Occult lung malignancy presenting with finger pain: a case report

<p>Abstract</p> <p>Introduction</p> <p>Lung cancer is currently one of the most common malignancies in the world. Early detection is an important prognostic factor. Unfortunately, initial symptoms may be vague and a substantial proportion of cases present with the effects of metastases.</p> <p>Case presentation</p> <p>We discuss a case of occult lung malignancy in a 61-year-old man. The only symptom at presentation was pain in the right ring finger due to metastasis from the lung primary.</p> <p>Conclusion</p> <p>This case highlights the need for vigilance when a patient presents with unusual or unexplained symptoms, especially if they have known risk factors for cancer.</p

Soundscapes predict species occurrence in tropical forests

Accurate occurrence data is necessary for the conservation of keystone or endangered species, but acquiring it is usually slow, laborious and costly. Automated acoustic monitoring offers a scalable alternative to manual surveys but identifying species vocalisations requires large manually annotated training datasets, and is not always possible (e.g. for lesser studied or silent species). A new approach is needed that rapidly predicts species occurrence using smaller and more coarsely labelled audio datasets. We investigated whether local soundscapes could be used to infer the presence of 32 avifaunal and seven herpetofaunal species in 20 min recordings across a tropical forest degradation gradient in Sabah, Malaysia. Using acoustic features derived from a convolutional neural network (CNN), we characterised species indicative soundscapes by training our models on a temporally coarse labelled point-count dataset. Soundscapes successfully predicted the occurrence of 34 out of the 39 species across the two taxonomic groups, with area under the curve (AUC) metrics from 0.53 up to 0.87. The highest accuracies were achieved for species with strong temporal occurrence patterns. Soundscapes were a better predictor of species occurrence than above-ground carbon density – a metric often used to quantify habitat quality across forest degradation gradients. Our results demonstrate that soundscapes can be used to efficiently predict the occurrence of a wide variety of species and provide a new direction for data driven large-scale assessments of habitat suitability

Limits to the accurate and generalizable use of soundscapes to monitor biodiversity

Although eco-acoustic monitoring has the potential to deliver biodiversity insight on vast scales, existing analytical approaches behave unpredictably across studies. We collated 8,023 audio recordings with paired manual avifaunal point counts to investigate whether soundscapes could be used to monitor biodiversity across diverse ecosystems. We found that neither univariate indices nor machine learning models were predictive of species richness across datasets but soundscape change was consistently indicative of community change. Our findings indicate that there are no common features of biodiverse soundscapes and that soundscape monitoring should be used cautiously and in conjunction with more reliable in-person ecological surveys

A Microscope Automated Fluidic System to Study Bacterial Processes in Real Time

Most time lapse microscopy experiments studying bacterial processes ie growth, progression through the cell cycle and motility have been performed on thin nutrient agar pads. An important limitation of this approach is that dynamic perturbations of the experimental conditions cannot be easily performed. In eukaryotic cell biology, fluidic approaches have been largely used to study the impact of rapid environmental perturbations on live cells and in real time. However, all these approaches are not easily applicable to bacterial cells because the substrata are in all cases specific and also because microfluidics nanotechnology requires a complex lithography for the study of micrometer sized bacterial cells. In fact, in many cases agar is the experimental solid substratum on which bacteria can move or even grow. For these reasons, we designed a novel hybrid micro fluidic device that combines a thin agar pad and a custom flow chamber. By studying several examples, we show that this system allows real time analysis of a broad array of biological processes such as growth, development and motility. Thus, the flow chamber system will be an essential tool to study any process that take place on an agar surface at the single cell level

Biologic Phenotyping of the Human Small Airway Epithelial Response to Cigarette Smoking

BACKGROUND: The first changes associated with smoking are in the small airway epithelium (SAE). Given that smoking alters SAE gene expression, but only a fraction of smokers develop chronic obstructive pulmonary disease (COPD), we hypothesized that assessment of SAE genome-wide gene expression would permit biologic phenotyping of the smoking response, and that a subset of healthy smokers would have a "COPD-like" SAE transcriptome. METHODOLOGY/PRINCIPAL FINDINGS: SAE (10th-12th generation) was obtained via bronchoscopy of healthy nonsmokers, healthy smokers and COPD smokers and microarray analysis was used to identify differentially expressed genes. Individual responsiveness to smoking was quantified with an index representing the % of smoking-responsive genes abnormally expressed (I(SAE)), with healthy smokers grouped into "high" and "low" responders based on the proportion of smoking-responsive genes up- or down-regulated in each smoker. Smokers demonstrated significant variability in SAE transcriptome with I(SAE) ranging from 2.9 to 51.5%. While the SAE transcriptome of "low" responder healthy smokers differed from both "high" responders and smokers with COPD, the transcriptome of the "high" responder healthy smokers was indistinguishable from COPD smokers. CONCLUSION/SIGNIFICANCE: The SAE transcriptome can be used to classify clinically healthy smokers into subgroups with lesser and greater responses to cigarette smoking, even though these subgroups are indistinguishable by clinical criteria. This identifies a group of smokers with a "COPD-like" SAE transcriptome

Microenvironmental Influence on Pre-Clinical Activity of Polo-Like Kinase Inhibition in Multiple Myeloma: Implications for Clinical Translation

Polo-like kinases (PLKs) play an important role in cell cycle progression, checkpoint control and mitosis. The high mitotic index and chromosomal instability of advanced cancers suggest that PLK inhibitors may be an attractive therapeutic option for presently incurable advanced neoplasias with systemic involvement, such as multiple myeloma (MM). We studied the PLK 1, 2, 3 inhibitor BI 2536 and observed potent (IC50<40 nM) and rapid (commitment to cell death <24 hrs) in vitro activity against MM cells in isolation, as well as in vivo activity against a traditional subcutaneous xenograft mouse model. Tumor cells in MM patients, however, don't exist in isolation, but reside in and interact with the bone microenvironment. Therefore conventional in vitro and in vivo preclinical assays don't take into account how interactions between MM cells and the bone microenvironment can potentially confer drug resistance. To probe this question, we performed tumor cell compartment-specific bioluminescence imaging assays to compare the preclinical anti-MM activity of BI 2536 in vitro in the presence vs. absence of stromal cells or osteoclasts. We observed that the presence of these bone marrow non-malignant cells led to decreased anti-MM activity of BI 2536. We further validated these results in an orthotopic in vivo mouse model of diffuse MM bone lesions where tumor cells interact with non-malignant cells of the bone microenvironment. We again observed that BI 2536 had decreased activity in this in vivo model of tumor-bone microenvironment interactions highlighting that, despite BI 2536's promising activity in conventional assays, its lack of activity in microenvironmental models raises concerns for its clinical development for MM. More broadly, preclinical drug testing in the absence of relevant tumor microenvironment interactions may overestimate potential clinical activity, thus explaining at least in part the gap between preclinical vs. clinical efficacy in MM and other cancers

Neuronal MicroRNA Deregulation in Response to Alzheimer's Disease Amyloid-β

Normal brain development and function depends on microRNA (miRNA) networks to fine tune the balance between the transcriptome and proteome of the cell. These small non-coding RNA regulators are highly enriched in brain where they play key roles in neuronal development, plasticity and disease. In neurodegenerative disorders such as Alzheimer's disease (AD), brain miRNA profiles are altered; thus miRNA dysfunction could be both a cause and a consequence of disease. Our study dissects the complexity of human AD pathology, and addresses the hypothesis that amyloid-β (Aβ) itself, a known causative factor of AD, causes neuronal miRNA deregulation, which could contribute to the pathomechanisms of AD. We used sensitive TaqMan low density miRNA arrays (TLDA) on murine primary hippocampal cultures to show that about half of all miRNAs tested were down-regulated in response to Aβ peptides. Time-course assays of neuronal Aβ treatments show that Aβ is in fact a powerful regulator of miRNA levels as the response of certain mature miRNAs is extremely rapid. Bioinformatic analysis predicts that the deregulated miRNAs are likely to affect target genes present in prominent neuronal pathways known to be disrupted in AD. Remarkably, we also found that the miRNA deregulation in hippocampal cultures was paralleled in vivo by a deregulation in the hippocampus of Aβ42-depositing APP23 mice, at the onset of Aβ plaque formation. In addition, the miRNA deregulation in hippocampal cultures and APP23 hippocampus overlaps with those obtained in human AD studies. Taken together, our findings suggest that neuronal miRNA deregulation in response to an insult by Aβ may be an important factor contributing to the cascade of events leading to AD

Quantifying Intramolecular Binding in Multivalent Interactions: A Structure-Based Synergistic Study on Grb2-Sos1 Complex

Numerous signaling proteins use multivalent binding to increase the specificity and affinity of their interactions within the cell. Enhancement arises because the effective binding constant for multivalent binding is larger than the binding constants for each individual interaction. We seek to gain both qualitative and quantitative understanding of the multivalent interactions of an adaptor protein, growth factor receptor bound protein-2 (Grb2), containing two SH3 domains interacting with the nucleotide exchange factor son-of-sevenless 1 (Sos1) containing multiple polyproline motifs separated by flexible unstructured regions. Grb2 mediates the recruitment of Sos1 from the cytosol to the plasma membrane where it activates Ras by inducing the exchange of GDP for GTP. First, using a combination of evolutionary information and binding energy calculations, we predict an additional polyproline motif in Sos1 that binds to the SH3 domains of Grb2. This gives rise to a total of five polyproline motifs in Sos1 that are capable of binding to the two SH3 domains of Grb2. Then, using a hybrid method combining molecular dynamics simulations and polymer models, we estimate the enhancement in local concentration of a polyproline motif on Sos1 near an unbound SH3 domain of Grb2 when its other SH3 domain is bound to a different polyproline motif on Sos1. We show that the local concentration of the Sos1 motifs that a Grb2 SH3 domain experiences is approximately 1000 times greater than the cellular concentration of Sos1. Finally, we calculate the intramolecular equilibrium constants for the crosslinking of Grb2 on Sos1 and use thermodynamic modeling to calculate the stoichiometry. With these equilibrium constants, we are able to predict the distribution of complexes that form at physiological concentrations. We believe this is the first systematic analysis that combines sequence, structure, and thermodynamic analyses to determine the stoichiometry of the complexes that are dominant in the cellular environment

Differential Glucose-Regulation of MicroRNAs in Pancreatic Islets of Non-Obese Type 2 Diabetes Model Goto-Kakizaki Rat

The Goto-Kakizaki (GK) rat is a well-studied non-obese spontaneous type 2 diabetes (T2D) animal model characterized by impaired glucose-stimulated insulin secretion (GSIS) in the pancreatic beta cells. MicroRNAs (miRNAs) are short regulatory RNAs involved in many fundamental biological processes. We aim to identify miRNAs that are differentially-expressed in the pancreatic islets of the GK rats and investigate both their short- and long term glucose-dependence during glucose-stimulatory conditions