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Abstract The incidence of multiple pronuclei (≥ 3PN) zygotes and blastomere multinucleation was found to be elevated in the presence of increased estradiol (E2) levels and a greater number of retrieved oocytes. This implies a potential link between the incidence of multinucleation at the two-cell stage (MN2) and a higher proportion of ≥ 3PN zygotes. We aimed to investigate the effect of high proportion of ≥ 3PN zygotes on MN2 incidence during conventional in vitro fertilization (C-IVF) by using time-lapse monitoring. This study included 1195 patients from January 2020 to December 2022. The patients were categorized into three groups: Group 1 comprised patients with no ≥ 3PN zygotes (n = 422), Group 2 included those with 0–25% ≥3PN zygotes (n = 617), and Group 3 consisted of patients with more than 25% ≥3PN zygotes (n = 156). The MN2 rate, types of MN2 and clinical outcomes were compared among the three groups. Our data indicated that the MN2 rate was significantly lower in groups 1 and 2 compared to group 3 (18.33 versus 25.62%; p 0.05). The embryos displaying binucleated at the two-cell stage in one blastomere (2BI1) and true multinucleated at the two-cell stage in one blastomere (2MULTI1) showed significantly higher blastocyst formation rates compared to embryos exhibiting true multinucleated at the two-cell stage in both blastomeres (2MULTI2) (59.50 versus 45.40%; p

Abstract Esophageal squamous cell carcinoma (ESCC) is highly heterogeneous. Our understanding of full molecular and immune landscape of ESCC remains limited, hindering the development of personalised therapeutic strategies. To address this, we perform genomic-transcriptomic characterizations and AI-aided histopathological image analysis of 120 Chinese ESCC patients. Here we show that ESCC can be categorized into differentiated, metabolic, immunogenic and stemness subtypes based on bulk and single-cell RNA-seq, each exhibiting specific molecular and histopathological features based on an amalgamated deep-learning model. The stemness subgroup with signature genes, such as WFDC2, SFRP1, LGR6 and VWA2, has the poorest prognosis and is associated with downregulated immune activities, a high frequency of EP300 mutation/activation, functional mutation enrichment in Wnt signalling and the highest level of intratumoural heterogeneity. The immune profiling by transcriptomics and immunohistochemistry reveals ESCC cells overexpress natural killer cell markers XCL1 and CD160 as immune evasion. Strikingly, XCL1 expression also affects the sensitivity of ESCC cells to common chemotherapy drugs. This study opens avenues for ESCC treatment and provides a valuable public resource to better understand ESCC.

Abstract Background Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder that has been found to be associated with dysregulation of gastrointestinal functions and gut microbial homeostasis (the so-called “gut-brain axis”). ASD is often accompanied by poor performances in social interaction and repetitive behaviors. Studies on the gut-brain axis provide novel insights and candidate targets for ASD therapeutics and diagnosis. Based on the ASD mice model, this work aims to reveal the mechanisms behind the interaction of intestinal barrier function and probiotics in ASD mouse models. Results We found an altered intestinal barrier in both BTBR T+ Itpr3tf/J (BTBR) and valproic acid (VPA) mice, including increased intestinal permeability, decreased expression of intestinal tight junction proteins (claudin1, claudin3, and occludin), and increased levels of IL-6, TNF-α, and IFN-γ. Based on intestinal microbial alternation, C. butyricum can drive reduced expression of histone deacetylases 1 (HDAC1) and enhanced intestinal barrier function, significantly promoting behavioral abnormalities of ASD in BTBR mice. In parallel, we confirmed that C. butyricum was involved in the regulation of intestinal function by the Trek1 channel, indicating that it is a target of C. butyricum/butyric acid to improve intestinal barrier function in ASD mice. Conclusions Our finding provides solid evidence for the gut microbiota involved in ASD through the brain-gut axis. In addition, the probiotics C. butyricum hold promise to improve gut health and ameliorate behavioral abnormalities associated with ASD.

Abstract Background Gastric intestinal metaplasia (GIM) is an essential precancerous lesion. Although the reversal of GIM is challenging, it potentially brings a state-to-art strategy for gastric cancer therapeutics (GC). The lack of the appropriate in vitro model limits studies of GIM pathogenesis, which is the issue this work aims to address for further studies. Method The air-liquid interface (ALI) model was adopted for the long-term culture of GIM cells in the present work. This study conducted Immunofluorescence (IF), quantitative real-time polymerase chain reaction (qRT-PCR), transcriptomic sequencing, and mucoproteomic sequencing (MS) techniques to identify the pathways for differential expressed genes (DEGs) enrichment among different groups, furthermore, to verify novel biomarkers of GIM cells. Result Our study suggests that GIM-ALI model is analog to the innate GIM cells, which thus can be used for mucus collection and drug screening. We found genes MUC17, CDA, TRIM15, TBX3, FLVCR2, ONECUT2, ACY3, NMUR2, and MAL2 were highly expressed in GIM cells, while GLDN, SLC5A5, MAL, and MALAT1 showed down-regulated, which can be used as potential biomarkers for GIM cells. In parallel, these genes that highly expressed in GIM samples were mainly involved in cancer-related pathways, such as the MAPK signal pathway and oxidative phosphorylation signal pathway. Conclusion The ALI model is validated for the first time for the in vitro study of GIM. GIM-ALI model is a novel in vitro model that can mimic the tissue micro-environment in GIM patients and further provide an avenue for studying the characteristics of GIM mucus. Our study identified new markers of GIM as well as pathways associated with GIM, which provides outstanding insight for exploring GIM pathogenesis and potentially other related conditions.

ABSTRACT Esophageal cancer (EC) is a multifaceted disease. Our understanding of the involvement of esophageal microbiota in its pathogenesis and progression is limited, which is due to the lack of proper endoscopic sampling methods. Hereby, we conducted a comparative analysis of paired samples obtained through endoscopic brushing and cytosponge, aiming at assessing the feasibility of using cytosponge as a minimally invasive sampling way for studying esophageal microbiota. Our findings suggest that cytosponge sampling yielded significantly superior community richness and diversity compared to endoscopic brushing in both controls (non-cancerous) and EC individuals. The analysis of beta-diversity revealed distinct microbial community pattern in the genus diversity between the two sampling methods, underscoring the importance of selecting appropriate sampling methods to effectively characterize the esophageal microbiota. Specifically, Lactococcus and Serratia showed higher abundance in the samples collected by endoscopic brushing, while Alloprevotella and Leptotrichia were more enriched in the samples collected by cytosponge. These differences in dominant microbes were associated with metabolic pathways that particularly were related to host inflammation, such as pyruvate and glucose metabolisms. Notably, the phylogenetic levels of the microbiota indicated varied explanatory power for different detection purposes. This study underscores the substantial impact of sampling method selection on the acquisition of esophageal microbiota associated with the EC development, encompassing considerations of both abundance and diversity. This highlights the significance of selecting an appropriate sampling method for investigating the esophageal microbial status and studying the micro-environment in EC-related individuals.IMPORTANCEThis study addresses a critical issue in esophageal cancer study by comparing two different sampling methods, endoscopic brushing and cytosponge, for investigating the esophageal microbiota. Our work highlights the suitability of the cytosponge technique as a minimally invasive sampling method for studying the esophageal microbiota and emphasizes the importance of selecting an appropriate sampling method to characterize the microbial community. Our findings have significant implications for advancing the understanding of the role of the esophageal microbiota in cancer development and will inform future research and clinical approaches in this field.

ABSTRACT Physicochemical methods for remediating phenol-contaminated soils are costly and inefficient, making biodegradation an environmentally friendly alternative approach. This study aims to screen for potential phenol-degrading bacteria and to verify the removal capacities of a selected strain in a bioaugmentation experiment at the greenhouse level using Brassica chinensis L. (Chinese cabbage) as the model plant and phenol-contaminated soil. In parallel, pot experiments were conducted using a collaborative approach based on this model system. We found that Myroides xuanwuensis strain H13 showed a high degradation capability, with a 97.67% efficiency in degrading 100 mg/L phenol. Under shaking flask conditions, H13 facilitated the solubilization of tricalcium phosphate and potassium feldspar powder. Pot experiments suggested a phenol removal percentage of 89.22% and enhanced availability of soil phosphorus and potassium for plants with H13 inoculation. In this case, the abundance of soil microbes and the activity of soil enzymes significantly increased as well. Furthermore, both photosynthesis and the antioxidant system in Chinese cabbage were enhanced following H13 inoculation, resulting in its increased yield and quality. Partial least squares path modeling revealed that H13 can primarily affect plant root growth, with a secondary impact on photosynthesis. These findings highlight the potential of biodegradation from phenol-degrading bacteria as a promising strategy for efficient phenol removal from soil while promoting plant growth and health.IMPORTANCEThis study is significant for environmental remediation and agriculture by its exploration of a more environmentally friendly and cost-effective bio-strategy in treating phenol-contaminated soil. These findings have essential implications for environmental remediation efforts and sustainable agriculture. By utilizing the biodegradation capabilities of Myroides xuanwuensis strain H13, it is possible to remove phenol contaminants from the soil efficiently, reducing their negative effects. Furthermore, the enhanced growth and health of the Chinese cabbage plants indicate the potential of this approach to promote sustainable crop production.

ObjectiveGastric intestinal metaplasia (IM) is a precancerous stage associated with gastric cancer. Despite the observed beneficial effects of metformin on IM, its molecular mechanism remains not fully elucidated. This study aims to reveal the effects and potential mechanisms of metformin in treating IM based on both bioinformatics and in vivo investigations.MethodsThe seven public databases (GeneCards, DisGeNET, OMIM, SuperPred, Pharm Mapper, Swiss Target Prediction, TargetNet) were used in this work to identify targeted genes related to intestinal metaplasia (IM) and metformin. The shared targeted genes between metformin and IM were further analyzed by network pharmacology, while the interactions in-between were investigated by molecular docking. In parallel, the therapeutic effect of metformin was evaluated in IM mice model, while the core targets and pathways effected by metformin were verified in vivo.ResultsWe screened out 1,751 IM-related genes and 318 metformin-targeted genes, 99 common genes identified in between were visualized by constructing the protein-protein interaction (PPI) network. The top ten core targeted genes were EGFR, MMP9, HIF1A, HSP90AA1, SIRT1, IL2, MAPK8, STAT1, PIK3CA, and ICAM1. The functional enrichment analysis confirmed that carcinogenesis and HIF-1 signaling pathways were primarily involved in the metformin treatment of IM. Based on molecular docking and dynamics, we found metformin affected the function of its targets by inhibiting receptor binding. Furthermore, metformin administration reduced the progression of IM lesions in Atp4a−/− mice model significantly. Notably, metformin enhanced the expression level of MUC5AC, while inhibited the expression level of CDX2. Our results also showed that metformin modulated the expression of core targets in vivo by reducing the activity of NF-κB and the PI3K/AKT/mTOR/HIF-1α signaling pathway.ConclusionThis study confirms that metformin improves the efficacy of IM treatment by regulating a complex molecular network. Metformin plays a functional role in inhibiting inflammation/apoptosis-related pathways of further IM progression. Our work provides a molecular foundation for understanding metformin and other guanidine medicines in IM treatment.

Background: Revealing the role of anoikis resistance plays in CRC is significant for CRC diagnosis and treatment. This study integrated the CRC anoikis-related key genes (CRC-AKGs) and established a novel model for improving the efficiency and accuracy of the prognostic evaluation of CRC. Methods: CRC-ARGs were screened out by performing differential expression and univariate Cox analysis. CRC-AKGs were obtained through the LASSO machine learning algorithm and the LASSO Risk-Score was constructed to build a nomogram clinical prediction model combined with the clinical predictors. In parallel, this work developed a web-based dynamic nomogram to facilitate the generalization and practical application of our model. Results: We identified 10 CRC-AKGs and a risk-related prognostic Risk-Score was calculated. Multivariate COX regression analysis indicated that the Risk-Score, TNM stage, and age were independent risk factors that significantly associated with the CRC prognosis(p

Background: Gastrointestinal cancer poses a considerable global health risk, encompassing a heterogeneous spectrum of malignancies that afflict the gastrointestinal tract. It is significant to develop efficacious therapeutic agents, as they are indispensable for both the treatment and prevention of this formidable disease. Methods: In this study, we synthesized a novel thiophene derivative, designated as compound 1312. An assessment was performed to investigate its anti-proliferative activity in several cancer cell lines (GES-1, EC9706, SGC7901, and HT-29). Furthermore, we performed molecular biology techniques to investigate the inhibitory impact of compound 1312 on gastrointestinal cell lines SGC-7901 and HT-29. Results: Our findings reveal that compound 1312 exhibits significant efficacy in suppressing colony formation of cancer cells. Notably, it triggers cell cycle arrest at the G2/M phase in gastrointestinal cell lines SGC7901 and HT-29. Compound 1312 was confirmed to exert inhibitory effects on cell migration and invasion in SGC7901. Additionally, the compound elicits apoptotic cell death through the activation of the DNA repair enzyme poly (ADP-ribose) polymerase (PARP) and the caspase signaling cascade. Furthermore, in vitro experiments revealed that compound 1312 effectively suppresses both the β-tubulin cytoskeletal network and the Wnt/β-catenin signaling pathway. These multifaceted anti-cancer activities highlight the potential of compound 1312 as a promising therapeutic agent for the treatment of gastrointestinal malignancies. Conclusion: This study indicates the promising potential of compound 1312 as a prospective candidate agent for gastrointestinal cancer treatment. Further comprehensive investigations are needed to explore its therapeutic efficacy in greater detail.

Esophageal cancer (EC) is an aggressive malignancy with a poor prognosis. Various factors, including dietary habits, and antacid and antibiotic use, have been shown to influence the esophageal microbiome. Conversely, enrichment and diversity of the esophageal microbiome can also impact its function. Recent studies have revealed prevalent changes in the esophageal microbiome among patients with EC, thus suggesting the potential contribution of the esophageal microbiome to EC development. Additionally, distinct microbiome compositions have been observed in patients with different responses to radiotherapy and chemotherapy, indicating the role of the esophageal microbiome in modulating treatment outcomes. In this review, we have examined previous studies on the esophageal microbiome in healthy individuals and patients with EC or other esophageal diseases, with a focus on identifying microbial communities associated with EC pathogenesis and prognosis. Understanding the role of the microbiome in EC may aid in early detection and optimized treatment strategies, ultimately leading to better outcomes for patients.

Sitobion avenae F. is a highly prevalent and devastating pest in wheat crops, leading to significant yield losses. Silicon (Si) has been widely recognized as an effective inducer of plant resistance against aphids. Nevertheless, the underlying mechanisms governing the physiological and biochemical responses of plants induced by Si defense against S. avenae F. remain incompletely understood. In this study, we conducted experiments by treating wheat leaves with varying concentrations of Tetraethyl orthosilicate (TEOS) spray under aphid infestation. We meticulously observed and recorded the life cycle of S. avenae F. and measured the content of plant hormones, secondary metabolites, and the activity of defense enzymes in wheat leaves. Furthermore, we utilized structural equation modeling to discern the causal correlation between aphid performance and the physiological-biochemical responses of wheat under TEOS sprays. Our findings revealed that a concentration of 3 mmol/L TEOS significantly shortened the net reproductive rate, intrinsic rate and finite rate of increase, and mean generation time of S. avenae F., while simultaneously prolonging the population doubling time. Additionally, the content of lignin, total phenolics, flavonoids, alkaloids, tannin, jasmonic acid (JA), and salicylic acid in wheat leaves exhibited a substantial increase. Furthermore, the activity of phenylalanine ammonia-lyase (PAL), polyphenol oxidase (PPO), catalase, and lipoxygenase in wheat leaves was significantly enhanced. Our results suggest that TEOS spray reduced the survival and population growth of S. avenae F. while enhancing the defense response of wheat against aphids by activating the activity of PAL and PPO in wheat, and increasing the content of total phenolic and JA. This work provides valuable insights for the development of appropriate Si fertilizers for effective pest management and offers robust theoretical support for wheat aphid control through agricultural fertilization strategies.

The development of cancer is not just the growth and proliferation of a single transformed cell, but its tumor microenvironment (TME) also coevolves with it, which is primarily involved in tumor initiation, development, metastasis, and therapeutic responses. Recent years, TME has been emerged as a potential target for cancer diagnosis and treatment. However, the clinical efficacy of treatments targeting the TME, especially its specific components, remains insufficient. In parallel, the gut microbiome is an essential TME component that is crucial in cancer immunotherapy. Thus, assessing and constructing frameworks between the gut microbiota and the TME can significantly enhance the exploration of effective treatment strategies for various tumors. In this review the role of the gut microbiota in human cancers, including its function and relationship with various tumors was summarized. In addition, the interaction between the gut microbiota and the TME as well as its potential applications in cancer therapeutics was described. Furthermore, it was summarized that fecal microbiota transplantation, dietary adjustments, and synthetic biology to introduce gut microbiota-based medical technologies for cancer treatment. This review provides a comprehensive summary for uncovering the mechanism underlying the effects of the gut microbiota on the TME and lays a foundation for the development of personalized medicine in further studies.

Background: Twin pregnancies carry significant fetal, perinatal and maternal risks. Thus, it is important to evaluate clinical outcomes of in vitro fertilization with donor sperm (IVFD) in the first attempt with double cleavage-stage embryos and explore optimal number of day 3 high-quality embryos for the blastocyst transfer on day 5. Methods: We retrospectively identified all IVFD embryo transfers (IVFD-ETs) for the initial time between 2014 and 2021 at our hospital. We mainly analyzed the twin pregnancy rates for double day 3 embryo transfers and clinical outcomes of day 5 blastocyst transfers by prolonged culture with different numbers of day 3 high-quality embryos. Results: Among 1512 IVFD-ETs, 834 were day 3 embryo transfers and 678 were day 5 blastocyst transfers. Our data indicated that the twin pregnancy rates reached up to 40% in the 674 double cleavage-stage embryo transfers and it was not due to the quality of the transferred embryos. For prolonged culture with 2, 3 and 4 day 3 high-quality embryos, the cycle rates of no high-quality blastocysts obtained were 30.43%, 19.80% and 7.91%, respectively. The clinical pregnancy rates were 56.52%, 74.26% and 72.32%, respectively. The twin pregnancies rates were 7.69%, 14.67% and 6.77%, respectively. Conclusions: Transferring double cleavage-stage embryos had high risks of twin pregnancies in the IVFD-ETs. Blastocyst transfer was safe and recommended for the patients with three or more high-quality embryos on day 3.

High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged a few reviews. However, current reviews of MOOC dropout prediction exist some common limitations. Firstly, different definitions of course dropout are not summarized. Secondly, there lacks an overall framework of MOOC dropout prediction. Thirdly, some key challenges are not fully explored. Thus, unlike past reviews, this systematic review concludes with three categories of definitions of course dropout. Then it proposes an overall framework including factors affecting dropout, general feature extraction methods, various machine learning methods and evaluation methods. Finally, the key challenges of interpretability, imbalanced data and semantic learning trajectory modeling are proposed. This study aims to enable researchers to capture a whole picture of dropout prediction from the perspective of machine learning.