Risk-Averse Matchings over Uncertain Graph Databases

A large number of applications such as querying sensor networks, and analyzing protein-protein interaction (PPI) networks, rely on mining uncertain graph and hypergraph databases. In this work we study the following problem: given an uncertain, weighted (hyper)graph, how can we efficiently find a (hyper)matching with high expected reward, and low risk? This problem naturally arises in the context of several important applications, such as online dating, kidney exchanges, and team formation. We introduce a novel formulation for finding matchings with maximum expected reward and bounded risk under a general model of uncertain weighted (hyper)graphs that we introduce in this work. Our model generalizes probabilistic models used in prior work, and captures both continuous and discrete probability distributions, thus allowing to handle privacy related applications that inject appropriately distributed noise to (hyper)edge weights. Given that our optimization problem is NP-hard, we turn our attention to designing efficient approximation algorithms. For the case of uncertain weighted graphs, we provide a $\frac{1}{3}$-approximation algorithm, and a $\frac{1}{5}$-approximation algorithm with near optimal run time. For the case of uncertain weighted hypergraphs, we provide a $\Omega(\frac{1}{k})$-approximation algorithm, where $k$ is the rank of the hypergraph (i.e., any hyperedge includes at most $k$ nodes), that runs in almost (modulo log factors) linear time. We complement our theoretical results by testing our approximation algorithms on a wide variety of synthetic experiments, where we observe in a controlled setting interesting findings on the trade-off between reward, and risk. We also provide an application of our formulation for providing recommendations of teams that are likely to collaborate, and have high impact.Comment: 25 page

Towards causal benchmarking of bias in face analysis algorithms

Measuring algorithmic bias is crucial both to assess algorithmic fairness, and to guide the improvement of algorithms. Current methods to measure algorithmic bias in computer vision, which are based on observational datasets, are inadequate for this task because they conflate algorithmic bias with dataset bias. To address this problem we develop an experimental method for measuring algorithmic bias of face analysis algorithms, which manipulates directly the attributes of interest, e.g., gender and skin tone, in order to reveal causal links between attribute variation and performance change. Our proposed method is based on generating synthetic ``transects'' of matched sample images that are designed to differ along specific attributes while leaving other attributes constant. A crucial aspect of our approach is relying on the perception of human observers, both to guide manipulations, and to measure algorithmic bias. Besides allowing the measurement of algorithmic bias, synthetic transects have other advantages with respect to observational datasets: they sample attributes more evenly allowing for more straightforward bias analysis on minority and intersectional groups, they enable prediction of bias in new scenarios, they greatly reduce ethical and legal challenges, and they are economical and fast to obtain, helping make bias testing affordable and widely available. We validate our method by comparing it to a study that employs the traditional observational method for analyzing bias in gender classification algorithms. The two methods reach different conclusions. While the observational method reports gender and skin color biases, the experimental method reveals biases due to gender, hair length, age, and facial hair

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

Trabecular bone volume and osteoprotegerin expression in uremic rats given high calcium

Calcium (Ca)-containing phosphate binders have been recommended for the treatment of hyperphosphatemia in children with chronic kidney disease. To study the effects of high Ca levels on trabecular bone volume (BV) and osteoprotegerin (OPG) expression in uremic young rats, a model of marked overcorrection of secondary hyperparathyroidism was created by providing a diet of high Ca to 5/6 nephrectomized young rats (Nx-Ca) for 4 weeks. The results of chondrocyte proliferation and apoptosis, osteoclastic activity, OPG expression and BV were compared among intact rats given the control diet, intact rats given a high Ca diet and 5/6 nephrectomized rats given the control diet (Nx-Control) and the high Ca diet (Nx-Ca). Ionized Ca levels were higher and parathyroid hormone levels were lower in Nx-Ca rats than in the other groups. Final weight, final length and final tibial length of Nx-Ca rats were significantly less than those of the other groups, although the length gain did not differ among the groups. The hypertrophic zone width was markedly enlarged in Nx-Ca rats. Chondrocyte proliferation rates did not differ among the groups, whereas osteoclastic activity was decreased in Nx-Ca rats compared with the Nx-Control animals. The OPG expression and BV were increased in Nx-Ca rats compared with the Nx-Control rats. Increased BV should improve bone strength, whereas disturbance of osteoclastogenesis interferes with bone remodeling. Bone quality has yet to be determined in high Ca-fed uremic young rats

Primary hyperparathyroidism diagnosed after surgical ablation of a costal mass mistaken for giant-cell bone tumor: a case report

<p>Abstract</p> <p>Introduction</p> <p>Primary hyperparathyroidism is a common endocrine disorder characterized by elevated parathyroid hormone levels, which cause continuous osteoclastic bone resorption. Giant cell tumor of bone is an expansile osteolytic tumor that contains numerous osteoclast-like giant cells. There are many similarities in the radiological and histological features of giant cell tumor of bone and brown tumor. This is a rare benign focal osteolytic process most commonly caused by hyperparathyroidism.</p> <p>Case presentation</p> <p>We report the unusual case of a 40-year-old Caucasian woman in which primary hyperparathyroidism was diagnosed after surgical ablation of a costal mass. The mass was suspected of being neoplastic and histopathology was compatible with a giant cell tumor of bone. On the basis of the biochemical results (including serum calcium, phosphorous and intact parathyroid hormone levels) primary hyperparathyroidism was suspected and a brown tumor secondary to refractory hyperparathyroidism was diagnosed.</p> <p>Conclusions</p> <p>Since giant cell tumor is a bone neoplasm that has major implications for the patient, the standard laboratory tests in patients with bone lesions are important for a correct diagnosis.</p

Sustained Oscillations of NF-κB Produce Distinct Genome Scanning and Gene Expression Profiles

NF-κB is a prototypic stress-responsive transcription factor that acts within a complex regulatory network. The signaling dynamics of endogenous NF-κB in single cells remain poorly understood. To examine real time dynamics in living cells, we monitored NF-κB activities at multiple timescales using GFP-p65 knock-in mouse embryonic fibroblasts. Oscillations in NF-κB were sustained in most cells, with several cycles of transient nuclear translocation after TNF-α stimulation. Mathematical modeling suggests that NF-κB oscillations are selected over other non-oscillatory dynamics by fine-tuning the relative strengths of feedback loops like IκBα. The ability of NF-κB to scan and interact with the genome in vivo remained remarkably constant from early to late cycles, as observed by fluorescence recovery after photobleaching (FRAP). Perturbation of long-term NF-κB oscillations interfered with its short-term interaction with chromatin and balanced transcriptional output, as predicted by the mathematical model. We propose that negative feedback loops do not simply terminate signaling, but rather promote oscillations of NF-κB in the nucleus, and these oscillations are functionally advantageous

Comparison of the Gene Expression Profiles from Normal and Fgfrl1 Deficient Mouse Kidneys Reveals Downstream Targets of Fgfrl1 Signaling

Fgfrl1 (fibroblast growth factor receptor-like 1) is a transmembrane receptor that is essential for the development of the metanephric kidney. It is expressed in all nascent nephrogenic structures and in the ureteric bud. Fgfrl1 null mice fail to develop the metanephric kidneys. Mutant kidney rudiments show a dramatic reduction of ureteric branching and a lack of mesenchymal-to-epithelial transition. Here, we compared the expression profiles of wildtype and Fgfrl1 mutant kidneys to identify genes that act downstream of Fgfrl1 signaling during the early steps of nephron formation. We detected 56 differentially expressed transcripts with 2-fold or greater reduction, among them many genes involved in Fgf, Wnt, Bmp, Notch, and Six/Eya/Dach signaling. We validated the microarray data by qPCR and whole-mount in situ hybridization and showed the expression pattern of candidate genes in normal kidneys. Some of these genes might play an important role during early nephron formation. Our study should help to define the minimal set of genes that is required to form a functional nephron

Diversity and abundance of solitary and primitively eusocial bees in an urban centre: a case study from Northampton (England)

The apparent reduction of solitary and primitively eusocial bees populations has remained a huge concern over the past few decades and urbanisation is considered as one of the factors affecting bees at different scales depending on bee guild. As urbanisation is increasing globally it necessitates more research to understand the complex community dynamics of solitary and primitively eusocial bees in urban settings. We investigated the urban core of a British town for diversity and abundance of solitary bees using standardized methods, and compared the results with nearby meadows and nature reserves. The study recorded 48 species within the town, about 22 % of the total species and 58 % of the genera of solitary bees in the United Kingdom. Furthermore we found the urban core to be more diverse and abundant in solitary and primitively eusocial bees compared to the meadows and nature re-serves. Of particular note was an urban record of the nationally rare Red Data Book species Coelioxys quadridentata and its host Anthophora quadrimaculata. This research demonstrates that urban settings can contribute significantly to the conservation of solitary and primitively eusocial bees in Britain

Retinoic Acid Increases Proliferation of Human Osteoclast Progenitors and Inhibits RANKL-Stimulated Osteoclast Differentiation by Suppressing RANK

It has been shown that high vitamin A intake is associated with bone fragility and fractures in both animals and humans. However, the mechanism by which vitamin A affects bones is unclear. In the present study, the direct effects of retinoic acid (RA) on human and murine osteoclastogenesis were evaluated using cultured peripheral blood CD14+ monocytes and RAW264.7 cells. Both the activity of the osteoclast marker tartrate resistant acid phosphatase (TRAP) in culture supernatant and the expression of the genes involved in osteoclast differentiation together with bone resorption were measured. To our knowledge, this is the first time that the effects of RA on human osteoclast progenitors and mature osteoclasts have been studied in vitro. RA stimulated proliferation of osteoclast progenitors both from humans and mice. In contrast, RA inhibited differentiation of the receptor activator of nuclear factor κB ligand (RANKL)-induced osteoclastogenesis of human and murine osteoclast progenitors via retinoic acid receptors (RARs). We also show that the mRNA levels of receptor activator of nuclear factor κB (RANK), the key initiating factor and osteoclast associated receptor for RANKL, were potently suppressed by RA in osteoclast progenitors. More importantly, RA abolished the RANK protein in osteoclast progenitors. This inhibition could be partially reversed by a RAR pan-antagonist. Furthermore, RA treatment suppressed the expression of the transcription factor nuclear factor of activated T-cells cytoplasmic 1 (NFATc1) and increased the expression of interferon regulatory factor-8 (IRF-8) in osteoclast progenitors via RARs. Also, RA demonstrated differential effects depending on the material supporting the cell culture. RA did not affect TRAP activity in the culture supernatant in the bone slice culture system, but inhibited the release of TRAP activity if cells were cultured on plastic. In conclusion, our results suggest that retinoic acid increases proliferation of human osteoclast progenitors and that it inhibits RANK-stimulated osteoclast differentiation by suppressing RANK