Comparison of chemical and biological methods for the estimation of urinary corticoids

Abstract Not Provided

Caveat Implementor! Key Recovery Attacks on MEGA

MEGA is a large-scale cloud storage and communication platform that aims to provide end-to-end encryption for stored data. A recent analysis by Backendal, Haller and Paterson (IEEE S&P 2023) invalidated these security claims by presenting practical attacks against MEGA that could be mounted by the MEGA service provider. In response, the MEGA developers added lightweight sanity checks on the user RSA private keys used in MEGA, sufficient to prevent the previous attacks. We analyse these new sanity checks and show how they themselves can be exploited to mount novel attacks on MEGA that recover a target user’s RSA private key with only slightly higher attack complexity than the original attacks. We identify the presence of an ECB encryption oracle under a target user’s master key in the MEGA system; this oracle provides our adversary with the ability to partially overwrite a target user’s RSA private key with chosen data, a powerful capability that we use in our attacks. We then present two distinct types of attack, each type exploiting different error conditions arising in the sanity checks and in subsequent cryptographic processing during MEGA’s user authentication procedure. The first type appears to be novel and exploits the manner in which the MEGA code handles modular inversion when recomputing u = q−1 mod p. The second can be viewed as a small subgroup attack (van Oorschot and Wiener, EUROCRYPT 1996, Lim and Lee, CRYPTO 1998). We prototype the attacks and show that they work in practice. As a side contribution, we show how to improve the RSA key recovery attack of Backendal-Haller-Paterson against the unpatched version of MEGA to require only 2 logins instead of the original 512. We conclude by discussing wider lessons about secure implementation of cryptography that our work surfaces.ISSN:0302-9743ISSN:1611-334

09311 Abstracts Collection -- Classical and Quantum Information Assurance Foundations and Practice

From 26 July 2009 to 31 July 2009, the Dagstuhl Seminar 09311 ``Classical and Quantum Information Assurance Foundations and Practice\u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. The workshop was intended to explore the latest developments and discuss the open issues in the theory and practice of classical and quantum information assurance. A further goal of the workshop was to bring together practitioners from both the classical and the quantum information assurance communities. To date, with a few exceptions, these two communities seem to have existed largely separately and in a state of mutual ignorance. It is clear however that there is great potential for synergy and cross-fertilization between and this we sought to stimulate and facilitate

Acute molecular changes in synovial fluid following human knee injury: association with early clinical outcomes

Objective To investigate whether molecules found to be up-regulated within hours of surgical joint destabilization in the mouse are also elevated in the analogous human setting of acute knee injury, how this molecular response varies between individuals, and whether it is related to patient-reported outcomes in the 3 months after injury. Methods Seven candidate molecules were analyzed in blood and synovial fluid (SF) from 150 participants with recent structural knee injury at baseline (<8 weeks from injury) and in blood at 14 days and 3 months following baseline. Knee Injury and Osteoarthritis Outcome Score 4 (KOOS4) was obtained at baseline and 3 months. Patient and control samples were compared using Meso Scale Discovery platform assays or enzyme-linked immunosorbent assay. Results Six of the 7 molecules were significantly elevated in human SF immediately after injury: interleukin-6 (IL-6), monocyte chemotactic protein 1, matrix metalloproteinase 3 (MMP-3), tissue inhibitor of metalloproteinases 1 (TIMP-1), activin A, and tumor necrosis factor–stimulated gene 6 (TSG-6). There was low-to-moderate correlation with blood measurements. Three of the 6 molecules were significantly associated with baseline KOOS4 (those with higher SF IL-6, TIMP-1, or TSG-6 had lower KOOS4). These 3 molecules, MMP-3, and activin A were all significantly associated with greater improvement in KOOS4 over 3 months, after adjustment for other relevant factors. Of these, IL-6 alone significantly accounted for the molecular contribution to baseline KOOS4 and change in KOOS4 over 3 months. Conclusion Our findings validate relevant human biomarkers of tissue injury identified in a mouse model. Analysis of SF rather than blood more accurately reflects this response. The response is associated with patient-reported outcomes over this early period, with SF IL-6 acting as a single representative marker. Longitudinal outcomes will determine if these molecules are biomarkers of subsequent disease risk

Near infrared spectroscopy of superficial and deep rectus femoris reveals markedly different exercise response to superficial vastus lateralis

To date our knowledge of skeletal muscle deoxygenation as measured by near-infrared spectroscopy (NIRS) is predicated almost exclusively on sampling of superficial muscle(s), most commonly the vastus lateralis (VL-s). Recently developed high power NIRS facilitates simultaneous sampling of deep (i.e., rectus femoris, RF-d) and superficial muscles of RF (RF-s) and VL-s. Because deeper muscle is more oxidative with greater capillarity and sustains higher blood flows than superficial muscle, we used time-resolved NIRS to test the hypotheses that, following exercise onset, the RF-d has slower deoxy[Hb+Mb] kinetics with reduced amplitude than superficial muscles. Thirteen participants performed cycle exercise transitions from unloaded to heavy work rates. Within the same muscle (RF-s vs. RF-d) deoxy[Hb+Mb] kinetics (mean response time, MRT) and amplitudes were not different. However, compared with the kinetics of VL-s, deoxy[Hb+Mb] of RF-s and RF-d were slower (MRT: RF-s, 51 ± 23; RF-d, 55 ± 29; VL-s, 18 ± 6 s; P MRT-on (P<0.05). Collectively these data reveal profoundly different O₂ transport strategies, with the RF-s and RF-d relying proportionately more on elevated perfusive and the VL-s on diffusive O₂ transport. These disparate O₂ transport strategies and their temporal profiles across muscles have previously been concealed within the “global” pulmonary VO₂ response

A novel mGluR5 antagonist, MFZ 10-7, inhibits cocaine-taking and cocaine-seeking behavior in rats

Pre-clinical studies suggest that negative allosteric modulators (NAMs) of the metabotropic glutamate receptor subtype 5 (mGluR5), including 2-methyl-6-(phenylethynyl)pyridine (MPEP), 3-[(2-methyl-1,3-thiazol-4-yl)ethynyl]pyridine (MTEP) and fenobam are highly effective in attenuating drug-taking and drug-seeking behaviors. However, both MPEP and MTEP have no translational potential for use in humans because of their off-target effects and short half-lives. Here, we report that 3-fluoro-5-[(6-methylpyridin-2-yl)ethynyl]benzonitrile (MFZ 10-7), a novel mGluR5 NAM, is more potent and selective than MPEP, MTEP and fenobam in both in vitro binding and functional assays. Similar to MTEP, intraperitoneal administration of MFZ 10-7 inhibited intravenous cocaine self-administration, cocaine-induced reinstatement of drug-seeking behavior and cocaine-associated cue-induced cocaine-seeking behavior in rats. Although MFZ 10-7 and MTEP lowered the rate of oral sucrose self-administration, they did not alter total sucrose intake. Further, MFZ 10-7 appeared to be more potent than MTEP in inducing downward shifts in the cocaine dose–response curve, but less effective than MTEP in attenuating sucrose-induced reinstatement of sucrose-seeking behavior. MFZ 10-7 and MTEP had no effect on basal locomotor behavior. These findings not only provide additional evidence supporting an important role for mGluR5 in cocaine reward and addiction, but also introduce a new tool for both in vitro and in vivo investigations with which to further characterize this role

Nicotinic acetylcholine receptor β2 subunit gene implicated in a systems-based candidate gene study of smoking cessation

Although the efficacy of pharmacotherapy for tobacco dependence has been previously demonstrated, there is substantial variability among individuals in treatment response. We performed a systems-based candidate gene study of 1295 single nucleotide polymorphisms (SNPs) in 58 genes within the neuronal nicotinic receptor and dopamine systems to investigate their role in smoking cessation in a bupropion placebo-controlled randomized clinical trial. Putative functional variants were supplemented with tagSNPs within each gene. We used global tests of main effects and treatment interactions, adjusting the P-values for multiple correlated tests. An SNP (rs2072661) in the 3′ UTR region of the β2 nicotinic acetylcholine receptor subunit (CHRNB2) has an impact on abstinence rates at the end of treatment (adjusted P = 0.01) and after a 6-month follow-up period (adjusted P = 0.0002). This latter P-value is also significant with adjustment for the number of genes tested. Independent of treatment at 6-month follow-up, individuals carrying the minor allele have substantially decreased the odds of quitting (OR = 0.31; 95% CI 0.18–0.55). Effect of estimates indicate that the treatment is more effective for individuals with the wild-type (OR = 2.14, 95% CI 1.20–3.81) compared with individuals carrying the minor allele (OR = 0.83, 95% CI 0.32–2.19), although this difference is only suggestive (P = 0.10). Furthermore, this SNP demonstrated a role in the time to relapse (P = 0.0002) and an impact on withdrawal symptoms at target quit date (TQD) (P = 0.0009). Overall, while our results indicate strong evidence for CHRNB2 in ability to quit smoking, these results require replication in an independent sample

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences

Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial intelligence with rich microbiome datasets can offer an improved understanding of the microbiome’s role in human health. To gain actionable insights it is essential to consider both the predictive power and the transparency of the models by providing explanations for the predictions. We combine the collection of leg skin microbiome samples from two healthy cohorts of women with the application of an explainable artificial intelligence (EAI) approach that provides accurate predictions of phenotypes with explanations. The explanations are expressed in terms of variations in the relative abundance of key microbes that drive the predictions. We predict skin hydration, subject's age, pre/post-menopausal status and smoking status from the leg skin microbiome. The changes in microbial composition linked to skin hydration can accelerate the development of personalized treatments for healthy skin, while those associated with age may offer insights into the skin aging process. The leg microbiome signatures associated with smoking and menopausal status are consistent with previous findings from oral/respiratory tract microbiomes and vaginal/gut microbiomes respectively. This suggests that easily accessible microbiome samples could be used to investigate health-related phenotypes, offering potential for non-invasive diagnosis and condition monitoring. Our EAI approach sets the stage for new work focused on understanding the complex relationships between microbial communities and phenotypes. Our approach can be applied to predict any condition from microbiome samples and has the potential to accelerate the development of microbiome-based personalized therapeutics and non-invasive diagnostics