment of NSCLC. WS-384 could be used as a lead compound to develop new dual LSD1/DCN1 inhibitors for the treatment of human diseases in which LSD1 and DCN1 are dysregulated.

Proapoptotic effect of WS-299 induced by NOXA accumulation and NRF2-counterbalanced oxidative stress damage through targeting RBX1-UBE2M interaction in gastric cancers.

The abnormal activation of Cullin RING E3 Ligases (CRLs) is closely associated with the occurrence and development of various cancers. Targeting the neddylation pathway represents an effective approach for cancer treatment. In this work, we reported that WS-299, structurally featuring a coumarin moiety attached to the triazolopyrimidine, exhibited excellent anti-proliferative activity in MGC-803 and HGC-27 cells. WS-299 exerted potent anticancer effects by inhibiting clone formation, EdU incorporation and inducing cell cycle arrest. WS-299 inhibited CUL3/5 neddylation and caused an obvious accumulation of Nrf2 and NOXA, substrates of CRL3 and CRL5, respectively. Biochemical studies showed that WS-299 inhibited CUL3 neddylation by inhibiting RBX1-UBE2M interaction. The anti-proliferative effect of WS-299 was mainly induced by NOXA-mediated apoptosis. Of note, Nrf2 attenuated WS-299-induced reactive oxygen species (ROS) levels. Furthermore, Nrf2 accumulation also had an antagonistic effect on NOXA-induced apoptosis. Therefore, WS-299 and siNrf2 synergistically increased ROS levels, apoptotic cells and suppressed tumor growth in vivo. Taken together, our research clarified the anti-cancer mechanisms of WS-299 through targeting the RBX1-UBE2M protein-protein interaction and inhibiting the neddylation modification of CUL3 and CUL5. More importantly, our studies also demonstrated that combination of WS-299 with shNrf2 could be an effective strategy for treating gastric cancers.

A noninvasive multianalytical approach establishment for risk assessment and gastric cancer screening.

Effective screening and early detection are critical to improve the prognosis of gastric cancer (GC). Our study aims to explore noninvasive multianalytical biomarkers and construct integrative models for preliminary risk assessment and GC detection. Whole genomewide methylation marker discovery was conducted with CpG tandems target amplification (CTTA) in cfDNA from large asymptomatic screening participants in a high-risk area of GC. The methylation and mutation candidates were validated simultaneously using one plasma from patients at various gastric lesion stages by multiplex profiling with Mutation Capsule Plus (MCP). Helicobacter pylori specific antibodies were detected with a recomLine assay. Integrated models were constructed and validated by the combination of multianalytical biomarkers. A total of 146 and 120 novel methylation markers were found in CpG islands and promoter regions across the genome with CTTA. The methylation markers together with the candidate mutations were validated with MCP and used to establish a 133-methylation-marker panel for risk assessment of suspicious precancerous lesions and GC cases and a 49-methylation-marker panel as well as a 144-amplicon-mutation panel for GC detection. An integrated model comprising both methylation and specific antibody panels performed better for risk assessment than a traditional model (AUC, 0.83 and 0.63, P < .001). A second model for GC detection integrating methylation and mutation panels also outperformed the traditional model (AUC, 0.82 and 0.68, P = .005). Our study established methylation, mutation and H. pylori-specific antibody panels and constructed two integrated models for risk assessment and GC screening. Our findings provide new insights for a more precise GC screening strategy in the future.

DRMref: comprehensive reference map of drug resistance mechanisms in human cancer.

Drug resistance poses a significant challenge in cancer treatment. Despite the initial effectiveness of therapies such as chemotherapy, targeted therapy and immunotherapy, many patients eventually develop resistance. To gain deep insights into the underlying mechanisms, single-cell profiling has been performed to interrogate drug resistance at cell level. Herein, we have built the DRMref database (https://ccsm.uth.edu/DRMref/) to provide comprehensive characterization of drug resistance using single-cell data from drug treatment settings. The current version of DRMref includes 42 single-cell datasets from 30 studies, covering 382 samples, 13 major cancer types, 26 cancer subtypes, 35 treatment regimens and 42 drugs. All datasets in DRMref are browsable and searchable, with detailed annotations provided. Meanwhile, DRMref includes analyses of cellular composition, intratumoral heterogeneity, epithelial-mesenchymal transition, cell-cell interaction and differentially expressed genes in resistant cells. Notably, DRMref investigates the drug resistance mechanisms (e.g. Aberration of Drug's Therapeutic Target, Drug Inactivation by Structure Modification, etc.) in resistant cells. Additional enrichment analysis of hallmark/KEGG (Kyoto Encyclopedia of Genes and Genomes)/GO (Gene Ontology) pathways, as well as the identification of microRNA, motif and transcription factors involved in resistant cells, is provided in DRMref for user's exploration. Overall, DRMref serves as a unique single-cell-based resource for studying drug resistance, drug combination therapy and discovering novel drug targets.

Sample average treatment effect on the treated (SATT) analysis using counterfactual explanation identifies BMT and SARS-CoV-2 vaccination as protective risk factors associated with COVID-19 severity and survival in patients with multiple myeloma.

Patients with multiple myeloma (MM), an age-dependent neoplasm of antibody-producing plasma cells, have compromised immune systems and might be at increased risk for severe COVID-19 outcomes. This study characterizes risk factors associated with clinical indicators of COVID-19 severity and all-cause mortality in myeloma patients utilizing NCATS' National COVID Cohort Collaborative (N3C) database. The N3C consortium is a large, centralized data resource representing the largest multi-center cohort of COVID-19 cases and controls nationwide (>16 million total patients, and >6 million confirmed COVID-19+ cases to date). Our cohort included myeloma patients (both inpatients and outpatients) within the N3C consortium who have been diagnosed with COVID-19 based on positive PCR or antigen tests or ICD-10-CM diagnosis code. The outcomes of interest include all-cause mortality (including discharge to hospice) during the index encounter and clinical indicators of severity (i.e., hospitalization/emergency department/ED visit, use of mechanical ventilation, or extracorporeal membrane oxygenation (ECMO)). Finally, causal inference analysis was performed using the Coarsened Exact Matching (CEM) and Propensity Score Matching (PSM) methods. As of 05/16/2022, the N3C consortium included 1,061,748 cancer patients, out of which 26,064 were MM patients (8,588 were COVID-19 positive). The mean age at COVID-19 diagnosis was 65.89 years, 46.8% were females, and 20.2% were of black race. 4.47% of patients died within 30 days of COVID-19 hospitalization. Overall, the survival probability was 90.7% across the course of the study. Multivariate logistic regression analysis showed histories of pulmonary and renal disease, dexamethasone, proteasome inhibitor/PI, immunomodulatory/IMiD therapies, and severe Charlson Comorbidity Index/CCI were significantly associated with higher risks of severe COVID-19 outcomes. Protective associations were observed with blood-or-marrow transplant/BMT and COVID-19 vaccination. Further, multivariate Cox proportional hazard analysis showed that high and moderate CCI levels, International Staging System (ISS) moderate or severe stage, and PI therapy were associated with worse survival, while BMT and COVID-19 vaccination were associated with lower risk of death. Finally, matched sample average treatment effect on the treated (SATT) confirmed the causal effect of BMT and vaccination status as top protective factors associated with COVID-19 risk among US patients suffering from multiple myeloma. To the best of our knowledge, this is the largest nationwide study on myeloma patients with COVID-19.

Paenibacillus spongiae sp. nov. isolated from deep-water marine sponge Theonella swinhoei.

A novel bacterial strain, designated as PHS-Z3T, was isolated from a marine sponge belonging to the genus Theonella on the Puerto Galera Deep Monkey, Philippines. Cells of PHS-Z3T were Gram-stain-positive, motile, oxidase- and catalase-positive, white-pigmented, spore-forming, short rods that could grow at 10-40 °C (optimum, 20 °C), pH 6.0-9.5 (optimum, pH 7.5) and with 2-16 % (w/v) NaCl (optimum, 7 %). The 16S rRNA gene sequence of PHS-Z3T showed 97.9 %, 96.7 %, and 96.2 % identities to Paenibacillus mendelii C/2T, Paenibacillus oenotherae DT7-4T and Paenibacillus aurantiacus RC11T, respectively. The results of phylogenetic analysis based on 16S rRNA gene sequences indicated that PHS-Z3T formed an independent cluster with Paenibacillus mendelii C/2T. The total genome of PHS-Z3T was approximately 7 613 364 bp in size with a DNA G+C content of 51.6 %. The average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values between PHS-Z3T and other type strains of species of the genus Paenibacillus were 68.0-81.4 % [ANI by blast (ANIb)], 83.0-88.0 % [ANI by MUMmer (ANIm)] and 12.7-32.1 % (dDDH). The dDDH and ANI values were below the standard cut-off criteria for delineation of bacterial species. The percentage of conserved proteins (POCP) values between the genome of PHS-Z3T and those of members of the genus Paenibacillus were 39.7-75.7 %, while the average amino acid identity (AAI) values were 55.9-83.7 %. The sole respiratory quinone in the strain was MK-7, and the predominant fatty acids were anteiso-C15 : 0 and C16 : 0. The major polar lipids of PHS-Z3T consisted of diphosphatidylglycerol, phospholipid and phosphatidylglycerol. The characteristic amino acid in the cell wall of PHS-Z3T was diamino heptanoic acid (meso-DAP). On the basis of the molecular, physiological, biochemical and chemotaxonomic features, strain PHS-Z3T represents a novel species of the genus Paenibacillus, for which the name Paenibacillus spongiae sp. nov. is proposed, with the type strain PHS-Z3T (=MCCC 1K07848T=KCTC 43443T).

SpaRx: elucidate single-cell spatial heterogeneity of drug responses for personalized treatment.

Spatial cellular authors heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx, MERSCOPE and Xenium delineate the spatial gene expression patterns at the single cell resolution. This provides unprecedented opportunities to identify spatially localized cellular resistance and to optimize the treatment for individual patients. In this work, we present a graph-based domain adaptation model, SpaRx, to reveal the heterogeneity of spatial cellular response to drugs. SpaRx transfers the knowledge from pharmacogenomics profiles to single-cell spatial transcriptomics data, through hybrid learning with dynamic adversarial adaption. Comprehensive benchmarking demonstrates the superior and robust performance of SpaRx at different dropout rates, noise levels and transcriptomics coverage. Further application of SpaRx to the state-of-the-art single-cell spatial transcriptomics data reveals that tumor cells in different locations of a tumor lesion present heterogenous sensitivity or resistance to drugs. Moreover, resistant tumor cells interact with themselves or the surrounding constituents to form an ecosystem for drug resistance. Collectively, SpaRx characterizes the spatial therapeutic variability, unveils the molecular mechanisms underpinning drug resistance and identifies personalized drug targets and effective drug combinations.

[Relationship between promoting effect of Zuogui Pills on angiogenesis of reproductive organs and mobilization factors GM-CSF, SDF-1, and their receptors of EPCs in early-aging rats].

This study aimed to investigate the relationship between the promoting effect of Zuogui Pills on ovarian and vaginal angiogenesis in early-aging rats and mobilization factors granulocyte-macrophage colony-stimulating factor(GM-CSF), stromal cell-derived factor-1(SDF-1), and their receptors of endothelial progenitor cells(EPCs) and explore the mechanism of Zuogui Pills in improving reproductive hypofunction in early-aging rats. Ultra-high performance liquid chromatography-tandem mass spectrometry(UHPLC-MS/MS) was used to analyze the chemical components of the extract of Zuogui Pills. Forty 14-month-old female early-aging rats with estrous cycle disorder were randomly divided into a blank group, a conjugated estrogen group(conjugated estrogen suspension, 65 µg·kg~(-1)), and low-(11 g·kg~(-1)) and high-dose(33 g·kg~(-1)) Zuogui Pills groups, with 10 rats in each group. In addition, 10 4-month-old female rats were assigned to the youth control group. The rats in the blank group and the youth control group were treated with 20 g·kg~(-1) distilled water by gavage, while those in the groups with drug intervention were treated with corresponding drugs by gavage, once a day for 15 days. Enzyme-linked immunosorbent assay(ELISA) was used to detect the levels of SDF-1 and GM-CSF in the mobilization of EPCs in serum. Hematoxylin-eosin(HE) staining was used to observe the changes in the number of ovarian follicles at all levels and corpus luteum, the number of vaginal epithelial layers, the number of vaginal folds, and the blood vessels of ovarian and vaginal tissues in the groups with drug intervention. Western blot was used to detect the expression of ER, GM-CSFR, CXCR4, and CXCR7 proteins in ovarian and vaginal tissues. As revealed by the results, the blank group showed decreased number of corpus luteum, gro-wing follicles at all levels, and blood vessels(P<0.05), decreased thickness of vaginal mucosa, the number of epithelial layers, the number of vaginal folds, and the number of vessels in the lamina propria(P<0.05), reduced content of SDF-1 and GM-CSF in the peripheral blood(P<0.05), and down-regulated levels of ER, CXCR4, CXCR7, and GM-CSFR proteins in ovarian and vaginal tissues(P<0.05). The groups with drug intervention showed increased number of growing follicles at all levels, corpus luteum, and blood vessels(P<0.05), decreased number of atresia follicles(P<0.05), increased thickness of vaginal mucosa, the number of epithelial layers, the number of vaginal mucosal folds, and the number of blood vessels in the lamina propria(P<0.05), increased content of SDF-1 and GM-CSF in the peripheral blood(P<0.05), and up-regulated levels of ER, CXCR4, CXCR7, and GM-CSFR proteins in ovarian and vaginal tissues(P<0.05). This experiment suggests that Zuogui Pills may promote ovarian and vaginal angiogenesis and improve the reproductive function of early-aging rats by up-regulating the levels of mobilization factors SDF-1, GM-CSF, and their receptors of EPCs.

Detection of lineage-reprogramming efficiency of tumor cells in a 3D-printed liver-on-a-chip model.

Background: The liver metastasis accompanied with the loss of liver function is one of the most common complications in patients with triple-negative breast cancers (TNBC). Lineage reprogramming, as a technique direct inducing the functional cell types from one lineage to another lineage without passing through an intermediate pluripotent stage, is promising in changing cell fates and overcoming the limitations of primary cells. However, most reprogramming techniques are derived from human fibroblasts, and whether cancer cells can be reversed into hepatocytes remains elusive. Methods: Herein, we simplify preparation of reprogramming reagents by expressing six transcriptional factors (HNF4A, FOXA2, FOXA3, ATF5, PROX1, and HNF1) from two lentiviral vectors, each expressing three factors. Then the virus was transduced into MDA-MB-231 cells to generated human induced hepatocyte-like cells (hiHeps) and single-cell sequencing was used to analyze the fate for the cells after reprogramming. Furthermore, we constructed a Liver-on-a-chip (LOC) model by bioprinting the Gelatin Methacryloyl hydrogel loaded with hepatocyte extracellular vesicles (GelMA-EV) bioink onto the microfluidic chip to assess the metastasis behavior of the reprogrammed TNBC cells under the 3D liver microenvironment in vitro. Results: The combination of the genes HNF4A, FOXA2, FOXA3, ATF5, PROX1 and HNF1A could reprogram MDA-MB-231 tumor cells into human-induced hepatocytes (hiHeps), limiting metastasis of these cells. Single-cell sequencing analysis showed that the oncogenes were significantly inhibited while the liver-specific genes were activated after lineage reprogramming. Finally, the constructed LOC model showed that the hepatic phenotypes of the reprogrammed cells could be observed, and the metastasis of embedded cancer cells could be inhibited under the liver microenvironment. Conclusion: Our findings demonstrate that reprogramming could be a promising method to produce hepatocytes and treat TNBC liver metastasis. And the LOC model could intimate the 3D liver microenvironment and assess the behavior of the reprogrammed TNBC cells.

SpaRx: Elucidate single-cell spatial heterogeneity of drug responses for personalized treatment.

Spatial cellular heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx SMI, MERSCOPE, and Xenium delineate the spatial gene expression patterns at the single cell resolution. This provides unprecedented opportunities to identify spatially localized cellular resistance and to optimize the treatment for individual patients. In this work, we present a graph-based domain adaptation model, SpaRx, to reveal the heterogeneity of spatial cellular response to drugs. SpaRx transfers the knowledge from pharmacogenomics profiles to single-cell spatial transcriptomics data, through hybrid learning with dynamic adversarial adaption. Comprehensive benchmarking demonstrates the superior and robust performance of SpaRx at different dropout rates, noise levels, and transcriptomics coverage. Further application of SpaRx to the state-of-art single-cell spatial transcriptomics data reveals that tumor cells in different locations of a tumor lesion present heterogenous sensitivity or resistance to drugs. Moreover, resistant tumor cells interact with themselves or the surrounding constituents to form an ecosystem for drug resistance. Collectively, SpaRx characterizes the spatial therapeutic variability, unveils the molecular mechanisms underpinning drug resistance, and identifies personalized drug targets and effective drug combinations. Key Points: We have developed a novel graph-based domain adaption model named SpaRx, to reveal the heterogeneity of spatial cellular response to different types of drugs, which bridges the gap between pharmacogenomics knowledgebase and single-cell spatial transcriptomics data.SpaRx is developed tailored for single-cell spatial transcriptomics data and is provided available as a ready-to-use open-source software, which demonstrates high accuracy and robust performance.SpaRx uncovers that tumor cells located in different areas within tumor lesion exhibit varying levels of sensitivity or resistance to drugs. Moreover, SpaRx reveals that tumor cells interact with themselves and the surrounding microenvironment to form an ecosystem capable of drug resistance.