Simultaneous quantification of 12 different nucleotides and nucleosides released from renal epithelium and in human urine samples using ion-pair reversed-phase HPLC

Nucleotides and nucleosides are not only involved in cellular metabolism but also act extracellularly via P1 and P2 receptors, to elicit a wide variety of physiological and pathophysiological responses through paracrine and autocrine signalling pathways. For the first time, we have used an ion-pair reversed-phase high-performance liquid chromatography ultraviolet (UV)-coupled method to rapidly and simultaneously quantify 12 different nucleotides and nucleosides (adenosine triphosphate, adenosine diphosphate, adenosine monophosphate, adenosine, uridine triphosphate, uridine diphosphate, uridine monophosphate, uridine, guanosine triphosphate, guanosine diphosphate, guanosine monophosphate, guanosine): (1) released from a mouse renal cell line (M1 cortical collecting duct) and (2) in human biological samples (i.e., urine). To facilitate analysis of urine samples, a solid-phase extraction step was incorporated (overall recovery rate ? 98 %). All samples were analyzed following injection (100 ?l) into a Synergi Polar-RP 80 Å (250 × 4.6 mm) reversed-phase column with a particle size of 10 ?m, protected with a guard column. A gradient elution profile was run with a mobile phase (phosphate buffer plus ion-pairing agent tetrabutylammonium hydrogen sulfate; pH 6) in 2-30 % acetonitrile (v/v) for 35 min (including equilibration time) at 1 ml min(-1) flow rate. Eluted compounds were detected by UV absorbance at 254 nm and quantified using standard curves for nucleotide and nucleoside mixtures of known concentration. Following validation (specificity, linearity, limits of detection and quantitation, system precision, accuracy, and intermediate precision parameters), this protocol was successfully and reproducibly used to quantify picomolar to nanomolar concentrations of nucleosides and nucleotides in isotonic and hypotonic cell buffers that transiently bathed M1 cells, and urine samples from normal subjects and overactive bladder patients

Comparing three short questionnaires to detect psychosocial dysfunction among primary school children: a randomized method

BACKGROUND: Good questionnaires are essential to support the early identification of children with psychosocial dysfunction in community based settings. Our aim was to assess which of three short questionnaires was most suitable for this identification among school-aged children METHODS: A community-based sample of 2,066 parents of children aged 7-12 years (85% of those eligible) filled out the Child Behavior Checklist (CBCL) and - randomly determined - one of three questionnaires to be compared: the Strengths and Difficulties Questionnaire with Impact Supplement (SDQ), the Pediatric Symptom Checklist (PSC) and the PSYBOBA, a Dutch-origin questionnaire. Preventive Child Healthcare professionals assessed children's psychosocial functioning during routine health examinations. We assessed the scale structure (by means of Structural Equation Modelling), validity (correlation coefficients, sensitivity and specificity) and usability (ratings by parents and professionals) of each questionnaire and the degree to which they could improve the identification based only on clinical assessment (logistic regression). RESULTS: For the three questionnaires, Cronbach's alphas varied between 0.80 and 0.89. Sensitivities for a clinical CBCL at a cut off point with specificity = 0.90 varied between 0.78 and 0.86 for the three questionnaires. Areas under the Receiver Operating Curve, using the CBCL as criterion, varied between 0.93 and 0.96. No differences were statistically significant. All three questionnaires added information to the clinical assessment. Odds ratios (95% confidence intervals) for added information were PSC: 29.3 (14.4-59.8), SDQ: 55.0 (23.1-131.2) and PSYBOBA: 68.5 (28.3-165.6). Parents preferred the SDQ and PSYBOBA. Preventive Child Health Care professionals preferred the SDQ. CONCLUSIONS: This randomized comparison of three questionnaires shows that each of the three questionnaires can improve the detection of psychosocial dysfunction among children substantially

Assessing childhood maltreatment and mental health correlates of disordered eating profiles in a nationally representative sample of English females

PURPOSE: Previous research suggests that childhood maltreatment is associated with the onset of eating disorders (ED). In turn, EDs are associated with alternative psychopathologies such as depression and posttraumatic stress disorder (PTSD), and with suicidality. Moreover, it has been reported that various ED profiles may exist. The aim of the current study was to examine the profiles of disordered eating and the associations of these with childhood maltreatment and with mental health psychopathology. METHODS: The current study utilised a representative sample of English females (N = 4206) and assessed for the presence of disordered eating profiles using Latent Class Analysis. Multinomial logistic regression was implemented to examine the associations of childhood sexual and physical abuse with the disordered eating profiles and the associations of these with PTSD, depression and suicidality. RESULTS: Results supported those of previous findings in that we found five latent classes of which three were regarded as disordered eating classes. Significant relationships were found between these and measures of childhood trauma and mental health outcomes. CONCLUSIONS: Childhood sexual and physical abuse increased the likelihood of membership in disordered eating classes and these in turn increased the likelihood of adverse mental health and suicidal outcomes

A Coevolutionary Residue Network at the Site of a Functionally Important Conformational Change in a Phosphohexomutase Enzyme Family

Coevolution analyses identify residues that co-vary with each other during evolution, revealing sequence relationships unobservable from traditional multiple sequence alignments. Here we describe a coevolutionary analysis of phosphomannomutase/phosphoglucomutase (PMM/PGM), a widespread and diverse enzyme family involved in carbohydrate biosynthesis. Mutual information and graph theory were utilized to identify a network of highly connected residues with high significance. An examination of the most tightly connected regions of the coevolutionary network reveals that most of the involved residues are localized near an interdomain interface of this enzyme, known to be the site of a functionally important conformational change. The roles of four interface residues found in this network were examined via site-directed mutagenesis and kinetic characterization. For three of these residues, mutation to alanine reduces enzyme specificity to ∼10% or less of wild-type, while the other has ∼45% activity of wild-type enzyme. An additional mutant of an interface residue that is not densely connected in the coevolutionary network was also characterized, and shows no change in activity relative to wild-type enzyme. The results of these studies are interpreted in the context of structural and functional data on PMM/PGM. Together, they demonstrate that a network of coevolving residues links the highly conserved active site with the interdomain conformational change necessary for the multi-step catalytic reaction. This work adds to our understanding of the functional roles of coevolving residue networks, and has implications for the definition of catalytically important residues

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Background: Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Results: Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Conclusions: Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Figure not available: see fulltext. © 2015 Freitas et al.; licensee Springer

Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study

BACKGROUND: A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. METHODS: Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening. RESULTS: About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95–100) to 100% and specificity from 99% (95% CI 97–100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76–87) to 94% (95% CI 89–98) and specificity ranging from 76% (95% CI 70–82) to 92% (95% CI 88–96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only. CONCLUSIONS: People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people. Trial Registration NCT04509713 (clinicaltrials.gov)

Role of Hsp70 ATPase Domain Intrinsic Dynamics and Sequence Evolution in Enabling its Functional Interactions with NEFs

Catalysis of ADP-ATP exchange by nucleotide exchange factors (NEFs) is central to the activity of Hsp70 molecular chaperones. Yet, the mechanism of interaction of this family of chaperones with NEFs is not well understood in the context of the sequence evolution and structural dynamics of Hsp70 ATPase domains. We studied the interactions of Hsp70 ATPase domains with four different NEFs on the basis of the evolutionary trace and co-evolution of the ATPase domain sequence, combined with elastic network modeling of the collective dynamics of the complexes. Our study reveals a subtle balance between the intrinsic (to the ATPase domain) and specific (to interactions with NEFs) mechanisms shared by the four complexes. Two classes of key residues are distinguished in the Hsp70 ATPase domain: (i) highly conserved residues, involved in nucleotide binding, which mediate, via a global hinge-bending, the ATPase domain opening irrespective of NEF binding, and (ii) not-conserved but co-evolved and highly mobile residues, engaged in specific interactions with NEFs (e.g., N57, R258, R262, E283, D285). The observed interplay between these respective intrinsic (pre-existing, structure-encoded) and specific (co-evolved, sequence-dependent) interactions provides us with insights into the allosteric dynamics and functional evolution of the modular Hsp70 ATPase domain