Estimating the proportion of true null hypotheses and adaptive false discovery rate control in discrete paradigm.

Storey's estimator for the proportion of true null hypotheses, originally proposed under the continuous framework, has been modified in this work under the discrete framework. The modification results in improved estimation of the parameter of interest. The proposed estimator is used to formulate an adaptive version of the Benjamini-Hochberg procedure. Control over the false discovery rate by the proposed adaptive procedure has been proved analytically. The proposed estimate is also used to formulate an adaptive version of the Benjamini-Hochberg-Heyse procedure. Simulation experiments establish the conservative nature of this new adaptive procedure. Substantial amount of gain in power is observed for the new adaptive procedures over the standard procedures. For demonstration of the proposed method, two important real life gene expression data sets, one related to the study of HIV and the other related to methylation study, are used.

Bias-corrected estimators for proportion of true null hypotheses: application of adaptive FDR-controlling in segmented failure data.

Two recently introduced model-based bias-corrected estimators for proportion of true null hypotheses ( π 0 ) under multiple hypotheses testing scenario have been restructured for random observations under a suitable failure model, available for each of the common hypotheses. Based on stochastic ordering, a new motivation behind formulation of some related estimators for π 0 is given. The reduction of bias for the model-based estimators are theoretically justified and algorithms for computing the estimators are also presented. The estimators are also used to formulate a popular adaptive multiple testing procedure. Extensive numerical study supports superiority of the bias-corrected estimators. The necessity of the proper distributional assumption for the failure data in the context of the model-based bias-corrected method has been highlighted. A case-study is done with a real-life dataset in connection with reliability and warranty studies to demonstrate the applicability of the procedure, under a non-Gaussian setup. The results obtained are in line with the intuition and experience of the subject expert. An intriguing discussion has been attempted to conclude the article that also indicates the future scope of study.

Estimation of the proportion of true null hypotheses under sparse dependence: Adaptive FDR controlling in microarray data.

The proportion of non-differentially expressed genes is an important quantity in microarray data analysis and an appropriate estimate of the same is used to construct adaptive multiple testing procedures. Most of the estimators for the proportion of true null hypotheses based on the thresholding, maximum likelihood and density estimation approaches assume independence among the gene expressions. Usually, sparse dependence structure is natural in modelling associations in microarray gene expression data and hence it is necessary to develop methods for accommodating the sparse dependence well within the framework of existing estimators. We propose a clustering based method to put genes in the same group that are not coexpressed using the estimated high dimensional correlation structure under sparse assumption as dissimilarity matrix. This novel method is applied to three existing estimators for the proportion of true null hypotheses. Extensive simulation study shows that the proposed method improves an existing estimator by making it less conservative and the corresponding adaptive Benjamini-Hochberg algorithm more powerful. The proposed method is applied to a microarray gene expression dataset of colorectal cancer patients and the results show gain in terms of number of differentially expressed genes. The R code is available at https://github.com/aniketstat/Proportiontion-of-true-null-under-sparse-dependence-2021.

Multidomain-Based Responsive Materials with Dual-Mode Optical Readouts.

Responsive materials designed to generate signals for both surface-enhanced Raman spectroscopy (SERS) and phosphorescence lifetime-"dual-mode"-measurements are described. To demonstrate this concept, we incorporated pH-sensitive and oxygen-sensitive microdomains into a single hydrogel that could be interrogated via SERS and phosphorescence lifetime, respectively. Microdomains consisted two populations of discrete microcapsules containing either (1) gold nanoparticles capped with pH-sensitive Raman molecules or (2) oxygen-sensitive benzoporphyrin phosphors. While the microdomain-embedded hydrogels presented an expected background luminescence, the pH-sensitive SERS signal was distinguishable for all tested conditions. Response characteristics of the dual sensor showed no significant difference when compared to standalone single-mode pH and oxygen sensors. In addition, the feasibility of redundant multimode sensing was proven by observing the reaction produced by glucose oxidase chemically cross-linked within the corresponding alginate matrix. Each optical mode showed a signal change proportional to glucose concentration with an opposite signal directionality. These results support the promise of micro-/nanocomposite materials to improve measurement accuracy using intrinsic multimode responses and built-in redundancy, concepts that have broad appeal in the chemical sensing and biosensing fields.

Composite Hydrogels Containing Bioactive Microreactors for Optical Enzymatic Lactate Sensing.

Continuously monitoring specific biomarkers offer a promising method to interrogate disease status and progression. In this work we have demonstrated a composite hydrogel-based sensing platform that may be used for optical detection of lactate. The sensor design consists of microsized enzymatic sensors that are embedded in an outer hydrogel matrix. In these engineered microdomains, encapsulated lactate oxidase serves as the bioactive component, phosphorescent metalloporphyrin acts as the optical transducer, and polyelectrolyte multilayers coated on the enzymatic microsensors control the permeation of lactate into the microsensors. The response of the composite hydrogel-based lactate sensors was characterized by subjecting the sensors to lactate concentration challenges at low physiological oxygen levels. The analytical range and the mean sensitivity were determined to be 9.2 ± 0.83 mg/dL and 11 ± 0.90% dL mg-1, respectively. Repeated cyclic exposure to high levels of lactate revealed that these sensors were extremely stable, with no significant loss in sensor response after 20 cycles. These preliminary results support the premise that these composite hydrogels are capable of continuous lactate tracking and have the potential for use as fully implantable optical lactate sensors.

Composite Hydrogels with Engineered Microdomains for Optical Glucose Sensing at Low Oxygen Conditions.

There is a growing need for advanced tools that enable frequent monitoring of biomarkers for precision medicine. In this work, we present a composite hydrogel-based system providing real-time optical bioanalyte monitoring. The responsive material, alginate-in-alginate (AnA), is comprised of an alginate hydrogel with embedded bioactive, nanofilm-coated phosphorescent microdomains; palladium tetracarboxyphenylporphyrin serves as an optical indicator, glucose oxidase as a model enzyme, and layer-by-layer deposited polyelectrolyte multilayers (PEMs) as the diffusion barrier. Glutaraldehyde crosslinking of the nanofilms resulted in a dramatic reduction in glucose diffusion (179%) while oxygen transport was not significantly affected. The responses of the AnA hydrogels to step changes of glucose at both ambient and physiological oxygen levels were evaluated, revealing controlled tuning of sensitivity and dynamic range. Stability, assessed by alternately exposing the responsive AnA hydrogels to extremely high and zero glucose concentrations, resulted in no significant difference in the response over 20 cycles. These AnA hydrogels represent an attractive approach to biosensing based on biocompatible materials that may be used as minimally-invasive, implantable devices capable of optical interrogation. The model glucose-responsive composite material studied in this work will serve as a template that can be translated for sensing additional analytes (e.g., lactate, urea, pyruvate, cholesterol) and can be used for monitoring other chronic conditions.

Gold Nanocluster Containing Polymeric Microcapsules for Intracellular Ratiometric Fluorescence Biosensing.

A new approach to sensing and imaging hydrogen peroxide (H2O2) was developed using microcapsule-based dual-emission ratiometric luminescent biosensors. Bovine serum albumin-capped gold nanoclusters (BSA-AuNCs) sensitive to H2O2 were coencapsulated with insensitive FluoSpheres (FSs) within polymeric capsules fabricated via the layer-by-layer method. Under single-wavelength excitation, the microcapsule-based biosensors exhibited emission bands at ∼516 and ∼682 nm resulting from the FSs and BSA-AuNCs, respectively. The polyelectrolyte multilayers lining the microcapsules were effective in protecting BSA-AuNCs from the degradation catalyzed by proteases (chymotrypsin, trypsin, papain, and proteinase K) and subsequent luminescent quenching, overcoming a key limitation of prior BSA-AuNC-based sensing systems. The luminescent response of the sensors was also found to be independent of local changes in pH (5-9). Quenching of the AuNCs in the presence of H2O2 enabled the spectroscopic quantification and imaging of changes in H2O2 concentration from 0 to 1 mM. The microcapsule sensors were easily phagocytized by murine macrophage cells (RAW 264.7), were effective as intracellular H2O2 imaging probes, and were successfully used to detect local release of H2O2 in response to an external chemical stimulus.

Fabrication of nanocapsule carriers from multilayer-coated vaterite calcium carbonate nanoparticles.

Nanosized luminescent sensors were prepared as reagents for optical sensing and imaging of oxygen using ratiometric emission properties of a two-dye system. Polymeric capsules were fabricated utilizing poly(vinylsulfonic acid) (PVSA)-stabilized vaterite CaCO3 nanoparticles (CCNPs) as sacrificial templates. The buffer and polymeric surfactant requirements of the layer-by-layer (LbL) process were evaluated toward deposition of multilayer coatings and, ultimately, formation of hollow capsules using these interesting materials. CCNPs were found to be more stable in alkaline NaHCO3 buffer after repeated cycles of washing under sonication and resuspension. An intermediate PVSA concentration was required to maximize the loading of oxygen-sensitive porphyrin and oxygen-insensitive fluorescent nanoparticles in the CCNPs while maintaining minimal nanoparticle size. The CCNPs were then coated with polyelectrolyte multilayers and subsequent removal of the CaCO3 core yielded nanocapsules containing dye and fluorescent nanoparticles. The resulting nanocapsules with encapsulated luminophores functioned effectively as oxygen sensors with a quenching response of 89.28 ± 2.59%, and O2 (S = 1/2) = 20.91 µM of dissolved oxygen.