Potential therapeutic targets of gastric cancer explored under endogenous network modeling of clinical data.

Improvement in the survival rate of gastric cancer, a prevalent global malignancy and the leading cause of cancer-related mortality calls for more avenues in molecular therapy. This work aims to comprehend drug resistance and explore multiple-drug combinations for enhanced therapeutic treatment. An endogenous network modeling clinic data with core gastric cancer molecules, functional modules, and pathways is constructed, which is then transformed into dynamics equations for in-silicon studies. Principal component analysis, hierarchical clustering, and K-means clustering are utilized to map the attractor domains of the stochastic model to the normal and pathological phenotypes identified from the clinical data. The analyses demonstrate gastric cancer as a cluster of stable states emerging within the stochastic dynamics and elucidate the cause of resistance to anti-VEGF monotherapy in cancer treatment as the limitation of the single pathway in preventing cancer progression. The feasibility of multiple objectives of therapy targeting specified molecules and/or pathways is explored. This study verifies the rationality of the platform of endogenous network modeling, which contributes to the development of cross-functional multi-target combinations in clinical trials.

Topology, vorticity, and limit cycle in a stabilized Kuramoto-Sivashinsky equation.

A noisy stabilized Kuramoto-Sivashinsky equation is analyzed by stochastic decomposition. For values of the control parameter for which periodic stationary patterns exist, the dynamics can be decomposed into diffusive and transverse parts which act on a stochastic potential. The relative positions of stationary states in the stochastic global potential landscape can be obtained from the topology spanned by the low-lying eigenmodes which interconnect them. Numerical simulations confirm the predicted landscape. The transverse component also predicts a universal class of vortex-like circulations around fixed points. These drive nonlinear drifting and limit cycle motion of the underlying periodic structure in certain regions of parameter space. Our findings might be relevant in studies of other nonlinear systems such as deep learning neural networks.

Analysis of Hospitalization Costs in Patients Suffering from Cerebral Infarction along with Varied Comorbidities.

OBJECTIVE: This study aimed to study the influence of comorbidities on hospitalization costs for inpatients with cerebral infarction. METHODS: The data from the medical records pertaining to 76,563 inpatients diagnosed with cerebral infarction were collected from public hospital records for the period between 1 January 2020 and 30 December 2020 in Gansu Province. EpiData 3.1 software was used for data collation, and SPSS 25.0 was used for data analysis. Numbers and percentages were calculated for categorical variables, the chi-squared test was used to compare differences between groups, and multiple independent-sample tests (Kruskal-Wallis H test, test level α = 0.05) and multiple linear regression were used to analyze the influence of different types of comorbidity on hospitalization costs. RESULTS: Among the 76,563 cerebral infarction inpatients, 41,400 were male (54.07%); the average age of the inpatients was 67.68 ± 10.75 years (the 60~80-year-old group accounted for 65.69%). Regarding the incidence of varied chronic disease comorbidities concomitant with cerebral infarction, hypertension was reported as the most frequent, followed by heart disease and chronic pulmonary disease. The average hospitalization cost of cerebral infarction inpatients is US $1219.66; the hospitalization cost increases according to the number of comorbidities with which a patient suffers (H = 404.506, p < 0.001); Regarding the types of comorbidities, the hospitalization cost of cancer was the highest, at US $1934.02, followed by chronic pulmonary disease (US $1533.02). Regarding the cost of hospitalization for combinations of comorbidities, cerebral infarction + chronic pulmonary disease was the most costly (US $1718.90), followed by cerebral infarction + hypertension + chronic pulmonary disease (US $1530.60). In the results of multiple linear regression analysis, cerebral infarction with chronic pulmonary disease had significant effects on hospitalization costs (ß = 0.181, p < 0.001), drug costs (ß = 0.144, p < 0.001) and diagnosis costs (ß = 0.171, p < 0.001). CONCLUSIONS: Comorbidities are significantly associated with high hospitalization costs for cerebral infarction patients. Furthermore, relevant health departments should build preventative and control systems to reduce the risk of comorbidities, as well as to improve hospital clinical pathway management and to strengthen and refine the cost-control management of cerebral infarction from the perspective of comorbidities.

The economic burden of systemic sclerosis-A systematic review.

AIM: Systemic sclerosis (SSc) is a rare, chronic autoimmune disease associated with a substantial economic burden. This study aimed to assess the costs associated with SSc and to identify major cost drivers. METHODS: A systematic search was conducted in MEDLINE and Embase to identify relevant studies. Two independent reviewers evaluated studies based on inclusion/exclusion criteria and performed data extraction. Costs were converted into 2017 US dollars by purchasing power parity. The review was conducted following the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guideline. RESULTS: The original literature search identified 113 potentially relevant citations, of which 10 articles met all the inclusion/exclusion criteria and were included in the data extraction and analysis. The identified studies evaluated costs associated with SSc in 11 countries from North America, Europe, and Australia published between 2009 and 2018. Eight studies reported direct costs and seven studies reported indirect costs. Direct costs varied from $3356 (Hungary) to $27 032 (Germany) with hospitalization and medication being two of the biggest components of direct medical costs in most studies. The indirect costs for lost productivity varied from $2433 (Italy) to $20 663 (UK), accounting for a significant portion of the total economic burden. CONCLUSIONS: Large variations existed in annual costs of SSc, but all studies found that SSc imposed a substantial economic burden on patients and their families. The identified studies were mostly from high-income countries and there is still a knowledge gap regarding the cost of SSc in other parts of the world.

Global Trends and Future Prospects of Child Nutrition: A Bibliometric Analysis of Highly Cited Papers.

Child nutrition has always been a global concern. This study performed visual analysis of 1,398 child nutrition highly cited papers (HCPs) from 2009 to 2019. The purpose of the study was to evaluate and present the performances of authors, journals, countries, institutions, top cited papers; to explore the hot topics, prospects, and to propose the future research directions on child nutrition. We used bibliometric methods to conduct in-depth statistical analysis of HCPs on child nutrition, showing research progress, trends and hot spots. We included HCPs on child nutrition from the Science Citation Index-Expanded (SCI-E) database February 7, 2020. Two tools, CiteSpace and VOSviewer, were used to conduct the bibliometric analyses. The results showed that, since 2011, the number of HCPs on child nutrition has increased rapidly. The top three contributors in this field were the USA, the UK and Canada. However, the contribution of developing countries was very limited. Intestinal microflora, food allergy, overweight and obesity were the three major research hotspots in this field. Results of this study provide valuable references for ongoing child nutrition related research, which may be interesting and noteworthy to the researchers involved.

Global potential, topology, and pattern selection in a noisy stabilized Kuramoto-Sivashinsky equation.

We formulate a general method to extend the decomposition of stochastic dynamics developed by Ao et al. [J. Phys. Math. Gen. 37, L25-L30 (2004)] to nonlinear partial differential equations which are nonvariational in nature and construct the global potential or Lyapunov functional for a noisy stabilized Kuramoto-Sivashinsky equation. For values of the control parameter where singly periodic stationary solutions exist, we find a topological network of a web of saddle points of stationary states interconnected by unstable eigenmodes flowing between them. With this topology, a global landscape of the steady states is found. We show how to predict the noise-selected pattern which agrees with those from stochastic simulations. Our formalism and the topology might offer an approach to explore similar systems, such as the Navier Stokes equation.

Resonant Confinement of an Excitonic Polariton and Ultraefficient Light Harvest in Artificial Photosynthesis.

We uncover a novel phenomenon from a recent artificial light-harvesting experiment [P.-Z. Chen et al., Angew. Chem., Int. Ed. Engl. 55, 2759 (2016)ACIEAY0570-083310.1002/anie.201510503] on organic nanocrystals of self-assembled difluoroboron chromophores. A resonant confinement of a polariton under strong photon-exciton coupling is predicted to exist within the microcavity of the crystal's own natural boundaries. Moreover, the radiative energy of a localized exciton falls into the spectrum of confinement. Hence, in the experiment, the spontaneous emission of an excited pigment would undergo a two-step process. It should first decay to an excitonic polariton trapped by the cavity resonance. The intermediate polariton could then funnel the energy directly to a doped acceptor, leading to the over 90% transfer efficiency observed at less than 1/1000 acceptor/donor ratio. The proposed mechanism is supported by parameter-free analyses entirely based on experiment data. Our finding may imply possible polariton-mediated pathways for energy transfers in biological photosynthesis.

Dynamical modelling of secondary metabolism and metabolic switches in Streptomyces xiamenensis 318.

The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary metabolites increase the metabolic fitness of the organism via stabilizing the underlying metabolic network. And the fluxes directing to NADH, NADPH, acetyl-CoA and glutamate provide the key switches for the overall and secondary metabolism. The information may be helpful for improving the xiamenmycin production on the strain.

Effects of a clinical pathway on antibiotic use in patients with community-acquired pneumonia: a multi-site study in China.

BACKGROUND: Community-acquired pneumonia (CAP) is a common condition with high mortality, morbidity and healthcare costs. This study aimed to determine whether clinical pathway (CP) implementation in different hospitals in China increased antibiotic compliance with the national CP in inpatients with CAP. METHODS: Chart reviews of CAP cases were conducted in 18 public hospitals from 3 different regions of China in 2015. Chi-square tests and the t-test were used to compare differences between hospitals that implemented CP (CP group) and those that did not (non-CP group). Multivariate logistic analysis was adopted to test whether CP implementation for CAP in hospitals affected their overall antibiotic use compliance rates with the national CP for CAP. RESULTS: The overall compliance rate with the national CP for inpatients with CAP was 43.69%. The compliance rates for timely initial antibiotic use, recommended antibiotic use and use of the recommended combination of antibiotics and the overall compliance rate were substantially higher in the CP group than in the non-CP group. A multivariate logistic model for overall compliance in inpatients with CAP showed that the hospitals in the CP group had greater overall compliance than those in the non-CP group (odds ratio [OR] = 1.76; 95% confidence interval [CI] = 1.16-2.71) after controlling for hospital and inpatient characteristics. CONCLUSION: In China, the overall compliance rate with the national CP for inpatients with CAP was low, but inpatients with CAP in the hospitals in the CP group received antibiotics more concordantly with the national CP. Since adherence to evidence-based care has been shown to improve clinical outcomes, internal and external support from hospitals is required to facilitate CP implementation for inpatients with CAP. Additionally, governmental commitment, hospital input and population involvement are required to improve antibiotic utilization.

Reversible Hydrophobicity-Hydrophilicity Transition Modulated by Surface Curvature.

Wettability (hydrophobicity and hydrophilicity) is of fundamental importance in physical, chemical, and biological behaviors, resulting in widespread interest. Herein, by modulating surface curvature, we observed a reversible hydrophobic-hydrophilic transition on a model referred to a platinum surface. The underlying mechanism is revealed to be the competition between strong water-solid attraction and interfacial water orderliness. On the basis of the competition, we further propose an equation of wetting transition in the presence of an ordered interfacial liquid. It quantitatively reveals the relation of solid wettability with interfacial water orderliness and solid surface curvature, which can be used for predicting the critical point of the wetting transition. Our findings thus provide an innovative perspective on the design of a functional device demonstrating a reversible wettability transition and even a molecular-level understanding of biological functions.

Towards stable kinetics of large metabolic networks: Nonequilibrium potential function approach.

While the biochemistry of metabolism in many organisms is well studied, details of the metabolic dynamics are not fully explored yet. Acquiring adequate in vivo kinetic parameters experimentally has always been an obstacle. Unless the parameters of a vast number of enzyme-catalyzed reactions happened to fall into very special ranges, a kinetic model for a large metabolic network would fail to reach a steady state. In this work we show that a stable metabolic network can be systematically established via a biologically motivated regulatory process. The regulation is constructed in terms of a potential landscape description of stochastic and nongradient systems. The constructed process draws enzymatic parameters towards stable metabolism by reducing the change in the Lyapunov function tied to the stochastic fluctuations. Biologically it can be viewed as interplay between the flux balance and the spread of workloads on the network. Our approach allows further constraints such as thermodynamics and optimal efficiency. We choose the central metabolism of Methylobacterium extorquens AM1 as a case study to demonstrate the effectiveness of the approach. Growth efficiency on carbon conversion rate versus cell viability and futile cycles is investigated in depth.

Kinetic model of metabolic network for xiamenmycin biosynthetic optimisation.

Xiamenmycins, a series of prenylated benzopyran compounds with anti-fibrotic bioactivities, were isolated from a mangrove-derived Streptomyces xiamenensis. To fulfil the requirements of pharmaceutical investigations, a high production of xiamenmycin is needed. In this study, the authors present a kinetic metabolic model to evaluate fluxes in an engineered Streptomyces lividans with xiamenmycin-oriented genetic modification based on generic enzymatic rate equations and stability constraints. Lyapunov function was used for a viability optimisation. From their kinetic model, the flux distributions for the engineered S. lividans fed on glucose and glycerol as carbon sources were calculated. They found that if the bacterium can utilise glucose simultaneously with glycerol, xiamenmycin production can be enhanced by 40% theoretically, while maintaining the same growth rate. Glycerol may increase the flux for phosphoenolpyruvate synthesis without interfering citric acid cycle. They therefore believe this study demonstrates a possible new direction for bioengineering of S. lividans.