Protein binding affinity prediction using support vector regression and interfecial features

In understanding biology at the molecular level, analysis of protein interactions and protein binding affinity is a challenge. It is an important problem in computational and structural biology. Experimental measurement of binding affinity in the wet-lab is expensive and time consuming. Therefore, machine learning approaches are widely used to predict protein interactions and binding affinities by learning from specific properties of existing complexes. In this work, we propose an innovative computational model to predict binding affinities and interaction based on sequence, structural and interface features of the interacting proteins that are robust to binding associated conformational changes. We modeled the prediction of binding affinity as classification and regression problem with least-squared and support vector regression models using structure and sequence features of proteins. Specifically, we have used the number and composition of interacting residues at protein complexes interface as features and sequence features. We evaluated the performance of our prediction models using Affinity Benchmark Dataset version 2.0 which contains a diverse set of both bound and unbound protein complex structures with known binding affinities. We evaluated our regression performance results with root mean square error (RMSE) as well as Spearman and Pearson's correlation coefficients using a leave-one-out cross-validation protocol. We evaluate classification results with AUC-ROC and AUC-PR Our results show that Support Vector Regression performs significantly better than other models with a Spearman Correlation coefficient of 0.58, Pearson Correlation score of 0.55 and RMSE of 2.41 using 3-mer and sequence feature. It is interesting to note that simple features based on 3-mer features and the properties of the interface of a protein complex are predictive of its binding affinity. These features, together with support vector regression achieve higher accuracy than existing sequence based methods

Images depicting headache pain – a tool to aid the diagnosis of cluster headache: a pilot study

Introduction and objective: The diagnosis of primary headaches is based on the International Classification of Headache Disorders (ICHD-3). Cluster headache (CH), a debilitating primary headache, is often misdiagnosed as migraine. In the absence of biological markers, a new visual screening tool with images depicting pain could aid the correct diagnosis of CH. The objective of the study is to test the tool on healthy participants and participants with CH and migraine.Methods: In phase 1, 6 images portraying people with pain were tested on 150 healthy participants. The healthy participants were asked to rate the images as mild, moderate, severe or excruciating pain. In phase 2, the images were further tested on 116 participants with headache (16 participants with CH, 100 participants with migraine). The participants were recruited prospectively from a tertiary headache center between February and May 2017. The participants were asked to choose which image best illustrated their headache attacks.Results: Phase 1 results showed that the images represent a range of headache pain severities from mild to excruciating as rated by healthy participants. They rated two images as excruciating, one image as severe, one image as moderate/severe, one image as moderate and one image as mild. Phase 2 results showed that two-thirds of participants with CH (69%) and half of the participants with migraine (52%) chose an image described as excruciating by the healthy participants.Conclusion: We developed a screening tool with six drawings depicting headache pain severities from mild to excruciating as rated by the healthy participants. Although the images did not differentiate between CH and migraine, the study indicated the potential of using visual aids to assess headache severity

Update on the pathophysiology of cluster headache: Imaging and neuropeptide studies

Objective: Cluster headache (CH) is the most severe primary headache condition. Its pathophysiology is multifaceted and incompletely understood. This review brings together the latest neuroimaging and neuropeptide evidence on the pathophysiology of CH.Methods: A review of the literature was conducted by searching PubMed and Web of Science. The search was conducted using the following keywords: imaging studies, voxel-based morphometry, diffusion-tensor imaging, diffusion magnetic resonance imaging, tractography, connectivity, cerebral networks, neuromodulation, central modulation, deep brain stimulation, orexin-A, orexin-B, tract-based spatial statistics, single-photon emission computer tomography studies, positron-emission tomography, functional magnetic resonance imaging, magnetic resonance spectroscopy, trigeminovascular system, neuropeptides, calcitonin gene-related peptide, neurokinin A, substance P, nitric oxide synthase, pituitary adenylate cyclase-activating peptide, vasoactive intestinal peptide, neuropeptide Y, acetylcholine, noradrenaline, and ATP. “Cluster headache” was combined with each keyword for more relevant results. All irrelevant and duplicated records were excluded. Search dates were from October 1976 to May 2018.Results: Neuroimaging studies support the role of the hypothalamus in CH, as well as other brain areas involved in the pain matrix. Activation of the trigeminovascular system and the release of neuropeptides play an important role in CH pathophysiology. Among neuropeptides, calcitonin gene-related peptide, vasoactive intestinal peptide, and pituitary adenylate cyclase-activating peptide have been reported to be reliable biomarkers for CH attacks, though not specific for CH. Several other neuropeptides are involved in trigeminovascular activation, but the current evidence does not qualify them as reliable biomarkers in CH.Conclusion: CH has a complex pathophysiology and the pain mechanism is not completely understood. Recent neuroimaging studies have provided insight into the functional and structural network bases of CH pathophysiology. Although there has been important progress in neuropeptide studies, a specific biomarker for CH is yet to be found

Development and evaluation of a screening tool to aid the diagnosis of a cluster headache

Cluster headache (CH), a severe primary headache, is often misdiagnosed and mismanaged. The aim of this study was to develop and evaluate a screening tool to aid the diagnosis of CH. We developed a novel 12-item screening tool. This was comprised of four components: (1) images depicting headache pain; (2) pain descriptors; (3) key questions that could differentiate between CH and migraine; and (4) a visual analogue pain scale. The total possible questionnaire score ranged from 3-32. Patients with CH and migraines (control group) were recruited prospectively from a headache centre in the North of England, UK. Two-hundred and ninety-six patients were included in the study: 81 CH patients, 36 of which suffer with episodic CH and 45 with chronic CH; 215 migraine patients, 92 of which suffer with episodic migraine and 123 with chronic migraine. The mean questionnaire score was higher in CH patients versus migraine patients (28.4 versus 19.5). At a cut-off score of >25 out of 32, the screening tool had a sensitivity of 86.4% and a specificity of 92.0% in differentiating between CH and migraine. The screening tool could be a useful instrument to aid the diagnosis of a CH. The images depicting headache pain do not clearly discriminate between CH and migraine

Development and evaluation of a screening tool to aid the diagnosis of a cluster headache

Cluster headache (CH), a severe primary headache, is often misdiagnosed and mismanaged. The aim of this study was to develop and evaluate a screening tool to aid the diagnosis of CH. We developed a novel 12-item screening tool. This was comprised of four components: (1) images depicting headache pain; (2) pain descriptors; (3) key questions that could differentiate between CH and migraine; and (4) a visual analogue pain scale. The total possible questionnaire score ranged from 3-32. Patients with CH and migraines (control group) were recruited prospectively from a headache centre in the North of England, UK. Two-hundred and ninety-six patients were included in the study: 81 CH patients, 36 of which suffer with episodic CH and 45 with chronic CH; 215 migraine patients, 92 of which suffer with episodic migraine and 123 with chronic migraine. The mean questionnaire score was higher in CH patients versus migraine patients (28.4 versus 19.5). At a cut-off score of >25 out of 32, the screening tool had a sensitivity of 86.4% and a specificity of 92.0% in differentiating between CH and migraine. The screening tool could be a useful instrument to aid the diagnosis of a CH. The images depicting headache pain do not clearly discriminate between CH and migraine

An analysis of domestic water consumption in Jaipur, India

Aim: To explore the relation between water consumption and water use behaviour and attitudes, and devices applied in households in urban areas in India. Methodology and study site: This paper presents the results of a domestic water consumption survey carried out in Jaipur, India. A questionnaire containing over 60 questions was developed to collect information on households’ characteristics (e.g. family size, household type, and number of children), indoor and outdoor water use activities and their respective frequencies and durations. Information was also gathered on the volume of water used in each of these activities. Over 90 households of different types (standalone houses and apartments in a university campus and Jaipur city) participated in the survey. The survey results were analysed using cluster analysis and one-way analysis of variance (ANOVA). Results: The results show that the per capita consumption varies considerably with household type and size. The average water consumption was 183 and 215 litres/person/day for standalone households and apartments, respectively. Water used in bathing and WC's represent the highest proportion of water consumption in both stand-alone houses and apartments. Over 40% of the households reported no use of showers. The per capita water consumption is inversely related to family size especially in stand-alone houses. Conclusion: The information pertaining to water use habits and the qualitative and quantitative analysis can be used as an input to a proposed domestic water efficiency tool (DoWET) which can generate optimal water efficient composite strategies keeping in view a range of sustainability indicators including water saving potential, cost and associated energy consumption of the water saving devices and fixtures available in India.The work presented here was undertaken to inform the research being carried out in Water4India project supported by EC as FP7 project bearing grant agreement no: 308496

Systematic literature review on the delays in the diagnosis and misdiagnosis of cluster headache

IntroductionPatients with cluster headache (CH), the most common trigeminal autonomic cephalalgia, often face delayed diagnosis, misdiagnosis and mismanagement.ObjectivesTo identify, appraise and synthesise clinical studies on the delays in diagnosis and misdiagnosis of CH in order to determine its causes and help the management of this condition.MethodsThe systematic review was prepared, conducted and reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis. It was registered with International Prospective Register of Systematic Reviews. A systematic search of different electronic databases (Medline, EMBASE, PsycINFO, PubMed, CINAHL, BNI, HMIC, AMED, HBE and Cochrane Library) was carried out in May 2017. Reference lists of relevant articles were hand searched.ResultsThe search identified 201 unique studies. Fifteen studies met the inclusion criteria of which 13 case series studies and two survey studies. Nine studies assessed the delays in diagnosis and misdiagnosis of CH, five studies the delays in diagnosis and one study the misdiagnosis of CH. The studies included 4661 patients. Delays in diagnosis, misdiagnosis and mismanagement have been reported in many European countries, Japan and in the USA with well-developed health services. The patients with CH often visited many different clinicians, surgeons and dentists and received multiple diagnosis prior to being correctly diagnosed.ConclusionThis systematic review shows that the delays in the diagnosis of CH are a widespread problem, the time to diagnosis still vary from country to country and both patients and physicians are responsible for the delays in diagnosis

Changes in physical activity during hospital admission for chronic respiratory disease: Inpatient step count does not recover

Background and objectiveEstablishing the amount of inpatient physical activity (PA) undertaken by individuals hospitalized for chronic respiratory disease is needed to inform interventions. This observational study investigated whether PA changes when a person is an inpatient, how long is required to obtain representative PA measures and whether PA varies within a day and between patients of differing lengths of stay.MethodsA total of 389 participants were recruited as early as possible into their hospitalization. Patients wore a PA monitor from recruitment until discharge. Step count was extracted for a range of wear time criteria. Single‐day intraclass correlation coefficients (ICC) were calculated, with an ICC ≥ 0.80 deemed acceptable.ResultsPA data were available for 259 participants. No changes in daily step count were observed during the inpatient stay (586 (95% CI: 427–744) vs 652 (95% CI: 493–812) steps/day for day 2 and 7, respectively). ICC across all wear time criteria were > 0.80. The most stringent wear time criterion, retaining 80% of the sample, was ≥11 h on ≥1 day. More steps were taken during the morning and afternoon than overnight and evening. After controlling for the Medical Research Council (MRC) grade or oxygen use, there was no difference in step count between patients admitted for 2–3 days (short stay) and those admitted for 7–14 days (long stay).ConclusionPatients move little during their hospitalization, and inpatient PA did not increase during their stay. A wear time criterion of 11 waking hours on any single day was representative of the entire admission whilst retaining an acceptable proportion of the initial sample size. Patients may need encouragement to move more during their hospital stay

Mechanistic interplay between ceramide and insulin resistance

Recent research adds to a growing body of literature on the essential role of ceramides in glucose homeostasis and insulin signaling, while the mechanistic interplay between various components of ceramide metabolism remains to be quantified. We present an extended model of C16:0 ceramide production through both the de novo synthesis and the salvage pathways. We verify our model with a combination of published models and independent experimental data. In silico experiments of the behavior of ceramide and related bioactive lipids in accordance with the observed transcriptomic changes in obese/diabetic murine macrophages at 5 and 16 weeks support the observation of insulin resistance only at the later phase. Our analysis suggests the pivotal role of ceramide synthase, serine palmitoyltransferase and dihydroceramide desaturase involved in the de novo synthesis and the salvage pathways in influencing insulin resistance versus its regulation

Visual histological assessment of morphological features reflects the underlying molecular profile in invasive breast cancer : a morpho‐molecular study

Background: Tumour genotype and phenotype are related and can predict outcome. In this study, we hypothesised that the visual assessment of breast cancer (BC) morphological features can provide valuable insight into underlying molecular profiles. Methods: The Cancer Genome Atlas (TCGA) BC cohort was used (n=743) and morphological features including Nottingham grade and its components and nucleolar prominence were assessed utilising whole slide images (WSIs). Two independent scores were assigned, and discordant cases were utilised to represent cases with intermediate morphological features. Differentially expressed genes (DEGs) were identified for each feature, compared among concordant/discordant cases and tested for specific pathways. Results: Concordant grading was observed in 467/743 (63%) of cases. Among concordant case groups, 8 common DEGs (UGT8, DDC, RGR, RLBP1, SPRR1B, CXorf49B, PSAPL1, and SPRR2G) were associated with overall tumour grade and its components. These genes are related mainly to cellular proliferation, differentiation and metabolism. The number of DEGs in cases with discordant grading was larger than those identified in concordant cases. The largest number of DEGs was observed in discordant grade 1:3 cases (n=1185). DEGs were identified for each discordant component. Some DEGs were uniquely associated with well‐defined specific morphological features, whereas expression/co‐expression of other genes was identified across multiple features and underlined intermediate morphological features. Conclusion: Morphological features are likely related to distinct underlying molecular profiles that drive both morphology and behaviour. This study provides further evidence to support the use of image‐based analysis of WSIs, including artificial intelligence algorithms, to predict tumour molecular profiles and outcome