Diagnostic criteria and tumor screening for individuals with isolated hemihyperplasia

Isolated hemihyperplasia, formerly termed isolated hemihypertrophy, is a congenital overgrowth disorder associated with an increased risk for embryonal tumors, mainly Wilms tumor and hepatoblastoma. This practice guideline will set forth the diagnostic criteria and tumor screening recommendations for children with isolated hemihyperplasia, based on the best information available. There is clinical overlap between isolated hemihyperplasia with Beckwith-Wiedemann syndrome. The majority of Beckwith-Wiedemann syndrome patients have a molecular abnormality involving the imprinted cluster of genes at 11p15.5. In contrast, the preponderance of isolated hemihyperplasia patients studied have no identified etiology. Tumors have developed in isolated hemihyperplasia patients with and without molecular abnormalities. For this reason, molecular diagnostics are not helpful in identifying the subset of isolated hemihyperplasia patients with tumor risk and all isolated hemihyperplasia patients should undergo tumor screening

Perceptions of, and reactions to, environmental heat: a brief note on issues of concern in relation to occupational health

Average temperatures around the world are already increasing, and climate change projections suggest that global mean temperatures will continue to rise. As the effects, and projected effects, of climate change are becoming clearer, it is more apparent that the health effects of heat exposure will need further investigation. The risks associated with heat exposure are especially relevant to understandings of occupational health for people involved in labouring or agricultural work in low-income countries. This review is a partial look at the ways in which issues surrounding heat exposure and occupational health have been treated in some of the available literature. This literature focuses on military-related medical understandings of heat exposure as well as heat exposure in working environments. The ways that these issues have been treated throughout the literature reflect the ways in which technologies of observation are intertwined with social attitudes. The effects of heat on the health of working people, as well as identification of risk groups, will require further research in order to promote prophylactic measures as well as to add to understandings of the actual and potential consequences of climatic change

ARHGEF7 (BETA-PIX) Acts as Guanine Nucleotide Exchange Factor for Leucine-Rich Repeat Kinase 2

Background: Mutations within the leucine-rich repeat kinase 2 (LRRK2) gene are a common cause of familial and sporadic Parkinson’s disease. The multidomain protein LRRK2 exhibits overall low GTPase and kinase activity in vitro. Methodology/Principal Findings: Here, we show that the rho guanine nucleotide exchange factor ARHGEF7 and the small GTPase CDC42 are interacting with LRRK2 in vitro and in vivo. GTPase activity of full-length LRRK2 increases in the presence of recombinant ARHGEF7. Interestingly, LRRK2 phosphorylates ARHGEF7 in vitro at previously unknown phosphorylation sites. We provide evidence that ARHGEF7 might act as a guanine nucleotide exchange factor for LRRK2 and that R1441C mutant LRRK2 with reduced GTP hydrolysis activity also shows reduced binding to ARHGEF7. Conclusions/Significance: Downstream effects of phosphorylation of ARHGEF7 through LRRK2 could be (i) a feedback control mechanism for LRRK2 activity as well as (ii) an impact of LRRK2 on actin cytoskeleton regulation. A newly identified familial mutation N1437S, localized within the GTPase domain of LRRK2, further underlines the importance of the GTPas

Tumor response to radiotherapy is dependent on genotype-associated mechanisms in vitro and in vivo

<p>Abstract</p> <p>Background</p> <p>We have previously shown that in vitro radiosensitivity of human tumor cells segregate non-randomly into a limited number of groups. Each group associates with a specific genotype. However we have also shown that abrogation of a single gene (p21) in a human tumor cell unexpectedly sensitized xenograft tumors comprised of these cells to radiotherapy while not affecting in vitro cellular radiosensitivity. Therefore in vitro assays alone cannot predict tumor response to radiotherapy.</p> <p>In the current work, we measure in vitro radiosensitivity and in vivo response of their xenograft tumors in a series of human tumor lines that represent the range of radiosensitivity observed in human tumor cells. We also measure response of their xenograft tumors to different radiotherapy protocols. We reduce these data into a simple analytical structure that defines the relationship between tumor response and total dose based on two coefficients that are specific to tumor cell genotype, fraction size and total dose.</p> <p>Methods</p> <p>We assayed in vitro survival patterns in eight tumor cell lines that vary in cellular radiosensitivity and genotype. We also measured response of their xenograft tumors to four radiotherapy protocols: 8 × 2 Gy; 2 × 5Gy, 1 × 7.5 Gy and 1 × 15 Gy. We analyze these data to derive coefficients that describe both in vitro and in vivo responses.</p> <p>Results</p> <p>Response of xenografts comprised of human tumor cells to different radiotherapy protocols can be reduced to only two coefficients that represent 1) total cells killed as measured in vitro 2) additional response in vivo not predicted by cell killing. These coefficients segregate with specific genotypes including those most frequently observed in human tumors in the clinic. Coefficients that describe in vitro and in vivo mechanisms can predict tumor response to any radiation protocol based on tumor cell genotype, fraction-size and total dose.</p> <p>Conclusions</p> <p>We establish an analytical structure that predicts tumor response to radiotherapy based on coefficients that represent in vitro and in vivo responses. Both coefficients are dependent on tumor cell genotype and fraction-size. We identify a novel previously unreported mechanism that sensitizes tumors in vivo; this sensitization varies with tumor cell genotype and fraction size.</p

Scenario-based requirements elicitation for user-centric explainable AI

Explainable Artificial Intelligence (XAI) develops technical explanation methods and enable interpretability for human stakeholders on why Artificial Intelligence (AI) and machine learning (ML) models provide certain predictions. However, the trust of those stakeholders into AI models and explanations is still an issue, especially domain experts, who are knowledgeable about their domain but not AI inner workings. Social and user-centric XAI research states it is essential to understand the stakeholder’s requirements to provide explanations tailored to their needs, and enhance their trust in working with AI models. Scenario-based design and requirements elicitation can help bridge the gap between social and operational aspects of a stakeholder early before the adoption of information systems and identify its real problem and practices generating user requirements. Nevertheless, it is still rarely explored the adoption of scenarios in XAI, especially in the domain of fraud detection to supporting experts who are about to work with AI models. We demonstrate the usage of scenario-based requirements elicitation for XAI in a fraud detection context, and develop scenarios derived with experts in banking fraud. We discuss how those scenarios can be adopted to identify user or expert requirements for appropriate explanations in his daily operations and to make decisions on reviewing fraudulent cases in banking. The generalizability of the scenarios for further adoption is validated through a systematic literature review in domains of XAI and visual analytics for fraud detection

SlimPLS: A Method for Feature Selection in Gene Expression-Based Disease Classification

A major challenge in biomedical studies in recent years has been the classification of gene expression profiles into categories, such as cases and controls. This is done by first training a classifier by using a labeled training set containing labeled samples from the two populations, and then using that classifier to predict the labels of new samples. Such predictions have recently been shown to improve the diagnosis and treatment selection practices for several diseases. This procedure is complicated, however, by the high dimensionality if the data. While microarrays can measure the levels of thousands of genes per sample, case-control microarray studies usually involve no more than several dozen samples. Standard classifiers do not work well in these situations where the number of features (gene expression levels measured in these microarrays) far exceeds the number of samples. Selecting only the features that are most relevant for discriminating between the two categories can help construct better classifiers, in terms of both accuracy and efficiency. In this work we developed a novel method for multivariate feature selection based on the Partial Least Squares algorithm. We compared the method's variants with common feature selection techniques across a large number of real case-control datasets, using several classifiers. We demonstrate the advantages of the method and the preferable combinations of classifier and feature selection technique

BCR-signalling synergizes with TLR-signalling for induction of AID and immunoglobulin class-switching through the non-canonical NF-κB pathway

By diversifying antibody biological effector functions, class switch DNA recombination has a central role in the maturation of the antibody response. Here we show that BCR-signalling synergizes with Toll-like receptor (TLR) signalling to induce class switch DNA recombination. BCR-signalling activates the non-canonical NF-κB pathway and enhances the TLR-dependent canonical NF-κB pathway, thereby inducing activation-induced cytidine deaminase (AID), which is critical for class switch DNA recombination. Escherichia coli lipopolysaccharide (LPS) triggers dual TLR4/BCR-signalling and induces hallmarks of BCR-signalling, including CD79a phosphorylation and Ca2+ mobilization, and activates both the NF-κB pathways to induce AID and class switch DNA recombination in a PI(3)K p85α-dependent fashion. CD40-signalling activates the two NF-κB pathways to induce AID and class switch DNA recombination independent of BCR-signalling. Finally, dual BCR/TLR-engaging NP–lipopolysaccharide effectively elicits class-switched NP-specific IgG3 and IgG2b in mice. Thus, by integrating signals of the non-canonical and canonical NF-κB pathways, BCR and TLRs synergize to induce AID and T-cell-independent class switch DNA recombination

A novel role for RecA under non-stress: promotion of swarming motility in Escherichia coli K-12

BACKGROUND: Bacterial motility is a crucial factor in the colonization of natural environments. Escherichia coli has two flagella-driven motility types: swimming and swarming. Swimming motility consists of individual cell movement in liquid medium or soft semisolid agar, whereas swarming is a coordinated cellular behaviour leading to a collective movement on semisolid surfaces. It is known that swimming motility can be influenced by several types of environmental stress. In nature, environmentally induced DNA damage (e.g. UV irradiation) is one of the most common types of stress. One of the key proteins involved in the response to DNA damage is RecA, a multifunctional protein required for maintaining genome integrity and the generation of genetic variation. RESULTS: The ability of E. coli cells to develop swarming migration on semisolid surfaces was suppressed in the absence of RecA. However, swimming motility was not affected. The swarming defect of a ΔrecA strain was fully complemented by a plasmid-borne recA gene. Although the ΔrecA cells grown on semisolidsurfaces exhibited flagellar production, they also presented impaired individual movement as well as a fully inactive collective swarming migration. Both the comparative analysis of gene expression profiles in wild-type and ΔrecA cells grown on a semisolid surface and the motility of lexA1 [Ind-] mutant cells demonstrated that the RecA effect on swarming does not require induction of the SOS response. By using a RecA-GFP fusion protein we were able to segregate the effect of RecA on swarming from its other functions. This protein fusion failed to regulate the induction of the SOS response, the recombinational DNA repair of UV-treated cells and the genetic recombination, however, it was efficient in rescuing the swarming motility defect of the ΔrecA mutant. The RecA-GFP protein retains a residual ssDNA-dependent ATPase activity but does not perform DNA strand exchange. CONCLUSION: The experimental evidence presented in this work supports a novel role for RecA: the promotion of swarming motility. The defective swarming migration of ΔrecA cells does not appear to be associated with defective flagellar production; rather, it seems to be associated with an abnormal flagellar propulsion function. Our results strongly suggest that the RecA effect on swarming motility does not require an extensive canonical RecA nucleofilament formation. RecA is the first reported cellular factor specifically affecting swarming but not swimming motility in E. coli. The integration of two apparently disconnected biologically important processes, such as the maintenance of genome integrity and motility in a unique protein, may have important evolutive consequences