Triple-negative breast cancer survival prediction: population-based research using the SEER database and an external validation cohort.

Introduction: Triple-negative breast cancer (TNBC) is linked to a poorer outlook, heightened aggressiveness relative to other breast cancer variants, and limited treatment choices. The absence of conventional treatment methods makes TNBC patients susceptible to metastasis. The objective of this research was to assess the clinical and pathological traits of TNBC patients, predict the influence of risk elements on their outlook, and create a prediction model to assist doctors in treating TNBC patients and enhancing their prognosis. Methods: We included 23,394 individuals with complete baseline clinical data and survival information who were diagnosed with primary TNBC between 2010 and 2015 based on the SEER database. External validation utilised a group from The Affiliated Lihuili Hospital of Ningbo University. Independent risk factors linked to TNBC prognosis were identified through univariate, multivariate, and least absolute shrinkage and selection operator regression methods. These characteristics were chosen as parameters to develop 3- and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) nomogram models. Model accuracy was assessed using calibration curves, consistency indices (C-indices), receiver operating characteristic curves (ROCs), and decision curve analyses (DCAs). Finally, TNBC patients were divided into groups of high, medium, and low risk, employing the nomogram model for conducting a Kaplan-Meier survival analysis. Results: In the training cohort, variables such as age at diagnosis, marital status, grade, T stage, N stage, M stage, surgery, radiation, and chemotherapy were linked to OS and BCSS. For the nomogram, the C-indices stood at 0.762, 0.747, and 0.764 in forecasting OS across the training, internal validation, and external validation groups, respectively. Additionally, the C-index values for the training, internal validation, and external validation groups in BCSS prediction stood at 0.793, 0.755, and 0.811, in that order. The findings revealed that the calibration of our nomogram model was successful, and the time-variant ROC curves highlighted its effectiveness in clinical settings. Ultimately, the clinical DCA showcased the prospective clinical advantages of the suggested model. Furthermore, the online version was simple to use, and nomogram classification may enhance the differentiation of TNBC prognosis and distinguish risk groups more accurately. Conclusion: These nomograms are precise tools for assessing risk in patients with TNBC and forecasting survival. They can help doctors identify prognostic markers and create more effective treatment plans for patients with TNBC, providing more accurate assessments of their 3- and 5-year OS and BCSS.

Fat mass and obesity-associated protein (FTO) mediated m6A modification of circFAM192A promoted gastric cancer proliferation by suppressing SLC7A5 decay.

Gastric cancer (GC) is a common malignant tumor worldwide, especially in East Asia, with high incidence and mortality rate. Epigenetic modifications have been reported to participate in the progression of gastric cancer, among which m6A is the most abundant and important chemical modification in RNAs. Fat mass and obesity-associated protein (FTO) is the first identified RNA demethylase but little is known about its role in gastric cancer. In our study, data from TCGA and clinical samples showed that FTO was highly expressed in gastric cancer tissues. Kaplan-Meier plotter suggested that patients with the high level of FTO had a poor prognosis. In vitro and in vivo experiments confirmed the role of FTO in promoting gastric cancer cell proliferation. Mechanistically, we found that FTO bound to circFAM192A at the specific site and removed the m6A modification in circFAM192A, protecting it from degradation. CircFAM192A subsequently interacted with the leucine transporter solute carrier family 7 member 5 (SLC7A5) and enhancing its stability. As a result, an increased amount of SLC7A5 was on the membrane, which facilitated leucine uptake and activated the mTOR signaling pathway. Therefore, our study demonstrated that FTO promoted gastric cancer proliferation through the circFAM192A/SLC7A5 axis in the m6A-dependent manner. Our study shed new light on the role of FTO in gastric cancer progression.

Genetic analysis of Vibrio alginolyticus challenged by Fructus schisandrae reveals the mechanism of virulence genes.

Due to the abusive use of antibiotics, bacterial resistance has become a global problem and poses severe threats to aquaculture. The drug-resistant diseases caused by Vibrio alginolyticus have caused significant economic losses to cultured marine fish. Fructus schisandrae is used to treat inflammatory diseases in China and Japan. There have been no reports of bacterial molecular mechanisms associated with F. schisandrae stress. In this study, the inhibiting effect of F. schisandrae on the growth of V. alginolyticus was detected to understand response mechanisms at the molecular level. The antibacterial tests were analyzed via next-generation deep sequencing technology (RNA sequencing, RNA-seq). Wild V. alginolyticus (CK) was compared with V. alginolyticus, F. schisandrae incubated for 2 h, and V. alginolyticus, F. schisandrae incubated for 4 h. Our results revealed that there were 582 genes (236 upregulated and 346 downregulated) and 1068 genes (376 upregulated and 692 downregulated), respectively. Differentially expressed genes (DEGs) were involved in the following functional categories: metabolic process, single-organism process, catalytic activity, cellular process, binding, membrane, cell part, cell, and localization. FS_2 h was compared with FS_4 h, and 21 genes (14 upregulated and 7 downregulated) were obtained. The RNA-seq results were validated by detecting the expression levels of 13 genes using quantitative real-time polymerase chain reaction (qRT-PCR). The qRT-PCR results matched those of the sequencing, which reinforced the reliability of the RNA-seq. The results revealed the transcriptional response of V. alginolyticus to F. schisandrae, which will provide new ideas for studying V. alginolyticus' complex virulence molecular mechanism and the possibility of developing Schisandra to prevent and treat drug-resistant diseases.

Microbial Interactions Related to N2O Emissions and Temperature Sensitivity from Rice Paddy Fields.

The soil microbiome is a driver of nitrous oxide (N2O) emissions in terrestrial ecosystems. Identifying the core microbiome of N2O emissions and its temperature sensitivity from trillions of soil microorganisms is a great challenge and is essential to improving the predictability of soil-climate feedback related to increasing temperature. Here, the integrated soil microbiome covering archaeal, bacterial, fungal, algal, and microfaunal communities was studied to disengage the potential linkage with its N2O emissions and its temperature sensitivity in paddy fields by hunting for core species pairs. The results showed that between-group interactions of core bacterial and archaeal members and the within-group interactions of core bacterial members jointly contributed to the N2O emissions and its temperature sensitivity. The contribution of between-group interactions (32 to 33%) was greater than that of within groups (10 to 18%). These results suggested that N2O emissions and their fluctuations related to climate warming are affected by the within- and between-group interactions of the soil microbiome. Our results help advance the knowledge on the importance of microbial keystone species and network associations in controlling N2O production and their responses to increasing temperature. IMPORTANCE Soil microorganisms drive emissions of nitrous oxide from soils; this is a powerful greenhouse gas and the dominant ozone-depleting agent. N2O emissions can be partly predicted from soil properties and specific microbial groups, whereas a possible role of below-ground microbial interactions has largely been overlooked. Here, the integrated soil microbiome covering archaeal, bacterial, fungal, algal, and microfaunal communities was studied to disengage the potential linkage with the N2O emissions and temperature sensitivity of the microbiome in paddy fields by hunting for core species pairs. The results showed that between-group interactions of core bacterial and archaeal members and the within-group interactions of core bacterial members jointly contributed to the N2O emissions. The contribution of between-group interactions (32 to 33%) was greater than that of within-group interactions (10 to 18%). Our results help advance the knowledge on the importance of microbial keystone species and interactions in controlling N2O production and their responses to increasing temperature.

Mechanisms Underlying the Virulence Regulation of Vibrio alginolyticus ND-01 pstS and pstB with a Transcriptomic Analysis.

Vibrio alginolyticus is a common opportunistic pathogen of fish, shrimp, and shellfish, and many diseases it causes can result in severe economic losses in the aquaculture industry. Causing host disease was confirmed by several virulence factors of V. alginolyticus. To date, there have been no reports on the effect of the pstS gene on its virulence regulation of V. alginolyticus. The virulence mechanism of target genes regulating V. alginolyticus is worthy of further study. Previous studies found that Fructus schisandrae (30 mg/mL) inhibited the growth of V. alginolyticus ND-01 (OD600 = 0.5) for 4 h, while the expressions of pstS and pstB were significantly affected by F. schisandrae stress. So, we speculated that pstS and pstB might be the virulence genes of V. alginolyticus, which were stably silenced by RNAi to construct the silencing strains pstS-RNAi and pstB-RNAi, respectively. After the expression of pstS or pstB gene was inhibited, the adhesion capacity and biofilm formation of V. alginolyticus were significantly down-regulated. The chemotaxis and biofilm formation ability of pstS-RNAi was reduced by 33.33% and 68.13% compared with the wild-type strain, respectively. Sequence alignment and homology analysis showed that pstS was highly conserved, which suggested that pstS played a vital role in the secretion system of V. alginolyticus. The pstS-RNAi with the highest silencing efficiency was selected for transcriptome sequencing. The Differentially Expressed Genes (DEGs) and GO terms were mapped to the reference genome of V. alginolyticus, including 1055 up-regulated genes and 1134 down-regulated genes. The functions of the DEGs were analyzed by GO and categorized into different enriched functional groups, such as ribosome synthesis, organelles, biosynthesis, pathogenesis, and secretion. These DEGs were then mapped to the reference KEGG pathways of V. alginolyticus and enriched in commonalities in the metabolic, ribosomal, and bacterial secretion pathways. Therefore, pstS and pstB could regulate the bacterial virulence of V. alginolyticus by affecting its adhesion, biofilm formation ability, and motility. Understanding the relationship between the expressions of pstS and pstB with bacterial virulence could provide new perspectives to prevent bacterial diseases.

Revisiting the involvement of ammonia oxidizers and denitrifiers in nitrous oxide emission from cropland soils.

Nitrous oxide (N2O), an ozone-depleting greenhouse gas, is generally produced by soil microbes, particularly NH3 oxidizers and denitrifiers, and emitted in large quantities after N fertilizer application in croplands. N2O can be produced via multiple processes, and reduced, with the involvement of more diverse microbes with different physiological constraints than previously thought; therefore, there is a lack of consensus on the production processes and microbes involved under different agricultural practices. In this study, multiple approaches were applied, including N2O isotopocule analyses, microbial gene transcript measurements, and selective inhibition assays, to revisit the involvement of NH3 oxidizers and denitrifiers, including the previously-overlooked taxa, in N2O emission from a cropland, and address the biological and environmental factors controlling the N2O production processes. Then, we synthesized the results from those approaches and revealed that the overlooked denitrifying bacteria and fungi were more involved in N2O production than the long-studied ones. We also demonstrated that the N2O production processes and soil microbes involved were different based on fertilization practices (plowing or surface application) and fertilization types (manure or urea). In particular, we identified the following intensified activities: (1) N2O production by overlooked denitrifying fungi after manure fertilization onto soil surface; (2) N2O production by overlooked denitrifying bacteria and N2O reduction by long-studied N2O-reducing bacteria after manure fertilization into the plowed layer; and (3) N2O production by NH3-oxidizing bacteria and overlooked denitrifying bacteria and fungi when urea fertilization was applied into the plowed layer. We finally propose the conceptual scheme of N flow after fertilization based on distinct physiological constraints among the diverse NH3 oxidizers and denitrifiers, which will help us understand the environmental context-dependent N2O emission processes.

Graphical models for mean and covariance of multivariate longitudinal data.

Joint mean-covariance modeling of multivariate longitudinal data helps to understand the relative changes among multiple longitudinally measured and correlated outcomes. A key challenge in the analysis of multivariate longitudinal data is the complex covariance structure. This is due to the contemporaneous and cross-temporal associations between multiple longitudinal outcomes. Graphical and data-driven tools that can aid in visualizing the dependence patterns among multiple longitudinal outcomes are not readily available. In this work, we show the role of graphical techniques: profile plots, and multivariate regressograms, in developing mean and covariance models for multivariate longitudinal data. We introduce an R package MLGM (Multivariate Longitudinal Graphical Models) to facilitate visualization and modeling mean and covariance patterns. Through two real studies, microarray data from the T-cell activation study and Mayo Clinic's primary biliary cirrhosis of the liver study, we show the key features of MLGM. We evaluate the finite sample performance of the proposed mean-covariance estimation approach through simulations.

Mitigating N2O emissions from agricultural soils with fungivorous mites.

Nitrous oxide (N2O) is an important greenhouse gas and an ozone-depleting substance. Due to the long persistence of N2O in the atmosphere, the mitigation of anthropogenic N2O emissions, which are mainly derived from microbial N2O-producing processes, including nitrification and denitrification by bacteria, archaea, and fungi, in agricultural soils, is urgently necessary. Members of mesofauna affect microbial processes by consuming microbial biomass in soil. However, how microbial consumption affects N2O emissions is largely unknown. Here, we report the significant role of fungivorous mites, the major mesofaunal group in agricultural soils, in regulating N2O production by fungi, and the results can be applied to the mitigation of N2O emissions. We found that the application of coconut husks, which is the low-value part of coconut and is commonly employed as a soil conditioner in agriculture, to soil can supply a favorable habitat for fungivorous mites due to its porous structure and thereby increase the mite abundance in agricultural fields. Because mites rapidly consume fungal N2O producers in soil, the increase in mite abundance substantially decreases the N2O emissions from soil. Our findings might provide new insight into the mechanisms of soil N2O emissions and broaden the options for the mitigation of N2O emissions.