Optimal adjustment sets for causal query estimation in partially observed biomolecular networks.

Causal query estimation in biomolecular networks commonly selects a 'valid adjustment set', i.e. a subset of network variables that eliminates the bias of the estimator. A same query may have multiple valid adjustment sets, each with a different variance. When networks are partially observed, current methods use graph-based criteria to find an adjustment set that minimizes asymptotic variance. Unfortunately, many models that share the same graph topology, and therefore same functional dependencies, may differ in the processes that generate the observational data. In these cases, the topology-based criteria fail to distinguish the variances of the adjustment sets. This deficiency can lead to sub-optimal adjustment sets, and to miss-characterization of the effect of the intervention. We propose an approach for deriving 'optimal adjustment sets' that takes into account the nature of the data, bias and finite-sample variance of the estimator, and cost. It empirically learns the data generating processes from historical experimental data, and characterizes the properties of the estimators by simulation. We demonstrate the utility of the proposed approach in four biomolecular Case studies with different topologies and different data generation processes. The implementation and reproducible Case studies are at https://github.com/srtaheri/OptimalAdjustmentSet.

Do-calculus enables estimation of causal effects in partially observed biomolecular pathways.

MOTIVATION: Estimating causal queries, such as changes in protein abundance in response to a perturbation, is a fundamental task in the analysis of biomolecular pathways. The estimation requires experimental measurements on the pathway components. However, in practice many pathway components are left unobserved (latent) because they are either unknown, or difficult to measure. Latent variable models (LVMs) are well-suited for such estimation. Unfortunately, LVM-based estimation of causal queries can be inaccurate when parameters of the latent variables are not uniquely identified, or when the number of latent variables is misspecified. This has limited the use of LVMs for causal inference in biomolecular pathways. RESULTS: In this article, we propose a general and practical approach for LVM-based estimation of causal queries. We prove that, despite the challenges above, LVM-based estimators of causal queries are accurate if the queries are identifiable according to Pearl's do-calculus and describe an algorithm for its estimation. We illustrate the breadth and the practical utility of this approach for estimating causal queries in four synthetic and two experimental case studies, where structures of biomolecular pathways challenge the existing methods for causal query estimation. AVAILABILITY AND IMPLEMENTATION: The code and the data documenting all the case studies are available at https://github.com/srtaheri/LVMwithDoCalculus. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Taxonomy of effective strategies to reduce unnecessary caesareans: a systematic review.

BACKGROUND: The increasing trend in unnecessary caesarean sections has caused maternal and neonatal health concerns worldwide. Various medical and non-medical interventions have been designed and implemented to reduce caesarian section overuse. However, their efficacy is questionable. AIMS: This study aimed to identify and classify effective interventions to reduce unnecessary caesarian sections. METHODS: We searched EMBASE, MEDLINE, Web of Knowledge and Scopus databases for articles, using appropriate search strategies, up to 2 June 2020. Overall, 7951 identified articles were screened and assessed using a valid quality assessment checklist. Finally, 109 eligible studies were included in this review. Thematic content analysis was used to identify and classify the effective interventions. RESULTS: Overall, 188 effective caesarian section reduction measures were identified. They were categorized into 45 actions, 16 intervention groups and 6 WHO building blocks, including "governance and leadership", "financing", "health workforce", "medical products and technologies", "information" and "service delivery". Using qualified and competent staff, intra-partum services, and oversight were the most commonly applied interventions to reduce unnecessary caesarian sections. CONCLUSIONS: A taxonomy of effective strategies to reduce unnecessary caesarian sections was developed in this study. A holistic approach is crucial to addressing the new epidemic of unnecessary caesarian section. Multiple interventions based on the underlying causes of caesarian section overuse should be designed and implemented at local and global levels.

The occurrence of Adrenocorticotropic hormone-independent Cushing's syndrome in a woman with the history of papillary thyroid carcinoma: a case report.

BACKGROUND: Thyroid papillary carcinoma is one of the most common endocrine tumors, and it accounts for 85% of thyroid tumors. Adrenocorticotropic hormone (ACTH)-independent Cushing's syndrome is a rare disease. In this case report, we discuss a very rare case of coexistence of papillary thyroid carcinoma and Cushing's syndrome with an adrenal origin. CASE PRESENTATION: The patient was a 33-year-old Iranian/Persian woman with a history of papillary thyroid carcinoma treated with iodine 131 three years ago. She presented with weight gain, amenorrhea, and mood disorders in the last six months. She was diagnosed with an ACTH-independent Cushing's syndrome due to benign adrenal adenoma and underwent laparoscopic adrenalectomy surgery. The symptoms of the syndrome were disappeared after the surgery. CONCLUSIONS: ACTH-independent Cushing's syndrome due to adrenal tumor and papillary thyroid cancer occurs sporadically. The co-occurrence of two endocrine tumors with different origins is rare. It is recommended that the occurrence of other endocrine neoplasms be considered when an endocrine tumor is diagnosed.

Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis.

Counterfactual inference is a useful tool for comparing outcomes of interventions on complex systems. It requires us to represent the system in form of a structural causal model, complete with a causal diagram, probabilistic assumptions on exogenous variables, and functional assignments. Specifying such models can be extremely difficult in practice. The process requires substantial domain expertise, and does not scale easily to large systems, multiple systems, or novel system modifications. At the same time, many application domains, such as molecular biology, are rich in structured causal knowledge that is qualitative in nature. This article proposes a general approach for querying a causal biological knowledge graph, and converting the qualitative result into a quantitative structural causal model that can learn from data to answer the question. We demonstrate the feasibility, accuracy and versatility of this approach using two case studies in systems biology. The first demonstrates the appropriateness of the underlying assumptions and the accuracy of the results. The second demonstrates the versatility of the approach by querying a knowledge base for the molecular determinants of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced cytokine storm, and performing counterfactual inference to estimate the causal effect of medical countermeasures for severely ill patients.

MSstatsQC 2.0: R/Bioconductor Package for Statistical Quality Control of Mass Spectrometry-Based Proteomics Experiments.

MSstatsQC is an R/Bioconductor package for statistical monitoring of longitudinal system suitability and quality control in mass spectrometry-based proteomics. MSstatsQC was initially designed for targeted selected reaction monitoring experiments. This paper presents an extension, MSstatsQC 2.0, that supports experiments with global data-dependent and data-independent acquisition. The extension implements data processing and analyses that are specific to these acquisition types. It relies on state-of-the-art methods of statistical process control to detect deviations from optimal performance of various metrics (such as intensity and retention time of chromatographic peaks) and to summarize the results across multiple metrics and analytes. Additionally, the web-based graphical user interface MSstatsQCgui, implemented as a separate R/Bioconductor package, provides a user-friendly way to visualize and report the results from MSstatsQC 2.0.

The Effect of Dietary Supplements Containing Green Tea, Capsaicin and Ginger Extracts on Weight Loss and Metabolic Profiles in Overweight Women: A Randomized Double-Blind Placebo-Controlled Clinical Trial.

BACKGROUND: This study was conducted to determine the effects of dietary supplements containing green tea, capsaicin and ginger extracts on weight loss and metabolic profiles among overweight women. METHODS: This randomized double-blind placebo-controlled clinical trial was implemented among 50 overweight women. Participants were randomly divided into 2 groups. Group A received dietary supplements containing 125 mg green tea, 25 mg capsaicin and 50 mg ginger extracts (n = 25) group B received placebos (n = 25) twice with lunch and twice with dinner daily for 8 weeks. RESULTS: Compared with placebo, taking dietary supplements containing green tea, capsaicin and ginger resulted in a significant decrease in weight (-1.8 ± 1.5 vs. +0.4 ± 1.2 kg, respectively, p < 0.001) and body mass index (BMI; -0.7 ± 0.5 vs. +0.1 ± 0.5 kg/m2, respectively, p < 0.001). In addition, subjects who received green tea, capsaicin and ginger co-supplements had significantly decreased serum insulin concentrations (-2.6 ± 3.9 vs. -0.6 ± 2.0 µIU/mL, p = 0.02), homeostatic model of assessment for insulin resistance (-0.5 ± 0.8 vs. -0.05 ± 0.6, p = 0.01), and increased quantitative insulin sensitivity check index (+0.01 ± 0.01 vs. +0.001 ± 0.01, p = 0.008) and plasma glutathione (GSH) levels (+73.8 ± 120.6 vs. -28.3 ± 193.4 µmol/L, p = 0.03) compared with the placebo. CONCLUSIONS: Our study indicated that taking green tea, capsaicin and ginger co-supplements for 8 weeks among overweight women had beneficial effects on weight, BMI, markers of insulin metabolism and plasma GSH levels.

MSstatsQC: Longitudinal System Suitability Monitoring and Quality Control for Targeted Proteomic Experiments.

Selected Reaction Monitoring (SRM) is a powerful tool for targeted detection and quantification of peptides in complex matrices. An important objective of SRM is to obtain peptide quantifications that are (1) suitable for the investigation, and (2) reproducible across laboratories and runs. The first objective is achieved by system suitability tests (SST), which verify that mass spectrometric instrumentation performs as specified. The second objective is achieved by quality control (QC), which provides in-process quality assurance of the sample profile. A common aspect of SST and QC is the longitudinal nature of the data. Although SST and QC have received a lot of attention in the proteomic community, the currently used statistical methods are limited. This manuscript improves upon the statistical methodology for SST and QC that is currently used in proteomics. It adapts the modern methods of longitudinal statistical process control, such as simultaneous and time weighted control charts and change point analysis, to SST and QC of SRM experiments, discusses their advantages, and provides practical guidelines. Evaluations on simulated data sets, and on data sets from the Clinical Proteomics Technology Assessment for Cancer (CPTAC) consortium, demonstrated that these methods substantially improve our ability of real time monitoring, early detection and prevention of chromatographic and instrumental problems. We implemented the methods in an open-source R-based software package MSstatsQC and its web-based graphical user interface. They are available for use stand-alone, or for integration with automated pipelines. Although the examples focus on targeted proteomics, the statistical methods in this manuscript apply more generally to quantitative proteomics.

The effects of vitamin D, K and calcium co-supplementation on carotid intima-media thickness and metabolic status in overweight type 2 diabetic patients with CHD.

This study was conducted to examine the effects of vitamin D, K and Ca co-supplementation on carotid intima-media thickness (CIMT) and metabolic status in overweight diabetic patients with CHD. This randomised, double-blind, placebo-controlled trial was conducted among sixty-six diabetic patients with CHD. Participants were randomly allocated into two groups to take either 5µg vitamin D, 90 µg vitamin K plus 500 mg Ca supplements (n 33) or placebo (n 33) twice a day for 12 weeks. Fasting blood samples were obtained at the beginning of the study and after the 12-week intervention period to determine related markers. Vitamin D, K and Ca co-supplementation resulted in a significant reduction in maximum levels of left CIMT (-0·04 (sd 0·22) v. +0·04 (sd 0·09) mm, P=0·02). Changes in serum vitamin D (+6·5 (sd 7·8) v. +0·4 (sd 2·2) ng/ml, P<0·001), Ca (+0·6 (sd 0·3) v. +0·1 (sd 0·1) mg/dl, P<0·001) and insulin concentrations (-0·9 (sd 3·1) v. +2·6 (sd 7·2) µIU/ml, P=0·01), homoeostasis model for assessment of estimated insulin resistance (-0·4 (sd 1·2) v. +0·7 (sd 2·3), P=0·01), ß-cell function (-2·1 (sd 9·0) v. +8·9 (sd 23·7), P=0·01) and quantitative insulin sensitivity check index (+0·007 (sd 0·01) v. -0·006 (sd 0·02), P=0·01) in supplemented patients were significantly different from those in patients in the placebo group. Supplementation resulted in significant changes in HDL-cholesterol (+2·7 (sd 7·0) v. -2·5 (sd 5·7) mg/dl, P=0·002), high-sensitivity C-reactive protein (-1320·1 (sd 3758·3) v. +464·0 (sd 3053·3) ng/ml, P=0·03) and plasma malondialdehyde concentrations (-0·4 (sd 0·5) v. -1·0 (sd 1·1) µmol/l, P=0·007) compared with placebo. Overall, vitamin D, K and Ca co-supplementation for 12 weeks among diabetic patients with CHD had beneficial effects on maximum levels of left CIMT and metabolic status. The effect of vitamin D, K and Ca co-supplementation on maximum levels of left CIMT could be a chance finding.

Self-assembly of smallest magnetic particles.

The assembly of tiny magnetic particles in external magnetic fields is important for many applications ranging from data storage to medical technologies. The development of ever smaller magnetic structures is restricted by a size limit, where the particles are just barely magnetic. For such particles we report the discovery of a kind of solution assembly hitherto unobserved, to our knowledge. The fact that the assembly occurs in solution is very relevant for applications, where magnetic nanoparticles are either solution-processed or are used in liquid biological environments. Induced by an external magnetic field, nanocubes spontaneously assemble into 1D chains, 2D monolayer sheets, and large 3D cuboids with almost perfect internal ordering. The self-assembly of the nanocubes can be elucidated considering the dipole-dipole interaction of small superparamagnetic particles. Complex 3D geometrical arrangements of the nanodipoles are obtained under the assumption that the orientation of magnetization is freely adjustable within the superlattice and tends to minimize the binding energy. On that basis the magnetic moment of the cuboids can be explained.

Analgesic Effects of Inhalation of Nitric Oxide (Entonox) and Parenteral Morphine Sulfate in Patients with Renal Colic; A Randomized Clinical Trial.

OBJECTIVE: To compare the analgesiceffects of Nitrous oxide and morphine sulfate in patients with acute renal colic due to urolithiasis. METHODS: This was randomized clinical trial being performed in Imam Hossein hospital affiliated with Shahid Beheshti University of Medical Sciences during a 1-year period from May2013 to May2014.  A total of number of 100 patients, with an age range of 20-50 years, who presented with renal colic secondary to urolithiasis confirmed by ultrasonography were randomly assigned to receive morphine sulfate injection (0.1 mg/kg) with 100 mg diclofenac suppository (n=50) or Entonox exhalation (50% nitric oxide and 50% oxygen) for 30-minutes with 100 mg diclofenac suppository (n=50). Quantitative measurement was of pain was performed according to a visual analogue scale (VAS), before, 3, 5, 10 and 30-minute after the intervention. The pain severity and side effects were measured between two study groups. RESULTS: The baseline characteristics of the patients in two study groups were comparable. The frequencies of pain persistence (at least 50%) at 3-, 5-, 10- and 30-minute intervals in morphine sulfategroup were 96%, 80%, 50% and 8%, respectively; these frequencies in Entonex  were 82%, 42%, 12% and 2%, respectively (p<0.001). Cox regression modeling showed that use of Entonox was the only effective agent in the success of treatment, compared to the use of morphine, i.e. use of Entonox increased the success of treatment up to 2.1 folds compared to the use of morphine (HR=2.1; 95% CI: 1.2-3.6; p=0.006). CONCLUSION: The results of the present study demonstrate that inhalation of Entonox is an effective and safe analgesic regimen for acute renal colic. It acts more rapidly and is more potent in relieving renal colic when compared to morphine sulfate.Entonox can be regarded as an appropriate alternative to analgesics like opioids in this ground.

Polymer ligand exchange to control stabilization and compatibilization of nanocrystals.

We demonstrate polymer ligand exchange to be an efficient method to control steric stabilization and compatibilization of nanocrystals. A rational design of polymer binding groups and ligand exchange conditions allows to attach polymer brushes with grafting densities >1 nm(-2) to inorganic nanocrystals for nearly any nanocrystal/polymer combination using only a few types of binding groups. We demonstrate the potential of the method as an alternative to established grafting-from and grafting-to routes in considerably increasing the stabilization of inorganic nanocrystals in solution, to prepare completely miscible polymer nanocomposites with a controllable distance between nanoparticles, and to induce and control aggregation into percolation networks in polymeric matrices for a variety of different nanocrystal/polymer combinations. A dense attachment of very short polymer ligands is possible enabling to prepare ordered nanoparticle monolayers with a distance or pitch of only 7.2 nm, corresponding to a potential magnetic storage density of 12.4 Tb/in(2). Not only end-functionalized homopolymers, but also commercially available copolymers with functional comonomers can be used for stable ligand exchange, demonstrating the versatility and broad potential of the method.

Molecular spoked wheels: synthesis and self-assembly studies on rigid nanoscale 2D objects.

We present the efficient synthesis of a new molecular spoked-wheel structure (MSW-3). Two derivatives with diameters of approximately 4 nm have been prepared. By highlighting the importance of pseudo-high-dilution conditions during cyclization, we were able to access the compounds on a several hundred milligram scale. In addition to the standard characterization (NMR spectroscopy, MS), we describe a detailed investigation of the optical properties of the fluorescent MSWs by comparison with appropriate model chromophores. Furthermore, a comprehensive study of the structure in solution by means of light- and X-ray scattering experiments has been conducted. Scanning tunneling microscopy (STM) revealed the two-dimensional organization of the molecules on highly oriented pyrolytic graphite and emphasized the spoked-wheel structure. The diameter of these molecules measured by small-angle X-ray scattering is in very good agreement with that obtained from STM and matches the results of molecular modeling. This confirms the rigidifying effect of the spokes, which results in highly shape-persistent nanometer-sized oblate organic compounds.

Completely miscible polyethylene nanocomposites.

A route to fully miscible polyethylene (PE) nanocomposites has been established based on polymer-brush-coated nanoparticles. These nanoparticles can be mixed with PE at any ratio, with homogeneous dispersion, and without aggregation. This allowed a first systematic study of the thermomechanical properties of PE nanocomposites without interference from aggregation effects. We observe that the storage modulus in the semicrystalline state and the softening temperature increase significantly with increasing nanoparticle content, whereas the melt viscosity is unaltered by the presence of nanoparticles. We show that the complete miscibility with the semicrystalline polymer matrix and the improvement of thermomechanical properties in the solid state is caused by the PE-coated nanoparticles being nucleating agents for the crystallization of PE. This provides a general route to fully miscibility nanocomposites with semicrystalline polymers.