Gram staining applied to Human spermatozoa: a simple method for studyng chromatin condensation status

Gram staining applied to human spermatozoa from fertile donors is described. The stain revealed populations of Gram-positive and Gram-negative spermatozoa. Data showed a significant and progressive decrease in the percentage of Gram-positive spermatozoa at different times during the chromatin decondensation procedure (SDS-BSA and SDS-EDTA). No significant correlation could be found between Gram staining and other functional tests used for spermatozoa; only the aniline blue staining test showed a poor correlation. Our study demonstrates that normal spermatozoa with regular chromatin condensation appear Gram-positive, while spermatozoa with altered chromatin condensation appear Gram-negative

Development and standardization of multiplexed antibody microarrays for use in quantitative proteomics

BACKGROUND: Quantitative proteomics is an emerging field that encompasses multiplexed measurement of many known proteins in groups of experimental samples in order to identify differences between groups. Antibody arrays are a novel technology that is increasingly being used for quantitative proteomics studies due to highly multiplexed content, scalability, matrix flexibility and economy of sample consumption. Key applications of antibody arrays in quantitative proteomics studies are identification of novel diagnostic assays, biomarker discovery in trials of new drugs, and validation of qualitative proteomics discoveries. These applications require performance benchmarking, standardization and specification. RESULTS: Six dual-antibody, sandwich immunoassay arrays that measure 170 serum or plasma proteins were developed and experimental procedures refined in more than thirty quantitative proteomics studies. This report provides detailed information and specification for manufacture, qualification, assay automation, performance, assay validation and data processing for antibody arrays in large scale quantitative proteomics studies. CONCLUSION: The present report describes development of first generation standards for antibody arrays in quantitative proteomics. Specifically, it describes the requirements of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; provides the rationale for the application of standardized statistical approaches to manage the data output of highly replicated assays; defines design requirements for controls to normalize sample replicate measurements; emphasizes the importance of stringent quality control testing of reagents and antibody microarrays; recommends the use of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and presents survey procedures to reveal the significance of biomarker findings

Four Months of Kettlebell Training Improves Muscle Strength and Functional Outcomes in Older Adults

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Computer-assisted liver graft steatosis assessment via learning-based texture analysis

Purpose: Fast and accurate graft hepatic steatosis (HS) assessment is of primary importance for lowering liver dysfunction risks after transplantation. Histopathological analysis of biopsied liver is the gold standard for assessing HS, despite being invasive and time consuming. Due to the short time availability between liver procurement and transplantation, surgeons perform HS assessment through clinical evaluation (medical history, blood tests) and liver texture visual analysis. Despite visual analysis being recognized as challenging in the clinical literature, few efforts have been invested to develop computer-assisted solutions for HS assessment. The objective of this paper is to investigate the automatic analysis of liver texture with machine learning algorithms to automate the HS assessment process and offer support for the surgeon decision process. Methods: Forty RGB images of forty different donors were analyzed. The images were captured with an RGB smartphone camera in the operating room (OR). Twenty images refer to livers that were accepted and 20 to discarded livers. Fifteen randomly selected liver patches were extracted from each image. Patch size was 100 × 100. This way, a balanced dataset of 600 patches was obtained. Intensity-based features (INT), histogram of local binary pattern (HLBPriu2), and gray-level co-occurrence matrix (FGLCM) were investigated. Blood-sample features (Blo) were included in the analysis, too. Supervised and semisupervised learning approaches were investigated for feature classification. The leave-one-patient-out cross-validation was performed to estimate the classification performance. Results: With the best-performing feature set (HLBPriu2+INT+Blo) and semisupervised learning, the achieved classification sensitivity, specificity, and accuracy were 95, 81, and 88%, respectively. Conclusions: This research represents the first attempt to use machine learning and automatic texture analysis of RGB images from ubiquitous smartphone cameras for the task of graft HS assessment. The results suggest that is a promising strategy to develop a fully automatic solution to assist surgeons in HS assessment inside the OR

Evidence for light-by-light scattering in heavy-ion collisions with the ATLAS detector at the LHC

Light-by-light scattering (gamma gamma -> gamma gamma) is a quantum-mechanical process that is forbidden in the classical theory of electrodynamics. This reaction is accessible at the Large Hadron Collider thanks to the large electromagnetic field strengths generated by ultra-relativistic colliding lead ions. Using 480 mu b(-1) of lead-lead collision data recorded at a centre-of-mass energy per nucleon pair of 5.02 TeV by the ATLAS detector, here we report evidence for light-by-light scattering. A total of 13 candidate events were observed with an expected background of 2.6 +/- 0.7 events. After background subtraction and analysis corrections, the fiducial cross-section of the process Pb + Pb (gamma gamma) -> Pb-(center dot) + Pb-(center dot) gamma gamma, for photon transverse energy E-T > 3 GeV, photon absolute pseudorapidity vertical bar eta vertical bar < 2.4, diphoton invariant mass greater than 6 GeV, diphoton transverse momentum lower than 2 GeV and diphoton acoplanarity below 0.01, is measured to be 70 +/- 24 (stat.) +/- 17 (syst.) nb, which is in agreement with the standard model predictions

Cell-laden hydrogel as a clinical-relevant 3D model for analyzing neuroblastoma growth, immunophenotype, and susceptibility to therapies

High risk Neuroblastoma (NB) includes aggressive, metastatic solid tumors of childhood. The survival rate improved only modestly, despite the use of combination therapies including novel immunotherapies based on the antibody mediated targeting of tumor-associated surface ligands. Treatment failures may be due to the lack of adequate in vitro models for studying, in a given patient, the efficacy of potential therapeutics, including those aimed to enhance anti-tumor immune responses. We here propose a 3D alginate-based hydrogel as extracellular microenvironment to evaluate the effects of the three-dimensionality on biological and immunological properties of NB cells. NB cell lines grown within the 3D alginate spheres presented spheroid morphology, optimal survival, and proliferation capabilities, and a reduced sensitivity to the cytotoxic effect of imatinib mesylate. 3D cultured NB cells were also evaluated for the constitutive and IFN-y-induced expression of surface molecules capable of tuning the anti-tumor activity of NK cells including immune checkpoint ligands. In particular, IFN-y induced de novo expression of high amounts of HLA-I molecules, which protected NB cells from the attack mediated by KIR/KIR-L matched NK cells. Moreover, in the 3D alginate spheres, the cytokine increased the expression of the immune checkpoint ligands PD-Ls and B7-H3 while virtually abrogating that of PVR, a ligand of DNAM-1 activating receptor, whose expression correlates with high susceptibility to NK-mediated killing. Our 3D model highlighted molecular features that more closely resemble the immunophenotypic variants occurring in vivo and not fully appreciated in classical 2D culture conditions.Thus, based on our results, 3D alginate-based hydrogels might represent a clinical-relevant cell culture platform where to test the efficacy of personalized therapeutic approaches aimed to optimize the current and innovative immune based therapies in a very systematic and reliable way

PD-L1 expression in metastatic neuroblastoma as an additional mechanism for limiting immune surveillance

The prognosis of high-risk neuroblastoma (NB) remains poor, although immunotherapies with anti-GD2 antibodies have been reported to provide some benefit. Immunotherapies can be associated with an IFNγ storm that induces in tumor cells the “adaptive immune resistance” characterized by the de-novo expression of Programmed Death Ligands (PD-Ls). Tumor cells can also constitutively express PD-Ls in response to oncogenic signaling. Here, we analyze the constitutive and the inducible surface expression of PD-Ls in NB cells. We show that virtually all HLA class Ipos NB cell lines constitutively express PD-L1, whereas PD-L2 is rarely detected. IFNγ upregulates or induces PD-L1 both in NB cell lines in vitro and in NB engrafted nude/nude mice. Importantly, after IFNγ stimulation PD-L1 can be acquired by NB cell lines, as well as by metastatic neuroblasts isolated from bone marrow aspirates of high-risk NB patients, characterized by different MYCN amplification status. Interestingly, in one patient NB cells were poorly responsive to IFNγ stimulation, pointing out that responsiveness to IFNγ might represent a further element of heterogeneity in metastatic neuroblasts. Finally, we document the presence of lymphocytes expressing the PD-1 receptor in NB-infiltrated bone marrow of patients. PD-1pos cells are mainly represented by αβ T cells, but also include small populations of γδ T cells and NK cells. Moreover, PD-1pos T cells have a higher expression of activation markers. Overall, our data show that a PD-L1-mediated immune resistance mechanism occurs in metastatic neuroblasts and provide a biological rationale for blocking the PD-1/PD-Ls axis in future combined immunotherapeutic approaches