An Overview of Nickel (Ni2+) Essentiality, Toxicity and Tolerance Strategies in Plants

Heavy metals (HMs) toxicity has an unavoidable threat to environment and public health due to their increasing contamination and accumulation in atmosphere which ultimately passes to the living beings by the route of food chain. Heavy metals are increasing rapidly in soil and water by weathering of rocks and anthropogenic activities and are now emerging as a major health hazard to humans and plants. Among them Nickel (Ni2+) is a controversial element because of debate on its essentiality or non-essentiality in plants. Ni2+ is an important constituent (micronutrient) of many metallo-enzymes including urease, Ni-Fe hydrogenase, Ni-superoxide dismutase etc. while at higher level it affects all cellular and metabolic processes and causes retardation of germination, competition with other essential metal ions, osmotic imbalance, alteration of many enzymatic activities, disruption of cell structure and wilting, reduced photosynthetic activity, oxidative stress etc. Plants also possess some natural and stress-induced strategies to cope up with Ni2+ excess/toxicity. These strategies include growth regulators, antioxidative enzymes, amino acids as osmoprotectant, and chelation of Ni2+ with metalloproteins and metallothionins. This review focuses on researches done on the morpho-biochemical alterations induced by elevated Ni2+ concentration in plants and as well as the strategies adapted by plants to survive and neutralize the effects of these alterations

An Active Learning Approach for Rapid Characterization of Endothelial Cells in Human Tumors

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers

HIF-α Effects on c-Myc Distinguish Two Subtypes of Sporadic VHL-Deficient Clear Cell Renal Carcinoma

VHL tumor suppressor loss results in hypoxia inducible factor-alpha (HIF-α) stabilization, and occurs in 70% of sporadic clear cell renal carcinomas (ccRCCs). To determine whether opposing influences of HIF-1α and HIF-2α on c-Myc activity regulate human ccRCC progression, we analyzed VHL genotype and HIF-α expression in 160 primary tumors, which segregated into three groups with distinct molecular characteristics. Interestingly, ccRCCs with intact VHL, as well as pVHL-deficient, HIF-1α/HIF-2α expressing ccRCCs, exhibited enhanced Akt/mTOR and ERK/MAPK signaling. In contrast, pVHL-deficient ccRCCs expressing only HIF-2α displayed elevated c-Myc activity, resulting in enhanced proliferation and resistance to replication stress. These reproducible distinctions in ccRCC behavior delineate HIF-α effects on c-Myc in vivo and suggest molecular criteria for selecting targeted therapies

Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study

Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p < 0.001, univariable hazard ratio [HR] = 2.83, 95% confidence interval [CI]: 2.03-3.93, concordance index [c-index] = 0.68, median years-to-BCR: 1.7). Histotyping was also prognostic in clinically stratified subsets, such as patients with Gleason grade group 3 (HR = 4.09) and negative surgical margins (HR = 3.26). Histotyping was prognostic independent of grade group, margin status, pathological stage, and preoperative prostate-specific antigen (PSA) (multivariable p < 0.001, HR = 2.09, 95% CI: 1.40-3.10, n = 648). The combination of Histotyping, grade group, and preoperative PSA outperformed Decipher (c-index = 0.75 vs. 0.70, n = 167). These results suggest that a prognostic classifier for prostate cancer based on digital images could serve as an alternative or complement to molecular-based companion diagnostic tests

Endoscopic orbital decompression for Graves′ orbitopathy

Aim: To study the efficacy of endonasal endoscopic orbital decompression in cases of Graves′ orbitopathy. Material and Methods: A total of 24 orbits in 12 patients underwent endoscopic orbital decompression for graves orbitopathy in the period between October 2002 and December 2010. Indications for surgery included proptosis, corneal exposure, keratitis, and compressive optic neuropathy. Decompression was accomplished by the removal of the medial and part of inferior wall of the orbit and slitting of the orbital periosteum. Pre and postoperative exophthalmometry measurements and visual acuity were recorded and compared. Results: A mean orbital regression of 3.70 mm was noted following endoscopic decompression. The visual acuity improved significantly in one of two eyes decompressed for failing visual acuity secondary to optic nerve compression. Transient diplopia was invariable following surgery but resolved over the next 8 weeks. One case manifested unilateral frontal sinus obstruction symptoms 4 months postoperatively and responded to medical therapy. Conclusion: Endonasal endoscopic orbital decompression provides for an effective, safe, and minimally invasive treatment for proptosis and visual loss of Graves Orbitopathy. Long-term problems with diplopia were not noted in the endonasal endoscopic approach for orbital decompression

The Relationship between Obesity, Prostate Tumor Infiltrating Lymphocytes and Macrophages, and Biochemical Failure.

Obesity reflects a chronic inflammatory environment that may contribute to prostate cancer progression and poor treatment outcomes. However, it is not clear which mechanisms drive this association within the tumor microenvironment. The aim of this pilot study was to examine prostatic inflammation via tumor infiltrating lymphocytes and macrophages characterized by obesity and cancer severity.We studied paraffin-embedded prostatectomy tissue from 99 participants (63 non-obese and 36 obese) from the Study of Clinical Outcomes, Risk and Ethnicity (University of Pennsylvania). Pathologists analyzed the tissue for type and count of lymphocytes and macrophages, including CD3, CD8, FOXP3, and CD68. Pathology data were linked to clinical and demographic variables. Statistical analyses included frequency tables, Kruskal-Wallis tests, Spearman correlations, and multivariable models.We observed positive univariate associations between the number of CD68 cells and tumor grade (p = 0.019). In multivariable analysis, CD8 counts were associated with time to biochemical failure (HR = 1.09, 95% CI = 1.004-1.192, p-value = 0.041.) There were no differences in lymphocytes or macrophages by obesity status or BMI.The number of lymphocytes and macrophages in the tumor microenvironment did not differ by obesity status. However, these inflammation markers were associated with poor prostate cancer outcomes. Further examination of underlying mechanisms that influence obesity-related effects on prostate cancer outcomes is warranted. Such research will guide immunotherapy protocols and weight management as they apply to diverse patient populations and phenotypes