The complex interactions between cells of the tumor microenvironment and cancer cells are considered a major determinant of cancer progression and metastasis. Yet, our understanding of the mechanisms of metastatic disease is not sufficient to successfully treat patients with advanced-stage cancer. JUNB is a member of the AP-1 transcription factor family shown to be frequently deregulated in human cancer and associated with invasion and metastasis. A strikingly high stromal JUNB expression in human breast cancer samples prompted us to functionally investigate the consequences of JUNB loss in cells of the tumor microenvironment on cancer progression and metastasis in mice. To adequately mimic the clinical situation, we applied a syngeneic spontaneous breast cancer metastasis model followed by primary tumor resection and identified stromal JUNB as a potent suppressor of distant metastasis. Comprehensive characterization of the JUNB-deficient tumor microenvironment revealed a strong influx of myeloid cells into primary breast tumors and lungs at early metastatic stage. In these infiltrating neutrophils, BV8 and MMP9, proteins promoting angiogenesis and tissue remodeling, were specifically upregulated in a JUNB-dependent manner. Taken together, we established stromal JUNB as a strong suppressor of distant metastasis. Consequently, therapeutic strategies targeting AP-1 should be carefully designed not to interfere with stromal JUNB expression as this may be detrimental for cancer patients.Quantitative abilities are widely recognized to play important roles in several ecological contexts, such as foraging, mate choice, and social interaction. Indeed, such abilities are widespread among vertebrates, in particular mammals, birds, and fish. Recently, there has been an increasing number of studies on the quantitative abilities of invertebrates. In this review, we present the current knowledge in this field, especially focusing on the ecological relevance of the capacity to process quantitative information, the similarities with vertebrates, and the different methods adopted to investigate this cognitive skill. The literature argues, beyond methodological differences, a substantial similarity between the quantitative abilities of invertebrates and those of vertebrates, supporting the idea that similar ecological pressures may determine the emergence of similar cognitive systems even in distantly related species.Neurological disorders affect various aspects of life. Finding drugs for the central nervous system is a very challenging and complex task due to the involvement of the blood-brain barrier, P-glycoprotein, and the drug’s high attrition rates. The availability of big data present in online databases and resources has enabled the emergence of artificial intelligence techniques including machine learning to analyze, process the data, and predict the unknown data with high efficiency. The use of these modern techniques has revolutionized the whole drug development paradigm, with an unprecedented acceleration in the central nervous system drug discovery programs. Also, the new deep learning architectures proposed in many recent works have given a better understanding of how artificial intelligence can tackle big complex problems that arose due to central nervous system disorders. Therefore, the present review provides comprehensive and up-to-date information on machine learning/artificial intelligence-triggered effort in the brain care domain. In addition, a brief overview is presented on machine learning algorithms and their uses in structure-based drug design, ligand-based drug design, ADMET prediction, de novo drug design, and drug repurposing. Lastly, we conclude by discussing the major challenges and limitations posed and how they can be tackled in the future by using these modern machine learning/artificial intelligence approaches.

To assess the prognostic value of the Dutch criteria for patients with early-stage hormone receptor-positive and human epidermal growth factor receptor 2-negative breast cancer from the Taiwan Cancer RegistryDatabase.

We included 8295 patients with early-stage node-negative breast cancer who underwent surgery during January 2008-December 2012. Patients were stratified into low- and high-risk groups based on the Dutch criteria. The Kaplan-Meier method and log-rank test were used to estimate the difference in breast cancer-specific survival (BCSS) and overall survival (OS) between groups. Multivariable analysis was used to evaluate the prognostic value of the Dutch criteria.

Overall, the low-risk and high-risk groups comprised 5375 and 2920 patients, respectively. In the low- and high-risk groups, the 5-year BCSS rate was 99.6% and 98.2% (P < 0.0001) and the 5-year OS rate was 98.3% and 96.8% (P < 0.0001), respectively. The hazard ratio for BCSS was 4.18 (95% confidence interval [CI] 2.63-6.63, P < 0.0001), and the hazard ratio for OS was 1.94 (95% CI 1.48-2.55); both were significantly poorer in the high-risk group than in the low-risk group. In the low-risk group, the 5-year BCSS and OS of patients who did and did not receive adjuvant chemotherapy were similar (99.5% versus 99.6% [P = 0.927] and 98.8% and 98.1% [P = 0.0683], respectively).

The prognosis of low-risk patients as classified using the Dutch criteria is excellent with or without adjuvant chemotherapy. The benefit of multi-gene testing for chemotherapy decision-making might be minimal in these patients.

The prognosis of low-risk patients as classified using the Dutch criteria is excellent with or without adjuvant chemotherapy. The benefit of multi-gene testing for chemotherapy decision-making might be minimal in these patients.

Identification of effective biomarkers for the benefit of endocrine treatment and understanding the molecular pathways that contribute to the development of resistance are of crucial importance to the management of luminal breast cancer. The amino acid transporter SLC1A5 has emerging importance as a prognostic marker and potential therapeutic target in various types of cancer. This study aims to investigate its role in luminal breast cancer as a potential predictive marker for endocrine treatment.

SLC1A5 expression was assessed at the transcriptomic and proteomic levels in large, well-characterized cohorts of luminal breast cancer. The sensitivity to endocrine therapy after SLC1A5 knockdown was investigated in vitro, using MCF7 and MDA-MB-175 cell lines. Bioinformatic analyses were performed to study the interacting networks of SLC1A5 and to identify a key co-expressed gene with SLC1A5.

Here, we showed that patients with tumors that highly expressed SLC1A5 associated with a high risk of relapse after endocrine treatment. In vitro, depletion of SLC1A5 increases the sensitivity of luminal breast cancer cells to tamoxifen. TALDO1 was identified as key co-expressed gene with SLC1A5, and in vitro knockdown of SLC1A5 showed reduction in TALDO1 expression. Indeed, TALDO1 was associated with poor clinical outcomes in patients who were subject to endocrine therapy.

These findings suggest that metabolic alterations, particularly the interaction between the key amino acid transporter SLC1A5 and metabolic enzyme TALDO1, could affect the sensitivity of endocrine therapy. This study demonstrated the prognostic value of both SLC1A5 and TALDO1 as biomarkers in luminal breast cancer.

These findings suggest that metabolic alterations, particularly the interaction between the key amino acid transporter SLC1A5 and metabolic enzyme TALDO1, could affect the sensitivity of endocrine therapy. This study demonstrated the prognostic value of both SLC1A5 and TALDO1 as biomarkers in luminal breast cancer.Knowledge of the persistence of Cry proteins in transgenic corn residue after harvest is necessary to assess the ecological risk to nontarget organisms. The amount of protein remaining in crop residue declines over time by a combination of microbial decomposition and leaching, both influenced by temperature, precipitation, and the amount of residue-soil contact. Here, we investigated how long biologically active Cry proteins persist in SmartStax corn residue expressing Cry1A.105, Cry1F, Cry2Ab2, Cry3Bb1, and Cry34/35Ab1, when subjected to four post-harvest practices (chisel plow tillage, flail mowing, cover crop planting, and undisturbed residue). Protein activity in residue samples collected up to 25 weeks after harvest was measured by Ostrinia nubilalis feeding bioassays and cross validated with detection frequencies determined by ELISA. All corn residue remained above ground in the flail-mowed and undisturbed treatments, while the cover crop and chisel plow treatments left 88.3 and 39.6% of the residue remaining above ground, respectively. Cry proteins retained biological activity for as long as 24 weeks after harvest when residue was left above ground with less soil contact, typical of no-till corn systems. ELISA detections were positively correlated with results of the feeding bioassays, which revealed the presence of active proteins beyond the point of ELISA detection.Excessive Cd content and high Cd/Zn ratio in rice grains threaten human health. To study the reduction effects of combined soil amendments on Cd content and Cd/Zn ratio in rice planting in soils with different Cd contamination levels, we conducted field trials in three regions of Hunan province, China. Six field treatments were designed in each study area, including control (CK), lime alone (L), lime combined with sepiolite (LS), phosphate fertilizer (LP), organic fertilizer (LO) and phosphate fertilizer + organic fertilizer (LPO). The application of the combined amendments reduced the Cd content in rice grains to less than the Food Health Standard of China (0.2 mg/kg) and the Cd/Zn ratio to less than the safety threshold of 0.015. The average reduction rates of grain Cd content under the combined treatments among the three regions increased with the increase in Cd content in the soil. Meanwhile, the amendments also decreased the soil available Cd and Zn concentration significantly. The LO had the highest efficiency on decreasing Cd content in rice grains among these amendments, which is ranged from 44.6% to 52.8% in the three regions compared with CK. Similarly, high reduction rates of Cd/Zn ratio were found in the LO treatment, with an average value of 57.3% among the three regions. The grain Cd contents and Cd/Zn ratios were significantly correlated with the soil available Cd concentrations, plant uptake factor and the straw to rice grain translocation factor (TFgs) (P  less then  0.05). The results indicated that the combined soil amendments, especially lime combined with organic fertilizer, would be an effective way to control Cd content in rice.Environmental exposure to trace elements has been widely suspected as an etiological factor for the emergence of chronic kidney disease of undetermined origin (CKDu) that prevails in certain districts of the dry zone areas of Sri Lanka. Contaminated rice can be act as a host for potentially toxic trace elements that ultimately led to health hazards; thus, rice soils were investigated in detail, giving particular attentions to identified CKDu hotspots. A total of 102 rice soil samples were collected from main climatic zones viz. wet and dry zones including CKDu hotspots. In addition to pH, electrical conductivity and cation exchange capacity, acid extracted major and trace element contents in rice soils were determined by using ICP-MS. Significant differences were observed for Mn, Ni, Cu, Zn, and Pb contents between climatic zones. Arsenic and Pb contents in soils were lower than the levels reported in soils from other regions of the world, though significantly higher contents were observed in CKDu regions compared to non-endemic wet zone regions.