Tests for IgG and IgM antibodies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became available in February 2020. On March 4, 2020, the seventh edition of the New Coronavirus Pneumonia Prevention and Control Protocol for the novel coronavirus disease 2019 (COVID-19) was released by the National Health Commission of the People’s Republic of China and added serological diagnostic criteria.¹ A previous study of 9 pregnant women and their infants found no maternal-infant transmission of SARS-CoV-2 based on reverse transcriptase–polymerase chain reaction (RT-PCR).² We applied these new criteria to 6 pregnant women with confirmed COVID-19 and their infants because serologic criteria would allow more detailed investigation of infection in newborns.

Cervical Cancer is one of the leading causes of cancer‑associated mortality in women. The present study aimed to identify key genes and pathways involved in cervical cancer (CC) progression, via a comprehensive bioinformatics analysis. The GSE63514 dataset from the Gene Expression Omnibus database was analyzed for hub genes and cancer progression was divided into four phases (phases I‑IV). Pathway enrichment, protein‑protein interaction (PPI) and pathway crosstalk analyses were performed, to identify key genes and pathways using a criterion nodal degree ≥5. Gene pathway analysis was determined by mapping the key genes into the key pathways. Co‑expression between key genes and their effect on overall survival (OS) time was assessed using The Cancer Genome Atlas database. A total of 3,446 differentially expressed genes with 107 hub genes were identified within the four phases. A total of 14 key genes with 11 key pathways were obtained, following extraction of ≥5 degree nodes from the PPI and pathway crosstalk networks. Gene pathway analysis revealed that CDK1 and CCNB1 regulated the cell cycle and were activated in phase I. Notably, the following terms, ‘pathways in cancer’, ‘focal adhesion’ and the ‘PI3K‑Akt signaling pathway’ ranked the highest in phases II‑IV. Furthermore, FN1, ITGB1 and MMP9 may be associated with metastasis of tumor cells. STAT1 was indicated to predominantly function at the phase IV via cancer‑associated signaling pathways, including ‘pathways in cancer’ and ‘Toll‑like receptor signaling pathway’. Survival analysis revealed that high ITGB1 and FN1 expression levels resulted in significantly worse OS. CDK1 and CCNB1 were revealed to regulate proliferation and differentiation through the cell cycle and viral tumorigenesis, while FN1 and ITGB1, which may be developed as novel prognostic factors, were co‑expressed to induce metastasis via cancer‑associated signaling pathways, including PI3K‑Art signaling pathway, and focal adhesion in CC; however, the underlying molecular mechanisms require further research.

The histone modification level has been shown to be related with gene activation and repression in stress-responsive process, but there is little information on the relationship between histone modification and cell cycle gene expression responsive to environmental cues. In this study, the function of histone modifications in mediating the transcriptional regulation of cell cycle genes under various types of stress was investigated in maize (Zea mays L.). Abiotic stresses all inhibit the growth of maize seedlings, and induce total acetylation level increase compared with the control group in maize roots. The positive and negative regulation of the expression of some cell cycle genes leads to perturbation of cell cycle progression in response to abiotic stresses. Chromatin immunoprecipitation analysis reveals that dynamic histone acetylation change in the promoter region of cell cycle genes is involved in the control of gene expression in response to external stress and different cell cycle genes have their own characteristic patterns for histone acetylation. The data also showed that the combinations of hyperacetylation and hypoacetylation states of specific lysine sites on the H3 and H4 tails on the promoter regions of cell cycle genes regulate specific cell cycle gene expression under abiotic stress conditions, thus resulting in prolonged cell cycle duration and an inhibitory effect on growth and development in maize seedlings.

The extracellular matrix (ECM) plays critical roles in cytoskeletal support, biomechanical transduction and biochemical signal transformation. Tumor-associated macrophage (TAM) function is regulated by matrix stiffness in solid tumors and is often associated with poor prognosis. ECM stiffness-induced mechanical cues can activate cell membrane mechanoreceptors and corresponding mechanotransducers in the cytoplasm, modulating the phenotype of TAMs. Currently, tuning TAM polarization through matrix stiffness-induced mechanical stimulation has received increasing attention, whereas its effect on TAM fate has rarely been summarized. A better understanding of the relationship between matrix stiffness and macrophage function will contribute to the development of new strategies for cancer therapy. In this review, we first introduced the overall relationship between macrophage polarization and matrix stiffness, analyzed the changes in mechanoreceptors and mechanotransducers mediated by matrix stiffness on macrophage function and tumor progression, and finally summarized the effects of targeting ECM stiffness on tumor prognosis to provide insight into this new field.

The present study was performed with the aim of understanding the mechanisms of pathogenesis and providing novel biomarkers for cervical cancer by constructing a regulatory circular (circ)RNA‑micro (mi)RNA‑mRNA network. Using an adjusted P-value of 1, 16 and 156 miRNAs from GSE30656 and The Cancer Genome Atlas (TCGA), 5,321 mRNAs from GSE63514, 4,076 mRNAs from cervical squamous cell carcinoma and endocervical adenocarcinoma (from TCGA) and 75 circRNAs from GSE102686 were obtained. Using RNAhybrid, Venn and UpSetR plot, 12 circRNA‑miRNA pairs and 266 miRNA‑mRNA pairs were obtained. Once these pairs were combined, a circRNA‑miRNA‑mRNA network with 11 circRNA nodes, 4 miRNA nodes, 153 mRNA nodes and 203 edges was constructed. By constructing the protein‑protein interaction network using Molecular Complex Detection scores >5 and >5 nodes, 7 hubgenes (RRM2, CEP55, CHEK1, KIF23, RACGAP1, ATAD2 and KIF11) were identified. By mapping the 7 hubgenes into the preliminary circRNA‑miRNA‑mRNA network, a circRNA‑miRNA‑hubgenes network consisting of 5 circRNAs (hsa_circRNA_000596, hsa_circRNA_104315, hsa_circRNA_400068, hsa_circRNA_101958 and hsa_circRNA_103519), 2 mRNAs (hsa‑miR‑15b and hsa‑miR‑106b) and 7 mRNAs (RRM2, CEP55, CHEK1, KIF23, RACGAP1, ATAD2 and KIF11) was constructed. There were 22 circRNA‑miRNA‑mRNA regulatory axes identified in the subnetwork. By analyzing the overall survival for the 7 hubgenes using the Gene Expression Profiling Interactive Analysis tool, higher expression of RRM2 was demonstrated to be associated with a significantly poorer overall survival. PharmGkb analysis identified single nucleotide polymorphisms (SNPs) of rs5030743 and rs1130609 of RRM2, which can be treated with cladribine and cytarabine. RRM2 was also indicated to be involved in the gemcitabine pathway. The 5 circRNAs (hsa_circRNA_000596, hsa_circRNA_104315, hsa_circRNA_400068, hsa_circRNA_101958 and hsa_circRNA_103519) may function as competing endogenous RNAs and serve critical roles in cervical cancer. In addition, cytarabine may produce similar effects to gemcitabine and may be an optional chemotherapeutic drug for treating cervical cancer by targeting rs5030743 and rs1130609 or other similar SNPs. However, the specific mechanism of action should be confirmed by further study.

Tumour cell senescence can be induced by various factors, including DNA damage, inflammatory signals, genetic toxins, ionising radiation and nutrient metabolism. The senescence‐associated secretory phenotype (SASP), secreted by senescent tumour cells, possesses the capacity to modulate various immune cells, including macrophages, T cells, natural killer cells and myeloid‐derived suppressor cells, as well as vascular endothelial cells and fibroblasts within the tumour microenvironment (TME), and this modulation can result in either the promotion or suppression of tumorigenesis and progression. Exploring the impact of SASP on the TME could identify potential therapeutic targets, yet limited studies have dissected its functions. In this review, we delve into the causes and mechanisms of tumour cell senescence. We then concentrate on the influence of SASP on the tumour immune microenvironment, angiogenesis, extracellular matrix and the reprogramming of cancer stem cells, along with their associated tumour outcomes. Last, we present a comprehensive overview of the diverse array of senotherapeutics, highlighting their prospective advantages and challenge for the treatment of cancer patients.Key points: Senescence‐associated secretory phenotype (SASP) secretion from senescent tumour cells significantly impacts cancer progression and biology. SASP is involved in regulating the remodelling of the tumour microenvironment, including immune microenvironment, vascular, extracellular matrix and cancer stem cells. Senotherapeutics, such as senolytic, senomorphic, nanotherapy and senolytic vaccines, hold promise for enhancing cancer treatment efficacy.