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This study highlights distinct gut microbiome and metabolomic changes in dust-exposed workers, suggesting potential early biomarkers for silicosis risk. Understanding these alterations could inform preventive strategies and early detection, improving occupational health and reducing silicosis progression. Objectives: This study aimed to identify distinct gut microbiome and serum metabolic features in workers exposed to dust compared to healthy controls. Methods: A case-control study was conducted with dust-exposed workers without silicosis and age-matched healthy controls. Gut microbiome composition was analyzed using 16S rRNA sequencing, and serum and fecal metabolomic profiles were assessed by LC-MS. Results: Dust-exposed workers showed higher levels of Blautia and Trichoderma and lower levels of Anaplasma , Aspergillus , Plasmodiophoromycetes, and Escherichia coli-Shigella. Metabolites such as indole-3-acetate and gentamicin C1a were downregulated, while adenine, 2-phenylacetamide, and 4-pyridoxic acid were upregulated. Conclusions: Blautia spp. were linked to altered metabolites in dust-exposed workers, suggesting microbiome-metabolite interactions that may affect silicosis progression. However, the small sample size and cross-sectional design limit generalizability, and further longitudinal studies are needed. [ABSTRACT FROM AUTHOR]

Watercress (Nasturtium officinale R.Br.) is a cruciferous aquatic vegetable that possesses significant nutritional value. The NAC family is a transcription factor family specific to plants that play an important role in regulating plant responses to abiotic stress. In order to investigate the response of NAC genes to flooding stress in watercress, we conducted a study on the NoNAC family. In this study, a total of 119 NoNAC genes were obtained through genome-wide identification. Phylogenetic analysis indicated that the NoNAC family members can be categorized into ten subgroups. The results of gene structure analysis revealed that each branch within the subgroups exhibited similar motif composition and gene structure. The heatmap analysis showed that several NoNAC genes demonstrated tissue-specific expression patterns, suggesting their potential as regulators of associated tissue development. As an aquatic plant, watercress serves as a valuable material for investigating plant resistance to flooding stress. This study found that flooding can significantly increase the watercress plant height, which is a typical escape strategy under flooding. The analysis of the expression of NoNAC genes in the stem transcriptome after flooding indicated that only NoNAC36a consistently exhibited significant differential changes and down-regulated expression at the three time points of flooding treatment. This suggests that NoNAC36a may be involved in regulating watercress plant height increases under flooding stress. The utilization of a virus-induced gene silencing assay to investigate the biological function of NoNAC36a revealed that NoNAC36a silencing caused cell elongation and expansion, thus increasing watercress plant height. The yeast one-hybrid and dual luciferase assays demonstrated that NoNAC36a binds the promoter of NoXTH33 and inhibits its expression. Subsequently, the results of yeast two-hybrid, luciferase complementary, and pull-down assays revealed the interaction between NoMOB1A and NoNAC36a in vivo and in vitro. Sequence alignment indicated that NoMOB1A and AtMOB1A share an identical amino acid sequence. RT-qPCR analysis indicated that flooding prompted the expression of NoMOB1A in stems. Thus, it is speculated that NoMOB1A may exhibit functions similar to AtMOB1A and that the up-regulation of NoMOB1A expression in stems may facilitate an increase in plant height under flooding. In summary, the NoNAC family was analyzed, and revealed a regulatory network centered on NoNAC36a that facilitates watercress resistance to flooding stress. This study enhanced the understanding of the NoNAC genes and established a theoretical foundation for investigating plant flooding tolerance. [ABSTRACT FROM AUTHOR]

Purpose: This retrospective study aims to compare the effectiveness and safety of four oral antiviral drugs including Simnotrelvir/Ritonavir, Nirmatrelvir/Ritonavir, Azvudine and Molnupiravir in hospitalized patients with Coronavirus Disease 2019 (COVID-19) in a real-world setting, providing evidence to guide clinical practice against COVID-19. Patients and Methods: Patients with mild or moderate COVID-19 hospitalized at Wuxi City's Second People's Hospital during December 2022 to June 2023 were included in this study. Patients were grouped by the antiviral drug received. The primary endpoint was the length of hospital stay. Patients were further divided into subgroups for stratified analysis, considering age, timing of medication, and drug mechanisms, to explore whether these factors could influence the treatment efficacy. Results: Of the enrolled 195 patients receiving any treatment, 42 received Nirmatrelvir/Ritonavir, 33 received Molnupiravir, 81 received Simnotrelvir/Ritonavir, and 39 received Azvudine. Patients in Nirmatrelvir/Ritonavir and Simnotrelvir/Ritonavir groups had significantly shorter hospital stays compared to those in Azvudine group (P < 0.05). No significant difference was observed in hospital stays between those initiating antiviral therapy within or more than five days after symptom onset (P = 0.1109). Among patients with comorbidities, the Nirmatrelvir/Ritonavir and Simnotrelvir/Ritonavir group showed shorter hospital stays than the Azvudine group (P < 0.05). No serious treatment-related adverse events were observed across the groups. Conclusion: In this retrospective study, Nirmatrelvir/Ritonavir and Simnotrelvir/Ritonavir exerts stronger potency on reducing duration of hospital stays in hospitalized patient with COVID-19, suggestive of a better choice for antiviral therapy. Patients who fail to take antiviral drugs in time after symptom onset would still benefit from these antiviral regimens. Additional well-designed clinical trials with large sample size are still needed to further confirm the effectiveness of these antivirals. [ABSTRACT FROM AUTHOR]

To evaluate the expression of PD-L1 (programmed death 1 ligand 1, PD-L1) and its clinical significance in breast invasive ductal carcinoma.

Our study aims to investigate the efficacy and clinical significance of the Zuogui pill (ZGP) on premature ovarian failure (POF) via the GDF-9/Smad2 pathway. Changes in clinical symptoms in the control group (treated with Femoston alone) and the treatment group (treated with ZGP combined with Femoston) were assessed before and after treatment. Sex hormone levels, serum inflammatory cytokine levels, and ultrasound parameters were measured before and after treatment. POF rat models were established using cyclophosphamide and the POF rats were treated with Femoston, or ZGP combined with Femoston. GDF-9 and Smad2 expression levels were determined by RT-qPCR. The follicle-stimulating hormone (FSH), luteinizing hormone (LH), interleukin (IL)-6, and IL-21 levels, and the pulsatility index (PI) and resistance index (RI) values were decreased, while the estradiol (E2) and anti-Mullerian hormone (AMH) levels, antral follicle count (AFC), ovarian volume (OV), mean ovarian diameter (MOD), and peak systolic velocity (PSV) values were increased in the treatment group compared to the control group. After treatment with ZGP combined with Femoston, GDF-9 and Smad2 expression in the ovarian tissues of POF rats increased. ZGP has a therapeutic effect on POF via modulation of the GDF-9/Smad2 pathway. [ABSTRACT FROM AUTHOR]

Dysregulated lipid metabolism promotes the progression of various cancer types, including breast cancer. The present study aimed to explore the lipidomic profiles of patients with breast cancer, providing insights into the correlation between lipid compositions and tumor subtypes characterized by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. Briefly, 30 patients with breast cancer were categorized into four groups based on their HR and HER2 status: HR+ no HER2 expression (HER2-0), HR+ HER2-low; HR+ HER2-positive (pos) and HR- HER2-pos. The lipidomic profiles of these patients were analyzed using high-throughput liquid chromatography-mass spectrometry. The data were processed through principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and random forest (RF) classification to assess the lipidomic variations and significant lipid features among these groups. The profiles of the lipids, particularly triglycerides (TG) such as TG(16:0-18:1-18:1)+NH4, were significantly different across the groups. PCA and PLS-DA identified unique lipid profiles in the HR+ HER2-pos and HR+ HER2-0 groups, while RF highlighted phosphatidylinositol-3,4,5-trisphosphate(21:2)+NH4 as a crucial lipid feature for accurate patient grouping. Advanced statistical analysis showed significant correlations between lipid carbon chain length and the number of double bonds within the classifications, providing insights into the role of structural lipid properties in tumor biology. Additionally, a clustering heatmap and network analysis indicated significant lipid-lipid interactions. Pathway enrichment analysis showed critical biological pathways, such as the 'Assembly of active LPL and LIPC lipase complexes', which has high enrichment ratio and statistical significance. In conclusion, the present study underscored that lipidomic profiling is crucial in understanding the metabolic alterations associated with different breast cancer subtypes. These findings highlighted specific lipid features and interactions that may serve as potential biomarkers for breast cancer classification and target pathways for therapeutic intervention. Furthermore, advanced lipidomic analyses can be integrated to decipher complex biological data, offering a foundation for further research into the role of lipid metabolism in cancer progression. [ABSTRACT FROM AUTHOR]

Exploration of versatile nanoplatforms within one single nanostructure for multidisciplinary treatment modalities, especially achieving a synergistic therapeutic efficacy of combinational gene/photothermal cancer therapy is still a great challenge in biomedicine and nanotechnology. In this study, a unique photothermal nanocarrier has successfully been designed and developed for a combination of gene therapy (GT) and photothermal therapy (PTT) of cancer cells. Surface-engineered iron oxides (α-Fe2O3) nanoparticles (NPs) with poly(3,4-ethylenedioxythiophene) (PEDOT) polymer coatings are synthesized using a one-pot in situ oxidative polymerization method. The results show that the as-prepared α-Fe2O3@PEDOT core–shell NPs with a uniform particle size exhibit positively charged surfaces, facilitating efficient siRNA Bcl-2 (B-cell lymphoma-2) uptake for delivery to breast cancer cells. More importantly, α-Fe2O3@PEDOT core–shell NPs not only display good biocompatibility and water dispersibility but also strong optical absorption enhancement in the Vis-NIR region as compared to α-Fe2O3 NPs. The obtained α-Fe2O3@PEDOT core–shell NPs show an efficient photothermal conversion efficacy (η = 54.3%) and photostability under NIR laser irradiation. As a result, both in vitro and in vivo biological studies on two types of breast cancer cells/tumors treated with α-Fe2O3@PEDOT-siRNA nanocomplexes demonstrate high cancer cell apoptosis and tumor inhibition induced by synergistic GT/PTT therapy under mild conditions compared to an individual GT or PTT alone. Taken together, this is the first example of the use of an α-Fe2O3@PEDOT core–shell nanoagent as a siRNA delivery nanocarrier for highly effective gene/photothermal combination anticancer therapy. [ABSTRACT FROM AUTHOR]

Although the prognosis of lower-grade glioma (LGG) patients is better than others, outcomes are highly heterogeneous. Isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status can identify patient subsets with different prognosis. However, in the era of precision medicine, there is still a lack of biomarkers that can accurately predict the individual prognosis of each patient. In this study, we found that most DNA damage response (DDR) genes were aberrantly expressed in LGG patients and were associated with their prognosis. Consequently, we developed an artificial neural network (ANN) model based on DDR genes to predict outcomes of LGG glioma patients. Then, we validated the predictive ability in an independent external dataset and found that the concordance indexes and area under time-dependent receiver operating characteristic curves of the predict index (PI) calculated based on the model were superior to those of the mutation markers. Subgroup analyses demonstrated that the model could accurately identify patients with the same mutation status but different prognosis. Moreover, the model can also identify patients with favorable prognostic mutation status but poor prognosis or vice versa. Finally, we also found that the PI was associated with the mutation status and with the altered immune microenvironment. These results demonstrated that the ANN model can accurately predict outcomes of LGG patients and will contribute to individualized therapies. In addition, a web-based application program for the model was developed. [ABSTRACT FROM AUTHOR]