Distinct microbiota dysbiosis in patients with non-erosive reflux disease and esophageal adenocarcinoma

Non-erosive reflux disease (NERD) and esophageal adenocarcinoma (EAC) are often regarded as bookends in the gastroesophageal reflux disease spectrum. However, there is limited clinical evidence to support this disease paradigm while the underlying mechanisms of disease progression remain unclear. In this study, we used 16S rRNA sequencing and mass-spectrometer-based proteomics to characterize the esophageal microbiota and host mucosa proteome, respectively. A total of 70 participants from four patient groups (NERD, reflux esophagitis, Barrett’s esophagus, and EAC) and a control group were analyzed. Our results showed a unique NERD microbiota composition, distinct to control and other groups. We speculate that an increase in sulfate-reducing Proteobacteria and Bacteroidetes along with hydrogen producer Dorea are associated with a mechanistic role in visceral hypersensitivity. We also observed a distinct EAC microbiota consisting of a high abundance of lactic acid-producing bacteria (Staphylococcus, Lactobacillus, Bifidobacterium, and Streptococcus), which may contribute towards carcinogenesis through dysregulated lactate metabolism. This study suggests the close relationship between esophageal mucosal microbiota and the appearance of pathologies of this organ

Genetic Diversity of Mycobacterium tuberculosis Isolates from Tibetans in Tibet, China

BACKGROUND: Tuberculosis (TB) is a serious health problem in Tibet where Tibetans are the major ethnic group. Although genotyping of Mycobacterium tuberculosis (M. tuberculosis) isolates is a valuable tool for TB control, our knowledge of population structure of M. tuberculosis circulating in Tibet is limited. METHODOLOGY/PRINCIPAL FINDINGS: In our study, a total of 576 M. tuberculosis isolates from Tibetans in Tibet, China, were analyzed via spoligotyping and 24-locus MIRU-VNTR. The Beijing genotype was the most prevalent family (90.63%, n = 522). Shared-type (ST) 1 was the most dominant genotype (88.89%, n = 512). We found that there was no association between the Beijing genotype and sex, age and treatment status. In this sample collection, 7 of the 24 MIRU-VNTR loci were highly or moderately discriminative according to their Hunter-Gaston discriminatory index. An informative set of 12 loci had similar discriminatory power with 24 loci set. CONCLUSIONS/SIGNIFICANCE: The population structure of M. tuberculosis isolates in Tibetans is homogeneous and dominated by Beijing genotype. The analysis of 24-locus MIRU-VNTR data might be useful to select appropriate VNTR loci for the genotyping of M. tuberculosis

Helicobacter pylori, persistent infection burden and structural brain imaging markers

Persistent infections, whether viral, bacterial or parasitic, including Helicobacter pylori infection, have been implicated in non-communicable diseases, including dementia and other neurodegenerative diseases. In this cross-sectional study, data on 635 cognitively normal participants from the UK Biobank study (2006–21, age range: 40–70 years) were used to examine whether H. pylori seropositivity (e.g. presence of antibodies), serointensities of five H. pylori antigens and a measure of total persistent infection burden were associated with selected brain volumetric structural MRI (total, white, grey matter, frontal grey matter (left/right), white matter hyperintensity as percent intracranial volume and bi-lateral sub-cortical volumes) and diffusion-weighted MRI measures (global and tract-specific bi-lateral fractional anisotropy and mean diffusivity), after an average 9–10 years of lag time. Persistent infection burden was calculated as a cumulative score of seropositivity for over 20 different pathogens. Multivariable-adjusted linear regression analyses were conducted, whereby selected potential confounders (all measures) and intracranial volume (sub-cortical volumes) were adjusted, with stratification by Alzheimer’s disease polygenic risk score tertile when exposures were H. pylori antigen serointensities. Type I error was adjusted to 0.007. We report little evidence of an association between H. pylori seropositivity and persistent infection burden with various volumetric outcomes (P > 0.007, from multivariable regression models), unlike previously reported in past research. However, H. pylori antigen serointensities, particularly immunoglobulin G against the vacuolating cytotoxin A, GroEL and outer membrane protein antigens, were associated with poorer tract-specific white matter integrity (P < 0.007), with outer membrane protein serointensity linked to worse outcomes in cognition-related tracts such as the external capsule, the anterior limb of the internal capsule and the cingulum, specifically at low Alzheimer’s disease polygenic risk. Vacuolating cytotoxin A serointensity was associated with greater white matter hyperintensity volume among individuals with mid-level Alzheimer’s disease polygenic risk, while among individuals with the highest Alzheimer’s disease polygenic risk, the urease serointensity was consistently associated with reduced bi-lateral caudate volumes and the vacuolating cytotoxin A serointensity was linked to reduced right putamen volume (P < 0.007). Outer membrane protein and urease were associated with larger sub-cortical volumes (e.g. left putamen and right nucleus accumbens) at middle Alzheimer’s disease polygenic risk levels (P < 0.007). Our results shed light on the relationship between H. pylori seropositivity, H. pylori antigen levels and persistent infection burden with brain volumetric structural measures. These data are important given the links between infectious agents and neurodegenerative diseases, including Alzheimer’s disease, and can be used for the development of drugs and preventive interventions that would reduce the burden of those diseases

High-throughput quantitation of amino acids and acylcarnitine in cerebrospinal fluid: identification of PCNSL biomarkers and potential metabolic messengers

Background: Due to the poor prognosis and rising occurrence, there is a crucial need to improve the diagnosis of Primary Central Nervous System Lymphoma (PCNSL), which is a rare type of non-Hodgkin’s lymphoma. This study utilized targeted metabolomics of cerebrospinal fluid (CSF) to identify biomarker panels for the improved diagnosis or differential diagnosis of primary central nervous system lymphoma (PCNSL).Methods: In this study, a cohort of 68 individuals, including patients with primary central nervous system lymphoma (PCNSL), non-malignant disease controls, and patients with other brain tumors, was recruited. Their cerebrospinal fluid samples were analyzed using the Ultra-high performance liquid chromatography - tandem mass spectrometer (UHPLC-MS/MS) technique for targeted metabolomics analysis. Multivariate statistical analysis and logistic regression modeling were employed to identify biomarkers for both diagnosis (Dx) and differential diagnosis (Diff) purposes. The Dx and Diff models were further validated using a separate cohort of 34 subjects through logistic regression modeling.Results: A targeted analysis of 45 metabolites was conducted using UHPLC-MS/MS on cerebrospinal fluid (CSF) samples from a cohort of 68 individuals, including PCNSL patients, non-malignant disease controls, and patients with other brain tumors. Five metabolic features were identified as biomarkers for PCNSL diagnosis, while nine metabolic features were found to be biomarkers for differential diagnosis. Logistic regression modeling was employed to validate the Dx and Diff models using an independent cohort of 34 subjects. The logistic model demonstrated excellent performance, with an AUC of 0.83 for PCNSL vs. non-malignant disease controls and 0.86 for PCNSL vs. other brain tumor patients.Conclusion: Our study has successfully developed two logistic regression models utilizing metabolic markers in cerebrospinal fluid (CSF) for the diagnosis and differential diagnosis of PCNSL. These models provide valuable insights and hold promise for the future development of a non-invasive and reliable diagnostic tool for PCNSL

Operations strategies against demand uncertainty : process flexibility and real options

As markets are increasingly volatile today, this thesis aims to study two strategies, process flexibility and real options, that can help hedge against demand uncertainty which has posed big challenges for many manufacturing systems. We consider the process flexibility design problem for balanced but non-identical systems. While several methods and indices have been proposed in the literature, they are mostly time-consuming or do not explicitly take into account the demand variance information. In this thesis, we analytically study the effect of demand variance on the system performance and the long chain efficiency. We then develop a variance-based Hub-and-Chain method (VHC) to generate flexibility designs for the balanced but non-identical case. Numerical tests show that VHC outperforms the long chain by 45% on average and outperforms the constraint sampling method by 25% on average. Moreover, it only utilizes 1% of the computational requirements of the constraint sampling method. We then extend VHC to the unbalanced case. We benchmark VHC against the constraint sampling method and the expansion heuristic. We find that our method produces better flexibility designs than both existing methods in 99% of all the scenarios considered. Finally, we test the distributional robustness of VHC and show it is robust for the lognormal distribution and the gamma distribution. In the second essay, we prove in a multistage system the existence of a sparse process flexibility structure that is able to achieve most benefits of full flexibility and identify the corresponding conditions which show the number of links needed to accomplish such benefits is related to the number of stages. We also prove the dual problem of our model is a 0 -1 integer program. Assuming only the moment information known, we then solve the dual problem by a completely positive cross-moment model (CPCMM). In the third essay, we consider a two-period newsvendor problem in a B2C setting. To mitigate the demand risk, the manufacturer introduces a real-option-selling scheme in period 1 despite the spot market in period 2. Customers are uncertain about their future valuations for the product and may prefer to buy the option, the right to purchase one unit product at a fixed price in period 2. By inducing customers to buy the option, the manufacturer obtains more accurate demand information for period 2. We study the joint option pricing and production planning decision faced by the manufacturer. In the first part of this essay, we introduce a fluid model where the number of customers who exercise the option in period 2 is deterministic given a specific option. We first show in the single-option and single-market-segment setting the option-selling scheme is always optimal in comparison with the newsvendor. Moreover, surprisingly we find the optimal strike price constantly equals to the unit production cost. We then extend the fluid model to the two independent market segments setting with three subcases as follows, single option for high segment, single option for both segments, one option for each segment. The findings of interest are subcase 1 is equivalent to a single-option and single-market-segment problem along with a separate newsvendor problem and subcase 2 is a classic Kalman filtering problem while subcase 3 is similar to a mechanism design problem. The dominance of option selling over the newsvendor is again confirmed. In addition the condition of subcase 3 dominating subcase 1 can be characterized by the ratios of segment sizes and marginal profit and cost. In the second part of this essay, we concentrate on a binomial model where the number of customers who will exercise the option is binomial but can be approximated by the normal distribution. The market has correlated informed and uninformed segments with homogeneous valuation distribution. The purpose of this part is threefold, to incorporate the advance selling into the option-selling framework and show the dominance of the latter, to show the dominance of option selling over the newsvendor in the expedite setting and a counterintuitive result - having more information is not always optimal.DOCTOR OF PHILOSOPHY (NBS

Computational ghost imaging encryption using RSA algorithm and discrete wavelet transform

Ghost imaging technology has been widely used in the field of optical image encryption owing to its unique non-local imaging characteristics. However, there are some problems such as long encryption and decrypting time, poor reliability and large number of keys. To solve these problems, this paper proposed a computational ghost imaging encryption scheme based on RSA algorithm and wavelet transform. Firstly, the representation relationship between measurement matrix and random integer sequence is established to reduce the transmission of key quantity. Secondly, RSA encryption algorithm is used to improve the security of the system. Finally, using wavelet decomposition for packet transmission. In addition, the cake cutting matrix is used as the measurement matrix to reduce the sampling times and improve the quality of reconstructed images. The simulation results show that the encryption system has strong information transmission security and good robustness. It provides some reference for image encryption and information security transmission

Spatial Distribution Characteristics of Microbial Mineralization in Saturated Sand Centrifuge Shaking Table Test

Calcium carbonate induced by microorganisms can quickly fill and cement sand particles, thereby effectively reducing the potential for the liquefaction of sand. This process could represent a new green approach to the liquefaction treatment of saturated sand and has good prospects for application. However, owing to the diversity of microbial activities and the heterogenous spatiotemporal distribution of bacterial nutrient seepage in sandy soil foundations, the resultant complex distribution of calcium carbonate deposition in a sandy soil foundation can lead to differences in solidification strength and improvement effect. To understand the influence of earthquake action on the liquefaction resistance of saturated sand treated by microorganisms, and to evaluate the effect of microbial technology on sand liquefaction prevention under dynamic load, this study simulated the dynamic stress conditions of saturated sand under shear waves, using the world′s first centrifuge shaking table (R500B), which realizes horizontal and vertical two-way vibration. On the basis of spatial heterogeneity of microbial mineralization after centrifuge shaking table tests, the effect of microbial strengthening on liquefied sand was analyzed, and the spatial distribution of calcium carbonate mineralization was examined. The results showed that the distribution of microorganisms in the solidified soil exhibited obvious spatial heterogeneity with a significant edge effect. Although microbial mineralization effectively improved the liquefaction resistance of saturated sand, a sudden change in the process of calcium carbonate deposition altered the cementation of the sand with depth. Moreover, the curing strength had obvious complexity and uncertainty that directly affected the shear stiffness of the soil under dynamic load, and this constitutes one of the reasons for the degradation of shear stiffness of sand during liquefaction. The derived conclusions could be used as a reference for engineering applications of microbial treatment of a liquefiable sandy soil foundation

Hydrological Monitoring System Design and Implementation Based on IOT

AbstractIn this article, an embedded system development platform based on GSM communication is proposed. Through its application in hydrology monitoring management, the author makes discussion about communication reliability and lightning protection, suggests detail solutions, and also analyzes design and realization of upper computer software. Finally, communication program is given. Hydrology monitoring system from wireless communication network is a typical practical application of embedded system, which has realized intelligence, modernization, high-efficiency and networking of hydrology monitoring management