Selective Vapor Condensation for the Synthesis and Assembly of Spherical Colloids with a Precise Rough Patch.

Patchy particles occupy an increasingly important space in soft matter research due to their ability to assemble into intricate phases and states. Being able to fine-tune the interactions among these particles is essential to understanding the principles governing the self-assembly processes. However, current fabrication techniques often yield patches that deviate chemically and physically from the native particles, impeding the identification of the driving forces behind self-assembly. To overcome this challenge, we propose a new approach to synthesizing spherical colloids with a well-defined rough patch on their surface. By treating polystyrene microspheres with vapors of a good solvent, here an acetone-water mixture, we achieve selective polymer corrugation on the particle surface resulting in a chemically similar yet rough surface patch. The key step is the selective condensation of the acetone-water vapors on the apex of the polystyrene microparticles immobilized on a substrate, which leads to rough patch formation. We leverage the ability to tune the vapor-liquid equilibrium of the volatile acetone-water mixture to precisely control the polymer corrugation on the particle surface. We demonstrate the dependence of patch formation on particle and substrate wettability, with the condensation occurring on the particle apex only when it is more wettable than the substrate, which is consistent with Volmer's classical nucleation theory. By combining experiments and molecular dynamics simulations, we identify the role of the rough patch in the depletion interaction-driven self-assembly of the microspheres, which is crucial for designing programmable supracolloidal structures.

Overexpression of Aurora Kinase B Is Correlated with Diagnosis and Poor Prognosis in Hepatocellular Carcinoma.

Aurora kinase B (AURKB) overexpression promotes tumor initiation and development by participating in the cell cycle. In this study, we focused on the mechanism of AURKB in hepatocellular carcinoma (HCC) progression and on AURKB's value as a diagnostic and prognostic biomarker in HCC. We used data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) to analyze AURKB expression in HCC. We found that the expression levels of AURKB in HCC samples were higher than those in the corresponding control group. R packages were used to analyze RNA sequencing data to identify AURKB-related differentially expressed genes (DEGs), and these genes were found to be significantly enriched during the cell cycle. The biological function of AURKB was verified, and the results showed that cell proliferation was slowed down and cells were arrested in the G2/M phase when AURKB was knocked down. AURKB overexpression resulted in significant differences in clinical symptoms, such as the clinical T stage and pathological stage. Kaplan-Meier survival analysis, Cox regression analysis, and Receiver Operating Characteristic (ROC) curve analysis suggested that AURKB overexpression has good diagnostic and prognostic potential in HCC. Therefore, AURKB may be used as a potential target for the diagnosis and cure of HCC.

Active learning of the thermodynamics-dynamics trade-off in protein condensates.

Phase-separated biomolecular condensates exhibit a wide range of dynamic properties, which depend on the sequences of the constituent proteins and RNAs. However, it is unclear to what extent condensate dynamics can be tuned without also changing the thermodynamic properties that govern phase separation. Using coarse-grained simulations of intrinsically disordered proteins, we show that the dynamics and thermodynamics of homopolymer condensates are strongly correlated, with increased condensate stability being coincident with low mobilities and high viscosities. We then apply an "active learning" strategy to identify heteropolymer sequences that break this correlation. This data-driven approach and accompanying analysis reveal how heterogeneous amino acid compositions and nonuniform sequence patterning map to a range of independently tunable dynamic and thermodynamic properties of biomolecular condensates. Our results highlight key molecular determinants governing the physical properties of biomolecular condensates and establish design rules for the development of stimuli-responsive biomaterials.

A Prediction Model for Sight-Threatening Diabetic Retinopathy Based on Plasma Adipokines among Patients with Mild Diabetic Retinopathy.

Background: Accumulating evidence has suggested a link between adipokines and diabetic retinopathy (DR). This study is aimed at investigating the risk factors for sight-threatening DR (STDR) and establishing a prognostic model for predicting STDR among a high-risk population of patients with type 2 diabetes mellitus (T2DM). Methods: Plasma concentrations of adipokines were determined by enzyme-linked immunosorbent assay. In the case-control set, principal component analysis (PCA) was performed to select optimal predictive cytokines for STDR, involving severe nonproliferative DR (NPDR) and proliferative DR. Support vector machine (SVM) was used to examine the possible combination of baseline plasma adipokines to discriminate the patients with mild NPDR who will later develop STDR. An individual prospective cohort with a follow-up period of 3 years was used for the external validation. Results: In both training and testing sets, involving 306 patients with T2DM, median levels of plasma adiponectin (APN), leptin, and fatty acid-binding protein 4 (FABP4) were significantly higher in the STDR group than those in mild NPDR. Except for adipsin, the other three adipokines, FABP4, APN, and leptin, were selected by PCA and integrated into SVM. The accuracy of the multivariate SVM classification model was acceptable in both the training set (AUC = 0.81, sensitivity = 71%, and specificity = 91%) and the testing set (AUC = 0.77, sensitivity = 61%, and specificity = 92%). 110 T2DM patients with mild NPDR, the high-risk population of STDR, were enrolled for external validation. Based on the SVM, the risk of each patient was calculated. More STDR occurred in the high-risk group than in the low-risk group, which were grouped by the median value of APN, FABP4, and leptin, respectively. The model was validated in an individual cohort using SVM with the AUC, sensitivity, and specificity reaching 0.77, 64%, and 91%, respectively. Conclusions: Adiponectin, leptin, and FABP4 were demonstrated to be associated with the severity of DR and maybe good predictors for STDR, suggesting that adipokines may play an important role in the pathophysiology of DR development.

Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis.

Introduction: Coronavirus disease 2019 (COVID-19) has become a global pandemic and poses a serious threat to human health. Many studies have shown that pre-existing nonalcoholic steatohepatitis (NASH) can worsen the clinical symptoms in patients suffering from COVID-19. However, the potential molecular mechanisms between NASH and COVID-19 remain unclear. To this end, key molecules and pathways between COVID-19 and NASH were herein explored by bioinformatic analysis. Methods: The common differentially expressed genes (DEGs) between NASH and COVID-19 were obtained by differential gene analysis. Enrichment analysis and protein-protein interaction (PPI) network analysis were carried out using the obtained common DEGs. The key modules and hub genes in PPI network were obtained by using the plug-in of Cytoscape software. Subsequently, the hub genes were verified using datasets of NASH (GSE180882) and COVID-19 (GSE150316), and further evaluated by principal component analysis (PCA) and receiver operating characteristic (ROC). Finally, the verified hub genes were analyzed by single-sample gene set enrichment analysis (ssGSEA) and NetworkAnalyst was used for the analysis of transcription factor (TF)-gene interactions, TF-microRNAs (miRNA) coregulatory network, and Protein-chemical Interactions. Results: A total of 120 DEGs between NASH and COVID-19 datasets were obtained, and the PPI network was constructed. Two key modules were obtained via the PPI network, and enrichment analysis of the key modules revealed the common association between NASH and COVID-19. In total, 16 hub genes were obtained by five algorithms, and six of them, namely, Kruppel-like factor 6 (KLF6), early growth response 1 (EGR1), growth arrest and DNA-damage-inducible 45 beta (GADD45B), JUNB, FOS, and FOS-like antigen 1 (FOSL1) were confirmed to be closely related to NASH and COVID-19. Finally, the relationship between hub genes and related pathways was analyzed, and the interaction network of six hub genes was constructed with TFs, miRNAs, and compounds. Conclusion: This study identified six hub genes related to COVID-19 and NASH, providing a new perspective for disease diagnosis and drug development.

Synergistic Role of Temperature and Salinity in Aggregation of Nonionic Surfactant-Coated Silica Nanoparticles.

The adsorption of nonionic surfactants onto hydrophilic nanoparticles (NPs) is anticipated to increase their stability in aqueous medium. While nonionic surfactants show salinity- and temperature-dependent bulk phase behavior in water, the effects of these two solvent parameters on surfactant adsorption and self-assembly onto NPs are poorly understood. In this study, we combine adsorption isotherms, dispersion transmittance, and small-angle neutron scattering (SANS) to investigate the effects of salinity and temperature on the adsorption of pentaethylene glycol monododecyl ether (C12E5) surfactant on silica NPs. We find an increase in the amount of surfactant adsorbed onto the NPs with increasing temperature and salinity. Based on SANS measurements and corresponding analysis using computational reverse-engineering analysis of scattering experiments (CREASE), we show that the increase in salinity and temperature results in the aggregation of silica NPs. We further demonstrate the non-monotonic changes in viscosity for the C12E5-silica NP mixture with increasing temperature and salinity and correlate the observations to the aggregated state of NPs. The study provides a fundamental understanding of the configuration and phase transition of the surfactant-coated NPs and presents a strategy to manipulate the viscosity of such dispersion using temperature as a stimulus.

Thyroid hormone resistance syndrome due to a novel heterozygous mutation and concomitant Hashimoto's Thyroiditis: A pedigree report.

Thyroid hormone resistance syndrome (THRS) is a rare disease characterized by reduced sensitivity to thyroid hormones. Mutations in the thyroid hormone receptor beta (THRB) gene are considered as contributing to the pathogenesis. This report describes a Chinese pedigree with THRS and Hashimoto's thyroiditis (HT) due to novel point mutation in the 11th exon of the THRB gene (c. 1378 G > A). The proband complained of goitre with increased thyroid hormone and normal thyroid stimulating hormone levels. Gene sequencing was performed to confirm the diagnosis. HT was also diagnosed based on positive thyroid autoantibodies and diffuse, grid-like changes in the thyroid on ultrasound examination. Additionally, a comprehensive examination of the proband's pedigree was conducted. The patient's father exhibited the same gene mutation site and was diagnosed with THRS and HT. No mutation site was detected in three patients with HT only and three healthy volunteers. Thus, gene sequencing should be considered the gold standard for diagnosing THRS. Furthermore, treatment should be individualized to control the patient's symptoms rather than normalizing thyroid hormone levels. Further studies that determine the relationship between THRS and TH are warranted.

The Association Between Fecal Short-Chain Fatty Acids, Gut Microbiota, and Visceral Fat in Monozygotic Twin Pairs.

PURPOSE: To examine the association of short-chain fatty acids (SCFAs), gut microbiota and obesity in individual twins and to control for genetic and shared environmental effects by studying monozygotic intrapair differences. PATIENTS AND METHODS: The study recruited 20 pairs of monozygotic twins. Body composition measurements were performed by using the multi-frequency bioelectrical impedance technique. SCFAs were extracted from feces and quantified by gas chromatography-mass spectrometer. Gut microbiota was evaluated by 16S rRNA gene sequencing. RESULTS: Fecal SCFAs were negatively correlated with adiposity parameters including body mass index, visceral adipose tissue and waist circumference (all P < 0.05). Metastat analysis showed that the top 5 relatively abundant bacterial taxa of viscerally obese and non-obese groups were Bacteroides, Collinsella, Eubacterium rectale group, Lachnoclostridium, and Tyzzerella. Participants with visceral obesity had lower abundance of Bacteroides and Collinsella compared to non-obese patients (P < 0.05). Among them, the abundance of Collinsella was positively correlated with acetic acid concentrations (r = 0.63, P = 0.011). There were no significant intrapair differences in each SCFA concentrations between the twins in our study (P > 0.05). CONCLUSION: Low fecal concentrations of SCFAs were associated with visceral obesity, and the gut microbiota might be involved in the underlying mechanism.

Increased Arterial Stiffness as a Predictor for Onset and Progression of Diabetic Retinopathy in Type 2 Diabetes Mellitus.

INTRODUCTION: Brachial-ankle pulse wave velocity (baPWV), an indicator of arterial stiffness, has been demonstrated to be associated with type 2 diabetes mellitus (T2DM) and its vascular complications. This study was aimed at investigating the correlations of baPWV with both the presence and severity of diabetic retinopathy (DR) at baseline and at exploring the predictive role of baPWV in the new onset/progression of DR in the follow-up analysis. METHODS: The prospective cohort study recruited 2,473 Chinese patients with T2DM, of whom 663 participants were finally included in the follow-up analysis. The presence and grading of DR were performed by the modified Early Treatment Diabetic Retinopathy Study. Uni- or multivariate linear and logistic regression models and Cox proportional-hazards regression analysis were conducted. RESULTS: Of 2,473 patients with T2DM at baseline, 734 individuals were assessed to have DR and further categorized into 630 with non-sight-threatening DR (NSTDR) and 104 with STDR. In addition to the positive relationship between increased baPWV and the presence of DR, multinominal logistic regression analysis revealed that higher tertiles of baPWV were significantly related to the NSTDR (T2: OR = 1.62 (1.22, 2.15), p < 0.001, and T3: OR = 2.58 (1.86, 3.58), p < 0.001) and STDR group (T3: OR = 3.87 (1.87, 8.02), p < 0.001). During a follow-up (mean period of 16.4 months), 111 participants had new onset/progression of DR. The cox regressions showed that high baseline baPWV was correlated with increased risk of development/progression of DR (HR = 2.24, 95% CI (1.24, 4.03), p = 0.007, for T2 baPWV and HR = 2.90, 95% CI (1.49, 5.64), p = 0.002, for T3 baPWV) after adjustments for multiple factors. CONCLUSIONS: Our results demonstrated that baseline baPWV might be an independent predictor in new onset/worsening of DR, suggesting that increased arterial stiffness might be involved in the development of DR. Follow-up studies with a longer duration are needed.

Metabolites of gut microbiome are associated with glucose metabolism in non-diabetic obese adults: a Chinese monozygotic twin study.

BACKGROUND: Evidence suggests gut microbiome is associated with diabetes. However, it's unclear whether the association remains in non-diabetic participants. A Chinese monozygotic twin study, in which the participants are without diabetes, and are not taking any medications, was conducted to explore the potential association. METHODS: Nine pairs of adult monozygotic twins were enrolled and divided into two twin-pair groups (a and b). Clinical and laboratory measurements were conducted. Visceral adipose tissue (VAT) was assessed. Fecal samples were collected to analyze the microbiome composition by 16S rDNA gene amplicon sequencing. Liquid chromatography mass spectrometry was performed to detect the metabolites. RESULTS: The participants aged 53 years old averagely, with 8 (88.9%) pairs were women. All the participants were obese with VAT higher than 100 cm2 (152.2 ± 31.6). There was no significant difference of VAT between the twin groups (153.6 ± 30.4 cm2 vs. 150.8 ± 29.5 cm2, p = 0.54). Other clinical measurements, including BMI, lipid profiles, fasting insulin and blood glucose, were also not significantly different between groups (p ≥ 0.056), whereas HbA1c level of group a is significantly higher than group b (5.8 ± 0.3% vs. 5.6 ± 0.2%, p = 0.008). The number and richness of OTUs are relatively higher in group a, and 13 metabolites were significantly different between two groups. Furthermore, several of the 13 metabolites could be significantly linked to special taxons. The potential pathway involved drug metabolism-other enzymes, Tryptophan metabolism and Citrate cycle. CONCLUSIONS: Gut microbiome composition and their metabolites may modulate glucose metabolism in obese adults without diabetes, through Tryptophan metabolism, Citrate cycle and other pathways.

Low serum levels of bone turnover markers are associated with perirenal fat thickness in patients with type 2 diabetes mellitus.

BACKGROUND: Obesity is known as a common risk factor for osteoporosis and type 2 diabetes mellitus (T2DM). Perirenal fat, surrounding the kidneys, has been reported to be unique in anatomy and biological functions. This study aimed to explore the relationship between perirenal fat and bone metabolism in patients with T2DM. METHODS: A total of 234 patients with T2DM were recruited from September 2019 to December 2019 in the cross-sectional study. The biochemical parameters and bone turnover markers (BTMs) were determined in all participants. Perirenal fat thickness (PrFT) was performed by ultrasounds via a duplex Doppler apparatus. Associations between PrFT and bone metabolism index were determined via correlation analysis and regression models. RESULTS: The PrFT was significantly correlated with ß-C-terminal telopeptides of type I collagen (ß-CTX) (r = -0.14, P < 0.036), parathyroid hormone (iPTH) (r = -0.18, P ≤ 0.006), and 25 hydroxyvitamin D (25-OH-D) (r = -0.14, P = 0.001). Multivariate analysis confirmed that the association of PrFT and ß-CTX (ß = -0.136, P = 0.042) was independent of other variables. CONCLUSION: This study showed a negative and independent association between PrFT and ß-CTX in subjects with T2DM, suggesting a possible role of PrFT in bone metabolism. Follow-up studies and further research are necessary to validate the associations and to elucidate the underlying mechanisms.

Low serum levels of bone turnover markers are associated with the presence and severity of diabetic retinopathy in patients with type 2 diabetes mellitus.

BACKGROUND: Accumulating evidence demonstrates an association of type 2 diabetes mellitus (T2DM) and its microvascular complications with increased fracture risk. In this study, we aimed to evaluate the relationships between serum concentrations of bone turnover markers and the presence and/or severity of diabetic retinopathy (DR) among patients with T2DM. METHODS: A total of 285 patients with T2DM comprising 168 patients without DR and 117 patients with DR were enrolled in the cross-sectional study. In the latter group, patients were further divided into patients of mild and severe DR stages. The biochemical parameters and bone turnover markers were determined in all participants. RESULTS: This study found that serum levels of procollagen type 1 N-terminal propeptide (P1NP), a bone formation marker, and the bone resorption marker serum ß-cross-linked C-telopeptide of type I collagen (ß-CTX) were more decreased in diabetic patients with DR than in those without DR, with differences remaining significant (P < .05) in multivariate linear regression models after adjustments for multiple confounding factors. Osteocalcin and ß-CTX levels were further reduced along with the severity of DR among participants with DR. Moreover, multivariate logistic regression analysis revealed that lower serum levels of P1NP and ß-CTX were associated with higher odds for the presence of DR, while ß-CTX was associated with the severity of DR. CONCLUSION: Our results suggest that the development of DR might be involved in the progression of T2DM-induced deficits in bone formation and resorption or vice versa. Follow-up studies and further research are necessary to validate the associations and elucidate the underlying mechanisms.

A combined experimental and computational approach reveals how aromatic peptide amphiphiles self-assemble to form ion-conducting nanohelices.

Reported here is a combined experimental-computational strategy to determine structure-property-function relationships in persistent nanohelices formed by a set of aromatic peptide amphiphile (APA) tetramers with the general structure K S XEK S , where KS= S-aroylthiooxime modified lysine, X = glutamic acid or citrulline, and E = glutamic acid. In low phosphate buffer concentrations, the APAs self-assembled into flat nanoribbons, but in high phosphate buffer concentrations they formed nanohelices with regular twisting pitches ranging from 9-31 nm. Coarse-grained molecular dynamics simulations mimicking low and high salt concentrations matched experimental observations, and analysis of simulations revealed that increasing strength of hydrophobic interactions under high salt conditions compared with low salt conditions drove intramolecular collapse of the APAs, leading to nanohelix formation. Analysis of the radial distribution functions in the final self-assembled structures led to several insights. For example, comparing distances between water beads and beads representing hydrolysable KS units in the APAs indicated that the KS units in the nanohelices should undergo hydrolysis faster than those in the nanoribbons; experimental results verified this hypothesis. Simulation results also suggested that these nanohelices might display high ionic conductivity due to closer packing of carboxylate beads in the nanohelices than in the nanoribbons. Experimental results showed no conductivity increase over baseline buffer values for unassembled APAs, a slight increase (0.4 × 102 µS/cm) for self-assembled APAs under low salt conditions in their nanoribbon form, and a dramatic increase (8.6 × 102 µS/cm) under high salt conditions in their nanohelix form. Remarkably, under the same salt conditions, these self-assembled nanohelices conducted ions 5-10-fold more efficiently than several charged polymers, including alginate and DNA. These results highlight how experiments and simulations can be combined to provide insight into how molecular design affects self-assembly pathways; additionally, this work highlights how this approach can lead to discovery of unexpected properties of self-assembled nanostructures.

The Composition of Gut Microbiota in Patients Bearing Hashimoto's Thyroiditis with Euthyroidism and Hypothyroidism.

AIMS: Hashimoto's thyroiditis (HT), a type of autoimmune disease, occurs due to genetic predisposition and environmental factors. It is well known that thyroid function may affect the gut microbiota. However, the composition of gut microbiota in HT patients with different thyroid function status has been less highlighted. Therefore, we focused on the alterations in the composition of gut microbiota in HT patients with euthyroidism and hypothyroidism. METHODS: We performed a cross-sectional study, including 45 HT patients with euthyroidism, 18 HT patients with hypothyroidism, and 34 healthy controls. Fecal samples were collected, and microbiota was examined by using 16S RNA ribosomal RNA gene sequencing. Then, we analyzed the possible pathways in relation to the enriched bacteria by linear discriminant analysis (LDA) effect size (LEfSe). RESULTS: Compared with the controls, bacterial richness and diversity were significantly lower in patients with HT, especially in hypothyroidism. Moreover, Lachnospiraceae_incertae_sedis, Lactonifactor, Alistipes, and Subdoligranulum were more enriched in HT patients with euthyroidism, while Phascolarctobacterium was more abundant in those with hypothyroidism. Further analysis suggested that Phascolarctobacterium was negatively related to several pathways, including environmental information processing and metabolism. CONCLUSION: In summary, our study demonstrated the altered composition of gut microbiota in HT patients with different thyroid function status. Moreover, Phascolarctobacterium may be involved in the development of HT.

Machine learning approach for accurate backmapping of coarse-grained models to all-atom models.

Four different machine learning (ML) regression models: artificial neural network, k-nearest neighbors, Gaussian process regression and random forest were built to backmap coarse-grained models to all-atom models. The ML models showed better predictions than the existing backmapping approaches for selected structures, suggesting the applications of the ML models for backmapping.

Orlistat-Induced Gut Microbiota Modification in Obese Mice.

INTRODUCTION: Accumulating evidence has indicated that alterations of gut microbiota have been involved in various metabolic diseases. Orlistat, a reversible inhibitor of pancreatic and gastric lipase, has beneficial effects on weight loss and metabolism. However, the effect of orlistat on the composition of gut microbiota remains unclear. OBJECTIVE: We aimed to explore the effect of orlistat on gut microbiota in high-fat diet (HFD) fed C57BL/6J obese mice. METHODS: C57BL/6J mice were randomly divided into three groups: control (NCD), HFD, and HFD + orlistat (ORL). Mice in the NCD group were fed chow diet, while the other groups were fed HFD for 6 months, and orlistat was added in the final 3 months in the HFD + ORL group. After sacrifice, body weight and metabolic parameters were assessed, and the gut microbial composition was analyzed by 16S rRNA gene sequencing. RESULTS: Orlistat treatment exerted beneficial effects on body weight, plasma cholesterol, and glucose tolerance. Meanwhile, orlistat treatment modified the gut microbiota, presenting as reduced total microbial abundance and obvious upregulated bacteria. Moreover, the upregulated bacteria correlated with several metabolic pathways. CONCLUSIONS: Orlistat may exert beneficial effects on body weight and glucose tolerance through modifying the composition of gut microbiota.

Solvation dynamics of N-substituted acrylamide polymers and the importance for phase transition behavior.

Functional groups present in thermo-responsive polymers are known to play an important role in aqueous solutions by manifesting their coil-to-globule conformational transition in a specific temperature range. Understanding the role of these functional groups and their interactions with water is of great interest as it may allow us to control both the nature and temperature of this coil-to-globule transition. In this work, polyacrylamide (PAAm), poly(N-isopropylacrylamide) (PNIPAm), and poly(N-isopropylmethacrylamide) (PNIPMAm) solvated in water are studied with the goal of discovering the structure of the solvent and its interaction with these polymers in determining the polymer conformations. Specifically, all-atom molecular dynamics (MD) simulations were performed on polymer chains with 30 monomer units (30-mers) at 295 K, 310 K and 320 K, which is below and above the lower critical solution temperature (LCST) of PNIPAm (LCST = 305 K) and PNIPMAm (LCST = 315 K), respectively. The MD simulation trajectories suggest that changes in the functional groups in the backbone and side-chains alter the water solvation shell around the polymer. This results in a change in the residence time probability and hydrogen bond characteristics of water at simulated temperatures. Specifically, water molecules reside for longer times near PAAm (no LCST) and PNIPMAm (LCST = 315 K) chains as compared to PNIPAm. This might be one of the possible causes for the higher LCST of PNIPMAm as compared to that of PNIPAm. These results can guide experimentalists and theoreticians to design new polymer structures with tailor-made LCST transitions while controlling the water solvation shell around the functional group.

Machine-Learning Based Stacked Ensemble Model for Accurate Analysis of Molecular Dynamics Simulations.

Accurate, faster, and on-the-fly analysis of the molecular dynamics (MD) simulations trajectory becomes very critical during the discovery of new materials or while developing force-field parameters due to automated nature of these processes. Here to overcome the drawbacks of algorithm based analysis approaches, we have developed and utilized an approach that integrates machine-learning (ML) based stacked ensemble model (SEM) with MD simulations, for the first time. As a proof-of-concept, two SEMs were developed to analyze two dynamical properties of a water droplet, its contact angle, and hydrogen bonds. The two SEMs consisted of two layered networks of random forest, artificial neural network, support vector regression, Kernel ridge regression, and k-nearest neighbors ML models. The root-mean-square error values, uncertainty quantification, and sensitivity analysis of both the SEMs suggested that the final result was more accurate as compared to that of the individual ML models. This new computational framework is very general, robust, and has a huge potential in analyzing large size MD simulation trajectories as it can capture critical information very accurately.

Development of Transferable Nonbonded Interactions between Coarse-Grained Hydrocarbon and Water Models.

Interactions between water and hydrocarbons play a significant role in chemical, physical, and biological processes. Here, we present a set of force-field (FF) parameters that define the interactions between coarse-grained (CG) hydrocarbon models ( An , Y. J. Phys. Chem. B , 2018 , 122 , 7143 - 7153 ) and one-site water model ( Bejagam , K. K. J. Phys. Chem. B , 2018 , 122 , 1958 - 1971 ) developed in our recent work. The nonbonded FF interactions between various hydrocarbon beads and the water beads are represented by the 12-6 Lennard-Jones potential. The FF parameters were optimized to reproduce the experimentally measured Gibbs hydration free energies of selected hydrocarbon models (decane and hexadecane with 2:1 mapping scheme and nonane and pentadecane with 3:1 mapping scheme) and the interfacial tensions of decane and nonane models at 300 K. The predicted values of Gibbs hydration free energies of CG decane, hexadecane, nonane, and pentadecane models by the optimized FF parameters were within 8, 12, 11, and 4% of their corresponding experimental values, respectively. These new optimized FF parameters were transferable when used to calculate the Gibbs hydration free energies of different hydrocarbons ranging from pentane to heptadecane at 300 K (minimum error ∼0.5%, and maximum error ∼40.8%). Furthermore, the interfacial tensions of the CG hydrocarbon models calculated by using these new FF parameters showed good agreement with their corresponding experimental values at 300 K. Homogeneous mixtures of CG water and hydrocarbon models were able to exhibit the phase segregation during 1 µs. These new nonbonded interaction parameters were expected to be utilized in modeling the interactions between water and polymer backbones represented with hydrocarbon beads.

Adrenomedullary function, obesity and permissive influences of catecholamines on body mass in patients with chromaffin cell tumours.

BACKGROUND: Obesity-associated activation of sympathetic nervous outflow is well documented, whereas involvement of dysregulated adrenomedullary hormonal function in obesity is less clear. This study assessed relationships of sympathoadrenal function with indices of obesity and influences of circulating catecholamines on body mass. METHODS: Anthropometric and clinical data along with plasma and 24-h urine samples were collected from 590 volunteers and 1368 patients tested for phaeochromocytoma and paraganglioma (PPGL), among whom tumours were diagnosed in 210 individuals. RESULTS: Among patients tested for PPGL, those with tumours less often had a body mass index (BMI) above 30 kg/m2 (12 vs. 31%) and more often a BMI under 25 kg/m2 (56 vs. 32%) than those without tumours (P < 0.0001). Urinary outputs of catecholamines in patients with PPGL were negatively related to BMI (r = -0.175, P = 0.0133). Post-operative weight gain (P < 0.0001) after resection of PPGL was positively related to presurgical tumoural catecholamine output (r = 0.257, P = 0.0101). Higher BMI in men and women and percent body fat in women of the volunteer group were associated with lower plasma concentrations and urinary outputs of adrenaline and metanephrine, the former indicating obesity-related reduced adrenaline secretion and the latter obesity-related reduced adrenomedullary adrenaline stores. Daytime activity was associated with substantial increases in urinary adrenaline and noradrenaline excretion, with blunted responses in obese subjects. CONCLUSIONS: The findings in patients with PPGL support an influence of high circulating catecholamines on body weight. Additional associations of adrenomedullary dysfunction with obesity raise the possibility of a permissive influence of the adrenal medulla on the regulation of body weight.