Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors

This paper considers identification and inference of a general latent nonlinear model using two samples, where a covariate contains arbitrary measurement errors in both samples, and neither sample contains an accurate measurement of the corresponding true variable. The primary sample consists of some dependent variables, some error-free covariates and an error-ridden covariate, where the measurement error has unknown distribution and could be arbitrarily correlated with the latent true values. The auxiliary sample consists of another noisy measurement of the mismeasured covariate and some error-free covariates. We first show that a general latent nonlinear model is nonparametrically identified using the two samples when both could have nonclassical errors, with no requirement of instrumental variables nor independence between the two samples. When the two samples are independent and the latent nonlinear model is parameterized, we propose sieve quasi maximum likelihood estimation (MLE) for the parameter of interest, and establish its root-n consistency and asymptotic normality under possible misspecification, and its semiparametric efficiency under correct specification. We also provide a sieve likelihood ratio model selection test to compare two possibly misspecified parametric latent models. A small Monte Carlo simulation and an empirical example are presented.Data combination, Nonlinear errors-in-variables model, Nonclassical measurement error, Nonparametric identification, Misspecified parametric latent model, Sieve likelihood estimation and inference

Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments

This note considers nonparametric identification of a general nonlinear regression model with a dichotomous regressor subject to misclassification error. The available sample information consists of a dependent variable and a set of regressors, one of which is binary and error-ridden with misclassification error that has unknown distribution. Our identification strategy does not parameterize any regression or distribution functions, and does not require additional sample information such as instrumental variables, repeated measurements, or an auxiliary sample. Our main identifying assumption is that the regression model error has zero conditional third moment. The results include a closed-form solution for the unknown distributions and the regression function.

Nonparametric identification and estimation of nonclassical errors-in-variables models without additional information

This paper considers identification and estimation of a nonparametric regression model with an unobserved discrete covariate. The sample consists of a dependent variable and a set of covariates, one of which is discrete and arbitrarily correlates with the unobserved covariate. The observed discrete covariate has the same support as the unobserved covariate, and can be interpreted as a proxy or mismeasure of the unobserved one, but with a nonclassical measurement error that has an unknown distribution. We obtain nonparametric identification of the model given monotonicity of the regression function and a rank condition that is directly testable given the data. Our identification strategy does not require additional sample information, such as instrumental variables or a secondary sample. We then estimate the model via the method of sieve maximum likelihood, and provide root-n asymptotic normality and semiparametric efficiency of smooth functionals of interest. Two small simulations are presented to illustrate the identification and the estimation results.

How patients think about social responsibility of public hospitals in China?

Questionnaire for the patients of public hospitals. The questionnaire was designed and implemented in the survey to understand patients’ opinion of the medical services, especially the view of social responsibility of this public hospital. (DOC 32 kb

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Measuring direct non-medical burden among patients with advanced non-small cell lung cancer in China: is there a difference in health status?

ObjectiveThis study was conducted to estimate the direct non-medical cost of advanced non-small cell lung cancer (NSCLC) patients and explore whether its associated factors vary by health status.MethodsData were obtained from 13 centers in five provinces for patients with advanced NSCLC in China. The direct non-medical cost of patients since the patients were diagnosed with NSCLC included the cost of transportation, accommodation, meal, hired caregiving, and nutrition. We measured patients' health status by EQ-5D-5L instrument and divided them into good (≥0.75) and poor (<0.75) groups based on the utility score. A generalized linear model (GLM) was used to assess independent associations between statistically significant factors and non-medical financial burden in health status subgroups.ResultsData from 607 patients were analyzed. The direct non-medical cost associated with advanced NSCLC since diagnosis was $2,951 per case ($4,060 in the poor health group and $2,505 in the other), with nutrition costing the most. GLM results showed that residence(Urban area vs. Rural area: −1.038, [−2.056, −0.02]), caregivers' occupation type (Farmer vs. Employee: −1.303, [−2.514, −0.093]), hospitalization frequency (0.077, [0.033, 0.12]), average length of hospital stay (0.101, [0.032, 0.17]), and pathological type (Squamous carcinoma vs. Non-squamous carcinoma: −0.852, [−1.607, −0.097]) were independent factors influencing direct non-medical cost in the poor health group. Among participants with good health status, residence (Urban area vs. Rural area: −0.621, [−1.005, −0.236]), marital status (Others vs. Married: 0.762, [0.035, 1.488]), patients' employment status, current caregiving time per day (more than 9 hours per day vs. less than 3 hours per day: 0.471, [0.134, 0.807]), duration of disease (0.015, [0.007, 0.024]), and hospitalization frequency (0.091, [0.068, 0.113]) were statistically associated factors.ConclusionThe direct non-medical economic burden of advanced NSCLC patients in China is considerable and differs by health status. Strengthening accessibility for more effective therapies and early nutritional intervention to improve prognosis, and further promoting accessible care forms within relevant healthcare insurance coverage may be potentially feasible approaches to alleviate the direct non-medical economic burden for patients and their families

What is valued most by patients with type 2 diabetes mellitus when selecting second-line antihyperglycemic medications in China

Objective: To estimate patient preferences for second-line antihyperglycemic medications in China. Methods: A face to face survey with the best-worst scaling (BWS) choices was administered in patients with diagnosed type 2 diabetes mellitus (T2DM). Study participants were asked to indicate which attribute they valued most and which attribute they valued least in 11 choice sets, each of which consisted of five alternatives out of 11 antihyperglycemic medication-specific attributes (treatment efficacy, weight change, hypoglycemic events, gastrointestinal side effects, cardiovascular health, urinary tract infection and genital infection side effects, edema, mode of administration, bone fracture, dosing frequency and out-of-pocket cost). A counting approach, a conditional logit model, and K-means clustering were used to estimate the relative importance of items and preference heterogeneity. Results: A total of 362 participants were included with a mean age of 63.6 (standard deviation: 11.8) years. There were 56.4% of participants were women, and 56.3% being diagnosed with diabetes for at least 5 years. Efficacy, cardiovascular health and hypoglycemic events were valued most, while dosing frequency, mode of administration and bone fracture were valued least. The K-means clustering further showed preference heterogeneity in out-of-pocket cost across the participants. Conclusion: Our study suggests that treatment efficacy, cardiovascular health and hypoglycemic events are valued most by Chinese patients with T2DM when selecting second-line antihyperglycemic medications. The study improves the understanding of patients’ preferences for second-line antihyperglycemic medications in China

In silico discovery of transcription regulatory elements in Plasmodium falciparum

<p>Abstract</p> <p>Background</p> <p>With the sequence of the <it>Plasmodium falciparum </it>genome and several global mRNA and protein life cycle expression profiling projects now completed, elucidating the underlying networks of transcriptional control important for the progression of the parasite life cycle is highly pertinent to the development of new anti-malarials. To date, relatively little is known regarding the specific mechanisms the parasite employs to regulate gene expression at the mRNA level, with studies of the <it>P. falciparum </it>genome sequence having revealed few <it>cis</it>-regulatory elements and associated transcription factors. Although it is possible the parasite may evoke mechanisms of transcriptional control drastically different from those used by other eukaryotic organisms, the extreme AT-rich nature of <it>P. falciparum </it>intergenic regions (~90% AT) presents significant challenges to <it>in silico cis</it>-regulatory element discovery.</p> <p>Results</p> <p>We have developed an algorithm called Gene Enrichment Motif Searching (GEMS) that uses a hypergeometric-based scoring function and a position-weight matrix optimization routine to identify with high-confidence regulatory elements in the nucleotide-biased and repeat sequence-rich <it>P. falciparum </it>genome. When applied to promoter regions of genes contained within 21 co-expression gene clusters generated from <it>P. falciparum </it>life cycle microarray data using the semi-supervised clustering algorithm Ontology-based Pattern Identification, GEMS identified 34 putative <it>cis</it>-regulatory elements associated with a variety of parasite processes including sexual development, cell invasion, antigenic variation and protein biosynthesis. Among these candidates were novel motifs, as well as many of the elements for which biological experimental evidence already exists in the <it>Plasmodium </it>literature. To provide evidence for the biological relevance of a cell invasion-related element predicted by GEMS, reporter gene and electrophoretic mobility shift assays were conducted.</p> <p>Conclusion</p> <p>This GEMS analysis demonstrates that <it>in silico </it>regulatory element discovery can be successfully applied to challenging repeat-sequence-rich, base-biased genomes such as that of <it>P. falciparum</it>. The fact that regulatory elements were predicted from a diverse range of functional gene clusters supports the hypothesis that <it>cis</it>-regulatory elements play a role in the transcriptional control of many <it>P. falciparum </it>biological processes. The putative regulatory elements described represent promising candidates for future biological investigation into the underlying transcriptional control mechanisms of gene regulation in malaria parasites.</p

Tumor cuproptosis and immune infiltration improve survival of patients with hepatocellular carcinoma with a high expression of ferredoxin 1

BackgroundCuproptosis is a novel cell death pathway dependent on cellular copper ions and ferredoxin 1 (FDX1). Hepatocellular carcinoma (HCC) is derived from healthy liver as a central organ for copper metabolism. It remains no conclusive evidence whether cuproptosis is involved in survival improvement of patients with HCC.MethodA 365–liver hepatocellular carcinoma (LIHC) cohort with RNA sequencing data and paired clinical and survival information was obtained from the The Cancer Genome Atlas (TCGA) dataset. A retrospective cohort of 57 patients with HCC with stages I/II/III was collected by Zhuhai People’s Hospital from August 2016 to January 2022. Low- or high-FDX1 groups were divided according to the median value of FDX1 expression. Cibersort, single-sample gene set enrichment analysis, and multiplex immunohistochemistry analyzed immune infiltration in LIHC and HCC cohorts. Cell proliferation and migration of HCC tissues and hepatic cancer cell lines were evaluated using the Cell Counting Kit-8. Quantitative real-time PCR and RNA interference measured and downregulated FDX1 expression. Statistical analysis was conducted by R and GraphPad Prism software.ResultsHigh FDX1 expression significantly enhanced survival of patients with LIHC from the TCGA dataset, which was also demonstrated through a retrospective cohort with 57 HCC cases. Immune infiltration was different between the low– and high–FDX1 expression groups. Natural killer cells, macrophages, and B cells were significantly enhanced, and PD-1 expression was low in the high-FDX1 tumor tissues. Meanwhile, we found that a high expression of FDX1 decreased cell viability in HCC samples. HepG2 cells with FDX1 expression are sensitive to Cu2+, and interference of FDX1 promoted proliferation and migration of tumor cells. The consistent results were also demonstrated in Hep3B cells.ConclusionThis study reveals that cuproptosis and tumor immune microenvironment were together involved in improvement of survival in patients with HCC with a high expression of FDX1

BASP1 is a prognostic biomarker associated with immunotherapeutic response in head and neck squamous cell carcinoma

BackgroundsImmunotherapy is effective in a subset of head and neck squamous cell carcinoma (HNSCC). However, the unfavorable response rate and inadequate biomarkers for stratifying patients have primarily limited its clinical application. Considering transcriptional factors (TFs) play essential roles in regulating immune activity during HNSCC progression, we comprehensively analyzed the expression alterations of TFs and their prognostic values.MethodsGene expression datasets and clinical information of HNSCC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repository. Then, Brain abundant membrane attached signal protein 1 (BASP1) was screened out of differentially expressed TFs by univariate and multivariate survival analysis. Tumor immune dysfunction and exclusion (TIDE) was applied to analyze the response to immunotherapy of BASP1high/low patients. Meanwhile, GO, KEGG and GSEA analyses were used to enrich the pathways between the BASP1high and BASP1low groups. Single-sample gene set enrichment analysis (ssGSEA), CIBERSORT, EPIC and quanTiseq algorithms were applied to explore immune infiltrations. Also, immune cycle analysis was conducted by ssGSEA. Additionally, lipid peroxidation, glutathione and reactive oxygen species were performed to detect the ferroptosis alternations.ResultsBASP1 was upregulated and associated with poor survival in HNSCC patients. BASP1high patients exhibited better response rates to anti-PD-1 immunotherapy and higher expressions of immune checkpoint inhibitors. GO, KEGG and GSEA analyses indicated that the expression of BASP1 was related to several immune-related pathways and immunogenic ferroptosis signature. The infiltration of activated CD8+ T cells was authenticated to be decreased in BASP1high patients. Furthermore, BASP1 was identified to be positively correlated with T cell dysfunction and immune escape. Moreover, silencing BASP1 triggered ferroptosis in HNSCC cells, representing as increased LDH, lipid peroxidation and ROS levels, and reduced glutathione synthesisConclusionsWe demonstrated that BASP1 suppressed immunogenic ferroptosis to induce immunosuppressive tumor microenvironment. BASP1 plays a critical role in immune response, and might be a promising classifier for selecting HNSCC patients who benefit from current immunotherapy