Exploring the potential of high-resolution LC-MS in combination with ion mobility separation and surrogate minimal depth for enhanced almond origin authentication

Almonds (Prunus dulcisMill.) are consumed worldwide and their geographical origin plays a crucial role in determining their market value. In the present study, a total of 250 almond reference samples from six countries (Australia, Spain, Iran, Italy, Morocco, and the USA) were non-polar extracted and analyzed by UPLC-ESI-IM-qToF-MS. Four harvest periods, more than 30 different varieties, including both sweet and bitter almonds, were considered in the method development. Principal component analysis showed that there are three groups of samples with similarities: Australia/USA, Spain/Italy and Iran/Morocco. For origin determination, a random forest achieved an accuracy of 88.8 %. Misclassifications occurred mainly between almonds from the USA and Australia, due to similar varieties and similar external influences such as climate conditions. Metabolites relevant for classification were selected using Surrogate Minimal Depth, with triacylglycerides containing oxidized, odd chained or short chained fatty acids and some phospholipids proven to be the most suitable marker substances. Our results show that focusing on the identified lipids (e. g., using a QqQ-MS instrument) is a promising approach to transfer the origin determination of almonds to routine analysis.

Efficacy of Noninvasive Brain Stimulation in Treating General Psychopathology Symptoms in Schizophrenia: A Meta-Analysis

OBJECTIVES

Noninvasive brain stimulation (NIBS) has been shown to effectively alleviate negative and positive symptoms in patients with schizophrenia. However, its impact on depressive symptoms and general psychopathology symptoms (GPSs), which are crucial for functional outcomes, remains uncertain. We aimed to compare the efficacy of various NIBS interventions in treating depressive symptoms and GPSs.

METHODS

We conducted a comprehensive search of multiple databases and performed a meta-analysis to evaluate the efficacy of NIBS in treating depressive symptoms and GPSs in schizophrenia. The effect sizes of NIBS for depression symptoms and GPSs were estimated using standard mean differences (SMDs) with 95% confidence intervals (CIs). Subgroup analyses were employed to examine potential influencing factors on the pooled SMD of NIBS for GPSs.

RESULTS

Our search yielded 35 randomized controlled trials involving 1715 individuals diagnosed with schizophrenia. The protocol of this systematic review was registered with INPLASY (protocol ID: INPLASY202320082). Neither repetitive transcranial magnetic stimulation (rTMS) nor transcranial direct current stimulation (tDCS) demonstrated significant improvements in depressive symptoms compared to sham controls. NIBS exhibited a small-to-moderate effect size for GPSs, with a pooled SMD of -0.2956 (95% CI: -0.459 to -0.132) and a heterogeneity (I2) of 58.9% (95% CI: 41.5% to 71.1%; p < 0.01) based on a random-effects model. Subgroup analyses of different types of NIBS, different frequencies of rTMS, and different stimulation sites of rTMS revealed no significant differences. Only sex had a significant influence on the effect size of NIBS for general psychopathology symptoms (p < 0.05). However, rTMS might be superior to tDCS, and high-frequency rTMS outperformed low-frequency rTMS in treating GPSs.

CONCLUSIONS

We found a small-to-moderate effect size of NIBS in alleviating GPSs in patients with schizophrenia. Both rTMS and tDCS were more effective than sham stimulation in reducing GPSs in schizophrenia. The frequency used was associated with rTMS efficacy for GPSs.

Bioinformatics, thermodynamics, and mechanical resistance of the FtsZ-ZipA complex of Escherichia coli supports a highly dynamic protein interaction in the divisome

In most microorganisms, cell division is guided by the divisome, a multiprotein complex that assembles at the equator of the cell and is responsible for the synthesis of new cell wall material. FtsZ, the first protein to assemble into this complex forms protofilaments in the cytosol which are anchored to the inner side of the cytosolic membrane by the proteins ZipA and FtsA. FtsZ protofilaments generate a force that deforms the cytosolic membrane and may contribute to the constriction force that leads to the septation of the cell. It has not been studied yet how the membrane protein anchors respond to this force generated by FtsZ. Here we studied the effect of force in the FtsZ-ZipA interaction. We used SMD and obtained the distance to the transition state of key interacting amino acids and SASA of FtsZ and ZipA through the dissociation. The SMD mechanism was corroborated by ITC, and the thermodynamic parameters ΔG0, ΔH0 and ΔS0 were obtained. Finally, we used force spectroscopy by optical tweezers to determine the lifetime of the interaction and rupture probability and their dependence on force at single molecule level. We also obtained the transition state distance, and free energy of the interaction. With the gathering of structural, thermodynamic, kinetic and force parameters we conclude that interaction between FtsZ and ZipA proteins is consistence with the highly dynamic treadmilling process and at least seven ZipA molecules are required to bind to a FtsZ protofilaments to transduce a significant force.

[Treatment of lower risk myelodysplastic syndromes]

For low-risk myelodysplastic syndromes, the goal of treatment is to correct cytopenias or their consequences. Erythropoiesis-stimulating agents have an important role in the management of anemia. In this chapter, we will detail the response to ESAs, the factors predictive of response to ESAs. However, the search for new therapeutic options for low-risk, ESA-resistant MDS remains necessary as the incidence of AML transformation of the patients is higher. We can retain luspatercept for MDS with excess ring of sideroblasts, lenalidomide, and some molecules currently being tested such as imetelstat or roxedustat. However, the search for new therapeutic options for ESA-resistant low-risk MDS remains necessary. We can use androgenotherapy or TPO agonists in limited access for symptomatic thrombocytopenia.

[Treating high-risk myelodysplastic syndromes]

Myelodysplastic syndromes (MDS) are clonal stem cell diseases that primarily affect the elderly. They are classified into low- and high-risk MDS according to prognostic scoring systems. In high-risk patients, treatment should aim to modify the course of the disease by preventing progression to acute myeloid leukemia, and thus improve survival. Stem cell transplantation remains the only curative treatment when possible, but this concerns a small minority of patients. Treatment is mainly based on hypomethylating agents (HMA). Our understanding of the biology of MDS has led to the development of drugs targeting key cellular processes such as apoptosis or post-translational modifications of proteins, the microenvironment and genetic mutations. Currently, new drugs are mainly tested in combination with HMAs in several clinical trials and, although none has yet obtained marketing authorization, many molecules seem promising.

[MDS & CMML: Diagnostic and classification]

In 2023, a diagnosis process of myelodysplastic syndrome (MDS) or chronic myelomonocytic leukemia (CMML) is mainly based on morphological results obtained on bone marrow and blood smears which could be completed by cytogenetical analyses. Due to recent finding, flow cytometry data are recognized as useful for the diagnosis of CMML especially. Actual classifications and prognostic scoring systems have changed and nowadays include results of high-throughput sequencing approaches in addition to cytogenetical results. All together, these data allow the medical world to correctly evaluate the prognosis of these patients and to provide some information for targeted therapies. This chapter will provide the most important modifications recently published in the field of diagnosis and prognosis of MDS and CMML.

Comparative Analysis of LC-ESI-IM-qToF-MS and FT-NIR Spectroscopy Approaches for the Authentication of Organic and Conventional Eggs

The importance of animal welfare and the organic production of chicken eggs has increased in the European Union in recent years. Legal regulation for organic husbandry makes the production of organic chicken eggs more expensive compared to conventional husbandry and thus increases the risk of food fraud. Therefore, the aim of this study was to develop a non-targeted lipidomic LC-ESI-IM-qToF-MS method based on 270 egg samples, which achieved a classification accuracy of 96.3%. Subsequently, surrogate minimal depth (SMD) was applied to select important variables identified as carotenoids and lipids based on their MS/MS spectra. The LC-MS results were compared with FT-NIR spectroscopy analysis as a low-resolution screening method and achieved 80.0% accuracy. Here, SMD selected parts of the spectrum which are associated with lipids and proteins. Furthermore, we used SMD for low-level data fusion to analyze relations between the variables of the LC-MS and the FT-NIR spectroscopy datasets. Thereby, lipid-associated bands of the FT-NIR spectrum were related to the identified lipids from the LC-MS analysis, demonstrating that FT-NIR spectroscopy partially provides similar information about the lipidome. In future applications, eggs can therefore be analyzed with FT-NIR spectroscopy to identify conspicuous samples that can subsequently be counter-tested by mass spectrometry.

Calculating the Aqueous pKa of Phenols: Predictions for Antioxidants and Cannabinoids

We aim to develop a theoretical methodology for the accurate aqueous pK_a prediction of structurally complex phenolic antioxidants and cannabinoids. In this study, five functionals (M06-2X, B3LYP, BHandHLYP, PBE0, and TPSS) and two solvent models (SMD and PCM) were combined with the 6-311++G(d,p) basis set to predict pK_a values for twenty structurally simple phenols. None of the direct calculations produced good results. However, the correlations between the calculated Gibbs energy difference of each acid and its conjugate base, ΔGaq(BA)°=ΔGaqA-°-ΔGaq(HA)°, and the experimental aqueous pK_a values had superior predictive accuracy, which was also tested relative to an independent set of ten molecules of which six were structurally complex phenols. New correlations were built with twenty-seven phenols (including the phenols with experimental pK_a values from the test set), which were used to make predictions. The best correlation equations used the PCM method and produced mean absolute errors of 0.26-0.27 pK_a units and R² values of 0.957-0.960. The average range of predictions for the potential antioxidants (cannabinoids) was 0.15 (0.25) pK_a units, which indicates good agreement between our methodologies. The new correlation equations could be used to make pK_a predictions for other phenols in water and potentially in other solvents where they might be more soluble.

Insight into the Binding Mechanisms of Quartz-Selective Peptides: Toward Greener Flotation Processes

Mining practices, chiefly froth flotation, are being critically reassessed to replace their use of biohazardous chemical reagents in favor of biofriendly alternatives as a path toward green processes. In this regard, this study aimed at evaluating the interactions of peptides, as potential floatation collectors, with quartz using phage display and molecular dynamics (MD) simulations. Quartz-selective peptide sequences were initially identified by phage display at pH = 9 and further modeled by a robust simulation scheme combining classical MD, replica exchange MD, and steered MD calculations. Our residue-specific analyses of the peptides revealed that positively charged arginine and lysine residues were favorably attracted by the quartz surface at basic pH. The negatively charged residues at pH 9 (i.e., aspartic acid and glutamic acid) further showed affinity toward the quartz surface through electrostatic interactions with the positively charged surface-bound Na⁺ ions. The best-binding heptapeptide combinations, however, contained both positively and negatively charged residues in their composition. The flexibility of peptide chains was also shown to directly affect the adsorption behavior of the peptide. While attractive intrapeptide interactions were dominated by a weak peptide-quartz binding, the repulsive self-interactions in the peptides improved the binding propensity to the quartz surface. Our results showed that MD simulations are fully capable of revealing mechanistic details of peptide adsorption to inorganic surfaces and are an invaluable tool to accelerate the rational design of peptide sequences for mineral processing applications.

Thoracic sarcopenia as a predictive factor of SARS-COV2 evolution

PURPOSE

Evaluation of CT sarcopenia as a predictor of intensive care hospitalization during SARS-COV2 infection.

MATERIALS AND METHODS

Single-center retrospective study of patients admitted to hospital with SARS-COV2 infection. The estimation of muscle mass (skeletal muscle index (SMI)) for sarcopenia, measurement of muscle density for muscle quality and body adiposity, were based on CT views on the T4 and L3 levels measured at admission. Demographic data, percentage of pulmonary parenchymal involvement as well as the orientation of patients during hospitalization and the risk of hospitalization in intensive care were collected.

RESULTS

A total of 162 patients hospitalized for SARS-COV2 infection were included (92 men and 70 women, with an average age of 64.6 years and an average BMI of 27.4). The muscle area measured at the level of L3 was significantly associated with the patient's unfavorable evolution (124.4cm2 [97; 147] vs 141.5 cm² [108; 173]) (p = 0.007), as was a lowered SMI (p < 0.001) and the muscle area measured in T4 (OR = 0.98 [0.97; 0.99]), (p = 0.026). Finally, an abdominal visceral fat area measured at the level of L3 was also associated with a risk of hospitalization in intensive care (249.4cm2 [173; 313] vs 147.5cm2 [93.1; 228] (p < 0.001).

CONCLUSION

This study demonstrates that thoracic and abdominal sarcopenia are independently associated with an increased risk of hospitalization in an intensive care unit, suggesting the need to assess sarcopenia on admission during SARS-COV2 infection.

Salient Findings on Host Range, Resistance Screening, and Molecular Studies on Sterility Mosaic Disease of Pigeonpea Induced by Pigeonpea sterility mosaic viruses (PPSMV-I and PPSMV-II)

Two distinct emaraviruses, Pigeonpea sterility mosaic virus-I (PPSMV-I) and Pigeonpea sterility mosaic virus-II (PPSMV-II) were found to be associated with sterility mosaic disease (SMD) of pigeonpea [Cajanus cajan (L.) Millsp.]. The host range of both these viruses and their vector are narrow, confined to Nicotiana benthamiana identified through mechanical transmission, and to Phaseolus vulgaris cvs. Top Crop, Kintoki, and Bountiful (F: Fabaceae) through mite transmission. A weed host Chrozophora rottleri (F: Euphorbiaceae) was also infected and tested positive for both the viruses in RT-PCR. Among the wild Cajanus species tested, Cajanus platycarpus accessions 15661, 15668, and 15671, and Cajanus scarabaeoides accessions 15683, 15686, and 15922 were infected by both the viruses and mite vector suggesting possible sources of SMD inoculum. Though accession 15666 of C. platycarpus, 15696 of C. scarabaeoides, and 15639 of Cajanus lanceolatus were infected by both the viruses, no mite infestation was observed on them. Phylogenetic analysis of nucleotide sequences of RNA-1 and RNA-2 of PPSMV-I and PPSMV-II isolates in southern India revealed significant divergence especially PPSMV-II, which is closely related to the Fig mosaic virus (FMV) than PPSMV-I. In multilocation testing of pigeonpea genotypes for their broad-based resistance to SMD for two consecutive years, genotypes ICPL-16086 and ICPL-16087 showed resistance reaction (<10% incidence) in all three locations studied. Overall, the present study gives a clear idea about the host range of PPSMV-I and PPSMV-II, their molecular relationship, and sources of resistance. This information is critical for the development of reliable diagnostic tools and improved disease management strategies.

Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations

The umbrella sampling (US) simulation is demonstrated to be an efficient approach for determining the unbinding pathway and binding affinity to the SARS-CoV-2 Mpro of small molecule inhibitors. The accuracy of US is in the same range as the linear interaction energy (LIE) and fast pulling of ligand (FPL) methods. In detail, the correlation coefficient between US and experiments does not differ from FPL and is slightly smaller than LIE. The root mean square error of US simulations is smaller than that of LIE. Moreover, US is better than FPL and poorer than LIE in classifying SARS-CoV-2 Mpro inhibitors owing to the reciever operating characteristic-area under the curve analysis. Furthermore, the US simulations also provide detailed insights on unbinding pathways of ligands from the binding cleft of SARS-CoV-2 Mpro. The residues Cys44, Thr45, Ser46, Leu141, Asn142, Gly143, Glu166, Leu167, Pro168, Ala191, Gln192 and Ala193 probably play an important role in the ligand dissociation. Therefore, substitutions at these points may change the mechanism of binding of inhibitors to SARS-CoV-2 Mpro.

Molecular characteristics of several drugs evaluated from solvent/water partition measurements: Solvation parameters and intramolecular hydrogen bond indicator

A wide set of well-known drugs, most of them included in the Abraham´s reference database, covering a wide variety of chemical structures and therapeutical functionalities were chosen in order to determine some molecular properties from solvent/water partition measurements. Partition data from aqueous solutions and four different solvents (n-dodecane, toluene, chloroform and n-octanol) were measured and reported. From them, Abraham´s molecular descriptors of selected compounds (A, B and S, accounting for hydrogen bond donor, hydrogen bond acceptor and dipolarity/polaritzability, respectively) were estimated. A and B values derived from the experimental measurements strongly agree with the tabulated ones showing the suitability of the used procedure to achieve reliable values for new molecules. However, obtained S values differ from those previously reported for several compounds. Moreover, values for a new indicator of the propensity to form intramolecular hydrogen bonds (Δlog P_oct-tol) were estimated from the experimental data and also calculated according to both, the Abraham´s model and the molecular structures (SMD). The quality of both series of calculated descriptors was evaluated by contrast with the experimental values and satisfactory results were obtained in both instances. Thus, the Abraham´s way is useful when molecular descriptors are available but very good estimations can be achieved by SMD, which only requires the drug´s molecular structure.

Application of in vitro PAMPA technique and in silico computational methods for blood-brain barrier permeability prediction of novel CNS drug candidates

Permeability assessment of small molecules through the blood-brain barrier (BBB) plays a significant role in the development of effective central nervous system (CNS) drug candidates. Since in vivo methods for BBB permeability estimation require a lot of time and resources, in silico and in vitro approaches are becoming increasingly popular nowadays for faster and more economical predictions in early phases of drug discovery. In this work, through application of in vitro parallel artificial membrane permeability assay (PAMPA-BBB) and in silico computational methods we aimed to examine the passive permeability of eighteen compounds, which affect serotonin and dopamine levels in the CNS. The data set was consisted of novel six human dopamine transporter (hDAT) substrates that were previously identified as the most promising lead compounds for further optimisation to achieve neuroprotective effect, twelve approved CNS drugs, and their related compounds. Firstly, PAMPA methods was used to experimentally determine effective BBB permeability (P_e) for all studied compounds and obtained results were further submitted for quantitative structure permeability relationship (QSPR) analysis. QSPR models were built by using three different statistical methods: stepwise multiple linear regression (MLR), partial least square (PLS), and support-vector machine (SVM), while their predictive capability was tested through internal and external validation. Obtained statistical parameters (MLR- R²_pred=-0.10; PLS- R²_pred=0.64, r²_m=0.69, r^/2_m=0.44; SVM- R²_pred=0.57, r²_m=0.72, r^/2_m=0.55) indicated that the SVM model is superior over others. The most important molecular descriptors (H₀p and SolvEMt_3D) were identified and used to propose structural modifications of the examined compounds in order to improve their BBB permeability. Moreover, steered molecular dynamics (SMD) simulation was employed to comprehensively investigate the permeability pathway of compounds through a lipid bilayer. Taken together, the created QSPR model could be used as a reliable and fast pre-screening tool for BBB permeability prediction of structurally related CNS compounds, while performed MD simulations provide a good foundation for future in silico examination.

Clinical and Laboratory Parameters Associated with Septic Myocardial Dysfunction in Children with Septic Shock

The authors' objective was to determine the association of clinical and laboratory parameters at admission with septic myocardial dysfunction (SMD) in children with septic shock. A chart review of children aged 3 mo-17 y with fluid refractory septic shock who underwent echocardiography within 3 h of admission was undertaken (2015-2017). Univariate followed by multivariate analysis was performed to identify factors associated with SMD. Of the 95 children fulfilling the inclusion criteria, SMD was diagnosed in 44 (46%) children. Children 'with SMD' had longer capillary refill time (CRT), increased lactate, lower platelet count, increased blood urea, and increased alanine aminotransferase (ALT) (p < 0.05 for all) compared to those 'without SMD'. On multivariate analysis, none of these were significant. The mortality rate was higher in those 'with SMD' than 'without SMD' [36% vs. 20% (p = 0.07)]. Prolonged CRT, increased lactate, lower platelet count, increased blood urea and elevated liver enzymes at admission may be associated with SMD in children with septic shock and may warrant early assessment of cardiac function.

Description of four patients with TRIP11 variants expand the clinical spectrum of odontochondroplasia (ODCD) and demonstrate the existence of common variants

More than two decades since the first clinical and radiological description of odontochondroplasia (ODCD) was reported, biallelic loss of function variants in the Thyroid hormone receptor interactor 11 gene (TRIP11) were identified, the same gene implicated in the lethal disorder achondrogenesis (ACG1A). Here we report the clinical and radiological follow-up of four ODCD patients, including two siblings and an adult who interestingly has the mildest form observed to date. Four TRIP11 variants were detected, two previously unreported. Subsequently, we review the clinical and radiological findings of the 14 reported ODCD patients. The majority of ODCD patients are compound heterozygotes for TRIP11 variants, 12/14 have a null allele and a splice variant whilst one is homozygous for an in-frame splicing variant, with the splice variants resulting in residual GMAP activity and hypothesized to explain why they have ODCD and not ACG1A. However, adult patient 4 has two potentially null alleles and it remains unknown why she has very mild clinical features. The c.586C>T; p.(Gln196*) variant, previously shown by mRNA studies to result in p.Val105_Gln196del, is the most frequent variant, present in seven individuals from four families, three from different regions of the world, suggesting that it may be a variant hotspot. Another variant, c.2993_2994del; p.(Lys998Serfs*5), has been observed in two individuals with a possible common ancestor. In summary, although there are clinical and radiological characteristics common to all individuals, we demonstrate that the clinical spectrum of TRIP11-associated dysplasias is even more diverse than previously described and that common genetic variants may exist.

The Research Protocol of SENIOR Project-Psychiatric Services and Support System for Serious Mental Illness in Old Age, Kerala, India

BACKGROUND

India has the second-largest population of elderly in the world. Serious mental illness (SMI) is a subset of the mental disorders that result in significant functional impairment and is usually long term. Persons with SMI face several challenges in their old age that are different from the issues faced by younger people with SMI. Understanding the problems faced by elderly individuals suffering from SMI is fundamental for planning programs to address them. The SENIOR (Support Systems Evaluation of Neuropsychiatric Illness in Old age) project is a study aimed at evaluating the problems faced in obtaining mental health care by elderly persons having SMI in the Kerala state of India.

AIM

To describe the scientific methodology of the SENIOR project.

METHODS

This study employs mixed-methods cross-sectional design among a minimum sample of 768 SMI patients identified through cluster sampling from three districts, and Focus Group Discussion among mental health program officials.

DISCUSSION

This paper presents a methodological model to assist researchers in future field epidemiological studies on mental illness. Assessing service needs and barriers to access for the most vulnerable among the mentally ill will help the policymakers make evidence-based decisions to improve their quality of life.

Estimating the ligand-binding affinity via λ-dependent umbrella sampling simulations

The umbrella sampling (US) approach has been demonstrated to be a very efficient method for estimating the ligand-binding affinity. However, most of the calculated values overestimate experimental ones that are probably caused by the inaccurate representation of the interaction between the ligand and the surrounding molecules. The issue can be resolved via the implementation aspects of λ-alteration simulation into the US approach, which we call the λ-dependent umbrella sampling (λUS) scheme. In particular, the electrostatic and van der Waals interactions were simultaneously changed by using the coupling parameter λ during λUS simulations. The mean value of obtained results, ∆ G US λ = 0.20 = - 11.59 ± 1.51 kcal mol^-1 , is in good fitting to the mean value of respective experiments, ∆G_EXP =  - 11.26 ± 0.89 kcal mol^-1 . Moreover, the correlation between the proposed approach and experiment is quite good with a value of R US λ = 0.20 = 0.82 ± 0.10 . The λUS scheme significantly enhances the calculated accuracy since the RMSE of the proposed scheme is smaller than traditional US simulations, RMSE US λ = 0.20 = 2.99 ± 0.82 kcal mol^-1 versus RMSE US λ = 0.00 = 5.48 ± 0.81 kcal mol^-1 . Furthermore, the precision is increased since the computed error via λUS approach, δ US λ = 0.20 = 1.51 kcal mol^-1 , was smaller than those of the US simulation, δ US λ = 0.00 = 1.78 kcal mol^-1 . Overall, the proposed approach perhaps provides an efficient way to accurately and precisely estimate the ligand-binding free energy.

Quantum chemical predictions of water-octanol partition coefficients applied to the SAMPL6 logP blind challenge

Theoretical approaches for predicting physicochemical properties are valuable tools for accelerating the drug discovery process. In this work, quantum chemical methods are used to predict water-octanol partition coefficients as a part of the SAMPL6 blind challenge. The SMD continuum solvent model was employed with MP2 and eight DFT functionals in conjunction with correlation consistent basis sets to determine the water-octanol transfer free energy. Several tactics towards improving the predictions of the partition coefficient were examined, including increasing the quality of basis sets, considering tautomerization, and accounting for inhomogeneities in the water and n-octanol phases. Evaluation of these various schemes highlights the impact of modeling approaches across different methods. With the inclusion of tautomers and adjustments to the permittivity constants, the best predictions were obtained with smaller basis sets and the O3LYP functional, which yielded an RMSE of 0.79 logP units. The results presented correspond to the SAMPL6 logP submission IDs: DYXBT, O7DJK, and AHMTF.

Investigation of Binding Affinity between Potential Antiviral Agents and PB2 Protein of Influenza A: Non-equilibrium Molecular Dynamics Simulation Approach

The PB2 protein of the influenza virus RNA polymerase is a major virulence determinant of influenza viruses. It binds to the cap structure at the 5' end of host mRNA to generate short capped RNA fragments that are used as primers for viral transcription named cap-snatching. A large number of the compounds were shown to bind the minimal cap-binding domain of PB2 to inhibit the cap-snatching machinery. However, their binding in the context of an extended form of the PB2 protein has remained elusive. A previous study reported some promising compounds including azaindole and hydroxymethyl azaindole, which were analyzed here to predict binding affinity to PB2 protein using the steered molecular dynamics (SMD) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods. The results show that the rupture force (F_max) value of three complexes is in agreement with the binding free energy value (ΔG_bind) estimated by the MM-PBSA method, whereas for the non-equilibrium pulling work (W_pull) value a small difference between A_PB2-4 and A_PB2-12 was observed. The binding affinity results indicate the A_PB2-12 complex is more favorable than the A_PB2-4 and A_PB2-16 complexes, which means the inhibitor (12) has the potential to be further developed as anti-influenza agents in the treatment of influenza A.

Single metal deposition versus physical developer: A comparison between two advanced fingermark detection techniques

Single metal deposition (SMD II) is a fingermark detection technique based on the use of colloidal gold. The technique has been simplified and optimised over the years to become more reliable, sensitive and user-friendly. Physical developer (PD) is a well-established detection method based on silver deposition from a redox solution. This study presents an extensive comparison of SMD II against PD for fingermark detection on porous substrates. The two techniques were compared as (i) standalone methods, (ii) in sequence after the application of routine amino acids reagents (1,2-indanedione/zinc followed by ninhydrin), and (iii) after the substrates have been wet. More than 1000 fingermark specimens were processed. Overall, the performance of SMD II was judged to be inferior to that of PD; therefore, SMD II cannot be recommended as a valid replacement for fingermark detection on porous substrates. Indanedione/zinc and ninhydrin application negatively impacts on SMD II performance and the technique gave inconsistent results across the selected range of porous substrates. Moreover, the detected fingermarks lacked contrast making their visualisation difficult. However, even if PD remains the technique of choice, SMD II showed significant potential. It proved to be less affected by donor variability and it can be applied on both porous and non-porous substrates. It did not lead to uncontrolled background staining that commonly occurs with PD. If contrast and consistency issues can be addressed in future research, SMD II may become a viable alternative to PD.

Circulating malondialdehyde concentrations in patients with stable chronic obstructive pulmonary disease: a systematic review and meta-analysis

The aim of this meta-analysis was to review the available evidence regarding the blood concentrations of the oxidative stress marker malondialdehyde (MDA) in chronic obstructive pulmonary disease (COPD) patients in comparison to healthy individuals. 14 studies were included in the meta-analysis (from inception to October 2017) with a total of 817 COPD patients and 530 healthy controls. Pooled MDA concentrations were significantly higher in patients with COPD than controls (standardized mean differences = 2.39 μmol/l, 95% CI: 1.50-3.28 μmol/l; p < 0.001). Our meta-analysis showed that the blood concentrations of MDA are consistently higher in patients with COPD when compared with healthy controls, suggesting an important role of lipid peroxidation, and thus oxidative stress, in the pathogenesis of COPD.

Residual Error Based Anomaly Detection Using Auto-Encoder in SMD Machine Sound

Detecting an anomaly or an abnormal situation from given noise is highly useful in an environment where constantly verifying and monitoring a machine is required. As deep learning algorithms are further developed, current studies have focused on this problem. However, there are too many variables to define anomalies, and the human annotation for a large collection of abnormal data labeled at the class-level is very labor-intensive. In this paper, we propose to detect abnormal operation sounds or outliers in a very complex machine along with reducing the data-driven annotation cost. The architecture of the proposed model is based on an auto-encoder, and it uses the residual error, which stands for its reconstruction quality, to identify the anomaly. We assess our model using Surface-Mounted Device (SMD) machine sound, which is very complex, as experimental data, and state-of-the-art performance is successfully achieved for anomaly detection.

Partition coefficients for the SAMPL5 challenge using transfer free energies

SAMPL challenges (Mobley et al. in J Comput Aided Mol Des 28:135-150, 2014; Skillman in J Comput Aided Mol Des 26:473-474, 2012; Geballe in J Comput Aided Mol Des 24:259-279, 2010; Guthrie in J Phys Chem B 113:4501-4507, 2009) provide excellent opportunities to assess theoretical approaches on new data sets with a goal of gaining greater insight towards protein and ligand modeling. In the SAMPL5 experiment, cyclohexane-water partition coefficients were determined using a vertical solvation scheme in conjunction with the SMD continuum solvent model. Several DFT functionals partnered with correlation consistent basis sets were evaluated for the prediction of the partition coefficients. The approach chosen for the competition, a B3PW91 vertical solvation scheme, yields a mean absolute deviation of 1.9 logP units and performs well at estimating the correct hydrophilicity and hydrophobicity for the full SAMPL5 molecule set.

Steered molecular dynamics analysis of the role of cofilin in increasing the flexibility of actin filaments

Cofilin is one of the most essential regulatory proteins and participates in the process of disassembling actin filaments. Cofilin induces conformational changes to actin filaments, and both the bending and torsional rigidity of the filament. In this study, we investigate the effects of cofilin on the mechanical properties of actin filaments using computational methods. Three models defined by their number of bound cofilins are constructed using coarse-grained MARTINI force field, and they are then extended with steered molecular dynamics simulation. After obtaining the stress-strain curves of the models, we calculate their Young's moduli and other mechanical properties that have not yet been determined for actin filaments. We analyze the cause of the different behaviors of the three models based on their atomistic geometrical differences. Finally, it is demonstrated that cofilin binding causes changes in the distances, angles, and stabilities of the residues in actin filaments.

Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model

We present blind predictions using the solubility parameter based method MOSCED submitted for the SAMPL5 challenge on calculating cyclohexane/water distribution coefficients at 298 K. Reference data to parameterize MOSCED was generated with knowledge only of chemical structure by performing solvation free energy calculations using electronic structure calculations in the SMD continuum solvent. To maintain simplicity and use only a single method, we approximate the distribution coefficient with the partition coefficient of the neutral species. Over the final SAMPL5 set of 53 compounds, we achieved an average unsigned error of [Formula: see text] log units (ranking 15 out of 62 entries), the correlation coefficient (R) was [Formula: see text] (ranking 35), and [Formula: see text] of the predictions had the correct sign (ranking 30). While used here to predict cyclohexane/water distribution coefficients at 298 K, MOSCED is broadly applicable, allowing one to predict temperature dependent infinite dilution activity coefficients in any solvent for which parameters exist, and provides a means by which an excess Gibbs free energy model may be parameterized to predict composition dependent phase-equilibrium.

A Meta-Analysis of C-Reactive Protein in Patients With Alzheimer's Disease

Inflammation may be associated with Alzheimer's disease (AD). This meta-analysis aimed to compare the level of C-reactive protein (CRP) in patients having AD to healthy controls. A total of 10 cross-sectional studies (n = 2093) were identified from PubMed and EMBASE after systematic searching and evaluation. The combined standardized mean difference (SMD) of CRP level between the disease and control group was analyzed. In the meta-analysis, there was no significant difference in serum between the CRP level of patients with AD and that of healthy controls (SMD: -0.400, 95% confidence interval [CI]: -0.827 to 0.027,P= .066). However, when we stratified the studies by Mini-Mental State Examination (MMSE) scores, the level of CRP in the mild and moderate dementia subgroup (MMSE ≥ 10) was significantly lower than that in the control group (SMD: -0.582, 95% CI: -0.957 to -0.208,P= .002). Therefore, the diagnostic value of CRP for mild and moderate AD may be useful in clinical practice.

Aqueous acidities of primary benzenesulfonamides: Quantum chemical predictions based on density functional theory and SMD

Aqueous pK(a) of selected primary benzenesulfonamides are predicted in a systematic manner using density functional theory methods and the SMD solvent model together with direct and proton exchange thermodynamic cycles. Some test calculations were also performed using high-level composite CBS-QB3 approach. The direct scheme generally does not yield a satisfactory agreement between calculated and measured acidities due to a severe overestimation of the Gibbs free energy changes of the gas-phase deprotonation reaction by the used exchange-correlation functionals. The relative pK(a) values calculated using proton exchange method compare to experimental data very well in both qualitative and quantitative terms, with a mean absolute error of about 0.4 pK(a) units. To achieve this accuracy, we find it mandatory to perform geometry optimization of the neutral and anionic species in the gas and solution phases separately, because different conformations are stabilized in these two cases. We have attempted to evaluate the effect of the conformer-averaged free energies in the pK(a) predictions, and the general conclusion is that this procedure is highly too costly as compared with the very small improvement we have gained.

The C-terminal binding protein (CTBP-1) regulates dorsal SMD axonal morphology in Caenorhabditis elegans

C-terminal binding proteins (CtBPs) are transcriptional co-repressors which cooperate with a variety of transcription factors to repress gene expression. Caenorhabditis elegans CTBP-1 expression has been observed in the nervous system and hypodermis. In C. elegans, CTBP-1 regulates several processes including Acute Functional Tolerance to ethanol and functions in the nervous system to modulate both lifespan and expression of a lipase gene called lips-7. Incorrect structure and/or function of the nervous system can lead to behavioral changes. Here, we demonstrate reduced exploration behavior in ctbp-1 mutants. Our examination of a subset of neurons involved in regulating locomotion revealed that the axonal morphology of dorsal SMD (SMDD) neurons is altered in ctbp-1 mutants at the fourth larval (L4) stage. Expressing CTBP-1 under the control of the endogenous ctbp-1 promoter rescued both the exploration behavior phenotype and defective SMDD axon structure in ctbp-1 mutants at the L4 stage. Interestingly, the pre-synaptic marker RAB-3 was found to localize to the mispositioned portion of SMDD axons in a ctbp-1 mutant. Further analysis of SMDD axonal morphology at days 1, 3 and 5 of adulthood revealed that the number of ctbp-1 mutants showing an SMDD axonal morphology defect increases in early adulthood and the observed defect appears to be qualitatively more severe. CTBP-1 is prominently expressed in the nervous system with weak expression detected in the hypodermis. Surprisingly, solely expressing CTBP-1a in the nervous system or hypodermis did not restore correct SMDD axonal structure in a ctbp-1 mutant. Our results demonstrate a role for CTBP-1 in exploration behavior and the regulation of SMDD axonal morphology in C. elegans.

The unbinding studies of vascular endothelial growth factor receptor-2 protein tyrosine kinase type II inhibitors

Vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase has two conformations, active and inactive conformations. Type II inhibitors bind to inactive conformation. It has two possible binding/unbinding paths. To explore the unbinding path of inhibitor 01-435 that was generated by fragment build in the binding pocket of VEGFR-2, molecular dynamics (MD) simulation was performed on the crystal structure of VEGFR-2 in complex with 01-435, then steered molecular dynamics (SMD) simulation was executed on the crystal structure of VEGFR-2 in complex with 01-435. Pull force, van der Waals and electrostatic interaction along the two paths were calculated by using SMD simulation. The SMD simulation results indicate that the more favorable path for inhibitor dissociation is along with the traditional ATP-channel rather than the allosteric-pocket-channel, which is mainly due to the less electrostatic interaction that the ligand suffers during dissociation process along the traditional ATP-channel.

Meta-analysis: aerobic exercise for the treatment of anxiety disorders

BACKGROUND

This meta-analysis investigates the efficacy of exercise as a treatment for DSM-IV diagnosed anxiety disorders.

METHODS

We searched PubMED and PsycINFO for randomized, controlled trials comparing the anxiolytic effects of aerobic exercise to other treatment conditions for DSM-IV defined anxiety disorders. Seven trials were included in the final analysis, totaling 407 subjects. The control conditions included non-aerobic exercise, waitlist/placebo, cognitive-behavioral therapy, psychoeducation and meditation. A fixed-effects model was used to calculate the standardized mean difference of change in anxiety rating scale scores of aerobic exercise compared to control conditions. Subgroup analyses were performed to examine the effects of (1) comparison condition; (2) whether comparison condition controlled for time spent exercising and (3) diagnostic indication.

RESULTS

Aerobic exercise demonstrated no significant effect for the treatment of anxiety disorders (SMD=0.02 (95%CI: -0.20-0.24), z = 0.2, p = 0.85). There was significant heterogeneity between trials (χ(2) test for heterogeneity = 22.7, df = 6, p = 0.001). The reported effect size of aerobic exercise was highly influenced by the type of control condition. Trials utilizing waitlist/placebo controls and trials that did not control for exercise time reported large effects of aerobic exercise while other trials report no effect of aerobic exercise.

CONCLUSIONS

Current evidence does not support the use of aerobic exercise as an effective treatment for anxiety disorders as compared to the control conditions. This remains true when controlling for length of exercise sessions and type of anxiety disorder. Future studies evaluating the efficacy of aerobic exercise should employ larger sample sizes and utilize comparison interventions that control for exercise time.

Growth factors in preeclampsia: a vascular disease model. A failed vasodilation and angiogenic challenge from pregnancy onwards?

Preeclampsia is the major cause of maternofetal and neonatal morbi-mortality including intrauterine growth retardation, miscarriages and stillbirths. Inadequate vascular dilation and angiogenesis represent the crucial underlying defect of gravidic hypertension, denoting a failed response to the vasodilatory and pro-angiogenic challenge imposed by pregnancy, especially if multifetal. A similar pathogenesis appears involved in gestational diabetes. In this review we aimed to provide a hint on understanding the deeply involved angiogenic disorders which eventually culminate in utero-placental failure. The key players in these complex processes may be found in an intricate network of growth factors (GFs) and GF inhibitors, controlled by several vascular risk factors modulated by environment and genes, which eventually impact on early and late cardiovascular outcomes of mother and fetus.

Resolution of a Challenge for Solvation Modeling: Calculation of Dicarboxylic Acid Dissociation Constants Using Mixed Discrete-Continuum Solvation Models

First and second dissociation constants (pKa values) of oxalic acid, malonic acid, and adipic acid were computed by using a number of theoretical protocols based on density functional theory and using both continuum solvation models and mixed discrete-continuum solvation models. We show that fully implicit solvation models (in which the entire solvent is represented by a dielectric continuum) fail badly for dicarboxylic acids with mean unsigned errors (averaged over six pKa values) of 2.4-9.0 log units, depending on the particular implicit model used. The use of water-solute clusters and accounting for multiple conformations in solution significantly improve the performance of both generalized Born solvation models and models that solve the nonhomogeneous dielectric Poisson equation for bulk electrostatics. The four most successful models have mean unsigned errors of only 0.6-0.8 log units.