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Breast cancer is composed of several well-recognized subtypes including estrogen receptor, progesterone receptor and HER2 triple-negative breast cancer (TNBC). Without available targeted therapy options, standard of care for TNBC remains chemotherapy. It is of interest to note that TNBC tumors generally have better responses to chemotherapy compared with other subtypes. However, patients without complete response account for approximately 80% of TNBC. Mounting evidence suggests significant heterogeneity within the TNBC subtype, and studies have focused on genetic targets with high rates of altered expression. Recent studies suggest clear possibilities for benefits from targeted therapy in TNBC. In this review, we summarize studies of targeted therapy, including within mouse models, and discuss their applications in the development of combinatorial treatments to treat TNBC.

The gut microbiota has a crucial effect on regulating the intestinal mucosal immunity and maintaining intestinal homeostasis both in health and in disease state. Many effects are mediated by gut microbiota-derived metabolites and tryptophan, an essential aromatic amino acid, is considered important among many metabolites in the crosstalk between gut microbiota and the host. Kynurenine, serotonin, and indole derivatives are derived from the three major tryptophan metabolism pathways modulated by gut microbiota directly or indirectly. Aryl hydrocarbon receptor (AHR) is a cytoplasmic ligand-activated transcription factor involved in multiple cellular processes. Tryptophan metabolites as ligands can activate AHR signaling in various diseases such as inflammation, oxidative stress injury, cancer, aging-related diseases, cardiovascular diseases (CVD), and chronic kidney diseases (CKD). Accumulated uremic toxins in the body fluids of CKD patients activate AHR and affect disease progression. In this review, we will elucidate the relationship between gut microbiota-derived uremic toxins by tryptophan metabolism and AHR activation in CKD and its complications. This review will provide therapeutic avenues for targeting CKD and concurrently present challenges and opportunities for designing new therapeutic strategies against renal fibrosis.

Dysbiosis represents changes in composition and structure of the gut microbiome community (microbiome), which may dictate the physiological phenotype (health or disease). Recent technological advances and efforts in metagenomic and metabolomic analyses have led to a dramatical growth in our understanding of microbiome, but still, the mechanisms underlying gut microbiome–host interactions in healthy or diseased state remain elusive and their elucidation is in infancy. Disruption of the normal gut microbiota may lead to intestinal dysbiosis, intestinal barrier dysfunction, and bacterial translocation. Excessive uremic toxins are produced as a result of gut microbiota alteration, including indoxyl sulphate, p -cresyl sulphate, and trimethylamine-N-oxide, all implicated in the variant processes of kidney diseases development. This review focuses on the pathogenic association between gut microbiota and kidney diseases (the gut–kidney axis), covering CKD, IgA nephropathy, nephrolithiasis, hypertension, acute kidney injury, hemodialysis and peritoneal dialysis in clinic. Targeted interventions including probiotic, prebiotic and symbiotic measures are discussed for their potential of re-establishing symbiosis, and more effective strategies for the treatment of kidney diseases patients are suggested. The novel insights into the dysbiosis of the gut microbiota in kidney diseases are helpful to develop novel therapeutic strategies for preventing or attenuating kidney diseases and complications.

The endosomal-lysosomal system is made up of a set of intracellular membranous compartments that dynamically interconvert, which is comprised of early endosomes, recycling endosomes, late endosomes, and the lysosome. In addition, autophagosomes execute autophagy, which delivers intracellular contents to the lysosome. Maturation of endosomes and/or autophagosomes into a lysosome creates an unique acidic environment within the cell for proteolysis and recycling of unneeded cellular components into usable amino acids and other biomolecular building blocks. In the endocytic pathway, gradual maturation of endosomes into a lysosome and acidification of the late endosome are accompanied by vesicle trafficking, protein sorting and targeted degradation of some sorted cargo. Two opposing sorting systems are operating in these processes: the endosomal sorting complex required for transport (ESCRT) supports targeted degradation and the retromer supports retrograde retrieval of certain cargo. The endosomal-lysosomal system is emerging as a central player in a host of neurodegenerative diseases, demonstrating potential roles which are likely to be revealed in pathogenesis and for viable therapeutic strategies. Here we focus on the physiological process of endosomal-lysosomal maturation, acidification and sorting systems along the endocytic pathway, and further discuss relationships between abnormalities in the endosomal-lysosomal system and neurodegenerative diseases, especially Alzheimer’s disease (AD).

WRKY transcription factors constitute one of the largest transcription factor families in plants, and play crucial roles in plant growth and development, defense regulation and stress responses. However, knowledge about this family in maize is limited. In the present study, we identified a drought-induced WRKY gene, ZmWRKY106, based on the maize drought de novo transcriptome sequencing data. ZmWRKY106 was identified as part of the WRKYII group, and a phylogenetic tree analysis showed that ZmWRKY106 was closer to OsWRKY13. The subcellular localization of ZmWRKY106 was only observed in the nucleus. The promoter region of ZmWRKY106 included the C-repeat/dehydration responsive element (DRE), low-temperature responsive element (LTR), MBS, and TCA-elements, which possibly participate in drought, cold, and salicylic acid (SA) stress responses. The expression of ZmWRKY106 was induced significantly by drought, high temperature, and exogenous abscisic acid (ABA), but was weakly induced by salt. Overexpression of ZmWRKY106 improved the tolerance to drought and heat in transgenic Arabidopsis by regulating stress-related genes through the ABA-signaling pathway, and the reactive oxygen species (ROS) content in transgenic lines was reduced by enhancing the activities of superoxide dismutase (SOD), peroxide dismutase (POD), and catalase (CAT) under drought stress. This suggested that ZmWRKY106 was involved in multiple abiotic stress response pathways and acted as a positive factor under drought and heat stress.

Chronic kidney disease (CKD) increases the risk and prevalence of cardiovascular disease (CVD) morbidity and mortality. Recent studies have revealed marked changes in the composition of the microbiome and the metabolome and their potential influence in renal disease and CVD via the accumulation of microbial-derived uremic toxins. However, the effect of unilateral ureteral obstruction (UUO) on the gut microbiome and circulating metabolites is unknown. Male Sprague-Dawley rats were randomized to UUO and sham-operated control groups. Renal histology, colonic microbiota, and plasma metabolites were examined two weeks later. We employed 16S rRNA sequence and untargeted metabolomic analyses to explore the changes in colonic microbiota and plasma metabolites and their relationship with tubulointerstitial fibrosis (TIF). The UUO rats exhibited tubular atrophy and dilatation, interstitial fibrosis and inflammatory cell infiltration in the obstructed kidney. UUO rats showed significant colonic enrichment and depletion of genera. Significant differences were identified in 219 plasma metabolites involved in lipid, amino acid, and bile acid metabolism, which were consistent with gut microbiota-related metabolism. Interestingly, tryptophan and its metabolites kynurenine, 5-hydroxytryptophan and 5-hydroxytryptamine levels, which were linked with TIF, correlated with nine specific genera. Plasma tryptophan level was positively correlated with Clostridium IV, Turicibacter , Pseudomonas and Lactobacillales , and negatively correlated with Oscillibacter , Blautia , and Intestinimonas , which possess the genes encoding tryptophan synthase (K16187), indoleamine 2,3-dioxygenase (K00463) and tryptophan 2,3-dioxygenase (K00453) and their corresponding enzymes (EC:1.13.11.52 and EC:1.13.11.11) that exacerbate TIF. In conclusion, UUO results in profound changes in the gut microbiome and circulating metabolites, events that contribute to the pathogenesis of inflammation and TIF. Chronic kidney disease: The contribution of gut bacteria An imbalance in gut bacteria contributes to kidney tissue scarring and declined kidney function. An international study led by Ying-Yong Zhao at Northwest University, Xi’an, China, analyzed the composition of the gut microbes in a rat model of chronic renal injury. They found that urinary tract obstruction was associated with changes in gut microbe composition and altered gut microbe-related metabolism of lipids, amino acids and bile acid. Lower levels of the essential amino acid tryptophan in plasma were linked to the deterioration of renal function. Treatment with ergone, a compound extracted from medicinal mushrooms, restored the levels of plasma tryptophan as well as the expression of proteins involved in maintaining the intestinal barrier. These findings suggest that restoring the function of the intestinal barrier could prevent kidney damage due to microbial imbalance in the gut.

Background The Pyrabactin resistance 1-like proteins (PYR/PYL/RCAR) protein plays a critical regulatory role in the ABA signal transduction pathway as a direct receptor of abscisic acid (ABA). Although PYL genes have been identified in a variety of plants, the evolution and structural characteristics of these genes in alfalfa ( Medicago sativa ) are largely unknown. Therefore, a comprehensive bioinformatics analysis of the PYL gene family was performed in this research. Results The results indicated that 41 MsPYL genes were unevenly distributed across 24 chromosomes. According to gene structure, conservative features, and phylogenetic relationships, MsPYL proteins can be divided into 6 groups, all of which have PYR/PYL/RCAR domains, and MsPYL proteins are relatively small (molecular weight 19.59 kDa to 25.31 kDa). MsPYL genes contains cis-acting elements that has functions in plant growth and development, hormone regulation, and stress response. Furthermore, transcriptome data showed that drought stress affected the MsPYL genes’ expression levels in alfalfa. Tissue specificity analysis revealed that all MsPYL genes exhibited varying responses to drought, abscisic acid (ABA), salicylic acid (SA), and indole-3-acetic acid (IAA). Additionally, all MsPYL genes were expressed to different extents in both the aboveground and underground tissues following stimulation. They were induced by IAA, ABA, and SA from 6 h to 12 h, and ABA induced MsPYL4 most significantly at the 12 h mark. MsPYL4 , MsPYL8 , MsPYL11 , and MsPYL19 were expressed only after hormone treatment. Conclusions The results of this study indicate that the MsPYL genes are closely related to stress response and provide new candidate genes for further exploration of MsPYL genes function and improvement and innovation of drought-resistant alfalfa germplasm.

Multi-modal systems extract information about the environment using specialized sensors that are optimized based on the wavelength of the phenomenology and material interactions. To maximize the entropy, complementary systems operating in regions of non-overlapping wavelengths are optimal. VIS-IR (Visible-Infrared) systems have been at the forefront of multi-modal fusion research and are used extensively to represent information in all-day all-weather applications. Prior to image fusion, the image pairs have to be properly registered and mapped to a common resolution palette. However, due to differences in the device physics of image capture, information from VIS-IR sensors cannot be directly correlated, which is a major bottleneck for this area of research. In the absence of camera metadata, image registration is performed manually, which is not practical for large datasets. Most of the work published in this area assumes calibrated sensors and the availability of camera metadata providing registered image pairs, which limits the generalization capability of these systems. In this work, we propose a novel end-to-end pipeline termed DeepFusion for image registration and fusion. Firstly, we design a recursive crop and scale wavelet spectral decomposition (WSD) algorithm for automatically extracting the patch of visible data representing the thermal information. After data extraction, both the images are registered to a common resolution palette and forwarded to the DNN for image fusion. The fusion performance of the proposed pipeline is compared and quantified with state-of-the-art classical and DNN architectures for open-source and custom datasets demonstrating the efficacy of the pipeline. Furthermore, we also propose a novel keypoint-based metric for quantifying the quality of fused output.

Industrial plants now stream thousands of temperature, pressure, flow rate, and composition measurements at minute-level intervals. These multi-sensor records often contain variable transport or residence time delays that hinder accurate disturbance analysis. This study applies lag-specific transfer entropy (LSTE) to historical sensor logs to identify the instrument that first deviates from normal operation and the time required for that deviation to appear at downstream points. A self-prediction optimization step removes each sensor’s own information storage, after which LSTE is computed at candidate lags and tested against time-shifted surrogates for statistical significance. The method is benchmarked on a nonlinear simulation, the Tennessee Eastman plant, a three-phase separator test rig, and a full-scale blast furnace line. Across all cases, LSTE locates the disturbance origin and reports propagation times that match known process physics, while significantly reducing false links compared to classical transfer entropy.