Truthful Generalized Linear Models

In this paper we study estimating Generalized Linear Models (GLMs) in the case where the agents (individuals) are strategic or self-interested and they concern about their privacy when reporting data. Compared with the classical setting, here we aim to design mechanisms that can both incentivize most agents to truthfully report their data and preserve the privacy of individuals' reports, while their outputs should also close to the underlying parameter. In the first part of the paper, we consider the case where the covariates are sub-Gaussian and the responses are heavy-tailed where they only have the finite fourth moments. First, motivated by the stationary condition of the maximizer of the likelihood function, we derive a novel private and closed form estimator. Based on the estimator, we propose a mechanism which has the following properties via some appropriate design of the computation and payment scheme for several canonical models such as linear regression, logistic regression and Poisson regression: (1) the mechanism is $o(1)$-jointly differentially private (with probability at least $1-o(1)$); (2) it is an $o(\frac{1}{n})$-approximate Bayes Nash equilibrium for a $(1-o(1))$-fraction of agents to truthfully report their data, where $n$ is the number of agents; (3) the output could achieve an error of $o(1)$ to the underlying parameter; (4) it is individually rational for a $(1-o(1))$ fraction of agents in the mechanism ; (5) the payment budget required from the analyst to run the mechanism is $o(1)$. In the second part, we consider the linear regression model under more general setting where both covariates and responses are heavy-tailed and only have finite fourth moments. By using an $\ell_4$-norm shrinkage operator, we propose a private estimator and payment scheme which have similar properties as in the sub-Gaussian case.Comment: To appear in The 18th Conference on Web and Internet Economics (WINE 2022

Examination of the Quantitative Relationship between Vegetation Canopy Height and LAI

Accurate estimation of vegetation biophysical variables such as the vegetation canopy height (H) is of great importance to the applications of the land surface models. It is difficult to obtain the data of H at the regional scale or larger scale, but the remote sensing provides the most useful and most effective method. The leaf area index (LAI) is closely related to the H, and we analyzed its relationship with the correlation analysis based on the dataset at 86 site-years of field measurements from sites worldwide in this study. The result indicates that there is significant positive exponent correlation between these two parameters and the change of LAI would exert great impacts on H. The higher the LAI is, the higher the H is, and vice versa. Besides, the coefficients of different land cover types are very heterogeneous, and LAI of the needleleaf forest shows strong correlation with H, while that of the cropland shows weak correlation with H. The results may provide certain reference information for the extraction of the data of H at the regional scale with the remote sensing data

The expression, clinical relevance, and prognostic significance of HJURP in cholangiocarcinoma

BackgroundCholangiocarcinoma (CCA) is the malignancy originating from the biliary epithelium, including intrahepatic (iCCA), perihilar (pCCA), and distal (dCCA) CCA. The prognosis of CCA is very poor, and the biomarkers of different CCA subsets should be investigated separately. Holliday junction recognition protein (HJURP) is a key component of the pre-nucleosomal complex, which is responsible for normal mitosis. The ectopic expression of HJURP has been reported in several cancers, but not CCA.Materials and methodsIn our study, we investigated the expression of HJURP in 127 CCA patients which were composed of 32 iCCAs, 71 pCCAs, and 24 dCCAs with immunohistochemistry and divided these patients into subgroups with a low or high expression of HJURP. With chi-square test and univariate and multivariate analyses, we evaluated the clinical relevance and prognostic significance of HJURP in iCCAs, pCCAs, and dCCAs.ResultsHJURP was ectopically upregulated in CCAs compared with the para-tumor tissues based on TCGA and other mRNA-seq databases. A high expression of HJURP was correlated with low overall survival rates of iCCA and pCCA, but not in dCCA. Moreover, HJURP was an independent prognostic biomarker in both iCCA and pCCA. Patients with high HJURP were more likely to suffer CCA-related death after operation.ConclusionsHJURP was an independent prognostic biomarker in both iCCA and pCCA, but not in dCCA. Our results provide more evidence of the molecular features of different CCA subsets and suggest that patients with high HJURP are more high-risk, which can guide more precision follow-up and treatment of CCA

An integrated software for virus community sequencing data analysis

BACKGROUND: A virus community is the spectrum of viral strains populating an infected host, which plays a key role in pathogenesis and therapy response in viral infectious diseases. However automatic and dedicated pipeline for interpreting virus community sequencing data has not been developed yet.RESULTS: We developed Quasispecies Analysis Package (QAP), an integrated software platform to address the problems associated with making biological interpretations from massive viral population sequencing data. QAP provides quantitative insight into virus ecology by first introducing the definition "virus OTU" and supports a wide range of viral community analyses and results visualizations. Various forms of QAP were developed in consideration of broader users, including a command line, a graphical user interface and a web server. Utilities of QAP were thoroughly evaluated with high-throughput sequencing data from hepatitis B virus, hepatitis C virus, influenza virus and human immunodeficiency virus, and the results showed highly accurate viral quasispecies characteristics related to biological phenotypes.CONCLUSIONS: QAP provides a complete solution for virus community high throughput sequencing data analysis, and it would facilitate the easy analysis of virus quasispecies in clinical applications.</p

Milk Oligopeptide Inhibition of (α)-Tocopherol Fortified Linoleic Acid Oxidation

This study investigated the effect of milk oligopeptides and (α)-tocopherol on inhibition of linoleic acid oxidation using Fe2+-vitamin C induced linoleic acid oxidation model through analysis of malondialdehyde, peroxide value, and conjugated diene and triene in the model. The alteration of milk oligopeptides maximal absorption wavelength, fluorescent feature, and secondary structure were further investigated to elucidate the interactions between milk oligopeptide and (α)-tocopherol that altered the inhibitory effect of linoleic acid oxidation. Results showed that Pro-Tyr-Tyr-Ala-Lys (PYYAK) and Ile-Pro-Ile-Gln-Tyr (IPIQY) with (α)-tocopherol significantly inhibited the oxidation of linoleic acid and reduced the formation of malondialdehyde by 38% and 41%, respectively. Additionally, Ile-Pro-Ile-Gln-Tyr-Val (IPIQYV) and (α)-tocopherol synergistically reduced the peroxide value in the model by 36.8%. Milk oligopeptides exhibited a blue shift on its maximal absorption wavelength, and their absorbance value decreased with the increase of the (α)-tocopherol concentration. The fluorescent intensity of milk oligopeptides was reduced with the addition of (α)-tocopherol and such fluorescent intensity reductions resulted from the static quenching process through the formation of milk oligopeptide-(α)-tocopherol complex. Fourier transform infrared spectroscopy analysis revealed that (α)-tocopherol significantly altered the secondary structure of milk oligopeptides and the percentage of β-turn obviously increased in milk oligopeptide-(α)-tocopherol complex. These indicated that the inhibition of linoleic acid oxidation might result from complex formed between milk oligopeptide and (α)-tocopherol through inter-molecular interactions

Characterization of gene expression profiles in HBV-related liver fibrosis patients and identification of ITGBL1 as a key regulator of fibrogenesis

Although hepatitis B virus (HBV) infection is the leading cause of liver fibrosis (LF), the mechanisms underlying liver fibrotic progression remain unclear. Here, we investigated the gene expression profiles of HBV-related LF patients. Whole genome expression arrays were used to detect gene expression in liver biopsy samples from chronically HBV infected patients. Through integrative data analysis, we identified several pathways and key genes involved in the initiation and exacerbation of liver fibrosis. Weight gene co-expression analysis revealed that integrin subunit β-like 1 (ITGBL1) was a key regulator of fibrogenesis. Functional experiments demonstrated that ITGBL1 was an upstream regulator of LF via interactions with transforming growth factor β1. In summary, we investigated the gene expression profiles of HBV-related LF patients and identified a key regulator ITGBL1. Our findings provide a foundation for future studies of gene functions and promote the development of novel antifibrotic therapies

The phenolics, antioxidant activity and in vitro digestion of pomegranate (Punica granatum L.) peels: an investigation of steam explosion pre-treatment

Pomegranate peels, the main byproduct of pomegranate production, are rich in phenolic compounds that are known for their effective antioxidant properties and have vast application prospects. In this study, steam explosion, an environmentally friendly technique, was applied to pretreat pomegranate peels for phenol extraction. We investigated the effects of explosion pressure, duration, and particle size on the content of total and individual phenolics, and antioxidant activity of pomegranate peels before and after in vitro digestion. The optimal conditions for a steam explosion for pomegranate peels in terms of total phenol content were a pressure of 1.5 MPa, a maintenance time of 90 s, and a particle size of 40 mesh. Under these conditions, pomegranate peel extract presented a higher yield of total phenols, gallic acid, and ellagic acid. However, it also had a lower content of punicalin and punicalagin, compared to the unexploded peels. There was no improvement in the antioxidant activity of pomegranate peels after the steam explosion. Moreover, the content of total phenol, gallic acid, ellagic acid, punicalin, and punicalagin, as well as the antioxidant activity of pomegranate peels, all increased after gastric digestion. Nevertheless, there was a large variation in the pomegranate peel processed by different pressure, duration, and sieve fractions. Overall, this study demonstrated that steam explosion pre-treatment could be an efficient method for improving the release of phenolics, especially gallic acid, and ellagic acid, from pomegranate peels

Trends in cutaneous squamous cell carcinoma on the lip incidence and mortality in the United States, 2000–2019

ObjectiveThis study provided a systematic analysis of the trend in incidence and incidence-based mortality for cutaneous squamous cell carcinoma (cSCC) on the lips in the USA using demographic characteristics from the Surveillance, Epidemiology, and End Results (SEER) database.MethodsPatients diagnosed with cSCC on the lips between 2000 and 2019 from the 17 registries of the USA were identified. Incidence and incidence-based mortality rates were analyzed using SEER*Stat 8.4.0.1 software. This paper calculated incidence rates and incidence-based mortality rates by 100,000 person-years for sex, age, race, SEER registries, median household income ($/year), rural-urban distribution, and primary site. The annual percent changes (APC) in incidence and incidence-based mortality rates were then calculated using joinpoint regression software.ResultsAmong 8,625 patients diagnosed with cSCC on the lips from 2000 to 2019, men (74.67%), white (95.21%), and 60–79 years old were the most common population, and 3,869 deaths from cSCC on the lips occurred. The overall incidence of cSCC on the lips was 0.516 per 100,000 person-years. cSCC on the lip incidence rates were highest among men, white, and patients aged 60–79 years old. cSCC on the lip incidence rates decreased by 3.210%/year over the study period. The incidence of cSCC on the lips has been decreasing in all sexes, ages, high- or low-income households, and urban or rural patients. The overall incidence-based mortality rate of cSCC on the lips during 2000–2019 was 0.235 per 100,000 person-years. cSCC on the lip incidence-based mortality rates were highest among men, whites, and people older than 80 years old. cSCC on the lip incidence-based mortality increased by 4.975%/year over the study period. cSCC on the lip incidence-based mortality rates increased for all sexes, races, ages, primary sites, high- or low-income households, and urban or rural patients during the study period.ConclusionAmong patients in the USA diagnosed with cSCC on the lips from 2000 to 2019, the overall incidence decreased by 3.210% annually, and incidence-based mortality increased by 4.975%/year. These findings update and supplement the epidemiological information of cSCC on the lips in the USA

Maximization of negative correlations in time-course gene expression data for enhancing understanding of molecular pathways

Positive correlation can be diversely instantiated as shifting, scaling or geometric pattern, and it has been extensively explored for time-course gene expression data and pathway analysis. Recently, biological studies emerge a trend focusing on the notion of negative correlations such as opposite expression patterns, complementary patterns and self-negative regulation of transcription factors (TFs). These biological ideas and primitive observations motivate us to formulate and investigate the problem of maximizing negative correlations. The objective is to discover all maximal negative correlations of statistical and biological significance from time-course gene expression data for enhancing our understanding of molecular pathways. Given a gene expression matrix, a maximal negative correlation is defined as an activation–inhibition two-way expression pattern (AIE pattern). We propose a parameter-free algorithm to enumerate the complete set of AIE patterns from a data set. This algorithm can identify significant negative correlations that cannot be identified by the traditional clustering/biclustering methods. To demonstrate the biological usefulness of AIE patterns in the analysis of molecular pathways, we conducted deep case studies for AIE patterns identified from Yeast cell cycle data sets. In particular, in the analysis of the Lysine biosynthesis pathway, new regulation modules and pathway components were inferred according to a significant negative correlation which is likely caused by a co-regulation of the TFs at the higher layer of the biological network. We conjecture that maximal negative correlations between genes are actually a common characteristic in molecular pathways, which can provide insights into the cell stress response study, drug response evaluation, etc