Identification of Key Genes and Pathways in Oxaliplatin-Induced Neuropathic Pain Through Bioinformatic Analysis.

Background: The mechanism of Chemotherapy-induced neuropathic pain (NP) remains obscure. This study was aimed to uncover the key genes as well as protein networks that contribute to Oxaliplatin-induced NP. Material/Methods: Oxaliplatin frequently results in a type of Chemotherapy-induced NP that is marked by heightened sensitivity to mechanical and cold stimuli, which can lead to intolerance and discontinuation of medication. We investigated whether these different etiologies lead to similar pathological outcomes by targeting shared genetic targets or signaling pathways. Gene expression data were obtained from the Gene Expression Comprehensive Database (GEO) for GSE38038 (representing differential expression in the spinal nerve ligation model rats) and GSE126773 (representing differential expression among the Oxaliplatin-induced NP model rats). Differential gene expression analysis was performed using GEO2R. Results: Protein-protein interaction (PPI) analysis identified 260 co-differentially expressed genes (co-DEGs). Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed three shared pathways involved in both models: Kaposi sarcoma-associated herpesvirus (KSHV) infection, Epstein-Barr virus (EBV) infection, and AGE-RAGE signaling pathway in diabetic complications. Further bioinformatics analysis highlighted eight significantly up-regulated genes in the NP group: Mapk14, Icam1, Cd44, IL6, Cxcr4, Stat1, Casp3 and Fgf2. Our results suggest that immune dysfunction, inflammation-related factors or regulating inflammation factors may also be related to Oxaliplatin-induced NP. Additionally, we analyzed a dataset (GSE145222) involving chronic compression of DRGs (CCD) and control groups. CCD model is a classic model for studying NP. We assessed these hub genes' expression levels. In contrast with the control groups, the hub genes were up-regulated in CCD groups, the difference was statistically significant, except Stat1. Conclusion: Our research significantly contributes to elucidating the mechanisms underlying the occurrence as well as the progression of Oxaliplatin-induced NP. We have identified crucial genes and signaling pathways associated with this condition.

Epigenomic tomography for probing spatially defined chromatin state in the brain.

Spatially resolved epigenomic profiling is critical for understanding biology in the mammalian brain. Single-cell spatial epigenomic assays were developed recently for this purpose, but they remain costly and labor intensive for examining brain tissues across substantial dimensions and surveying a collection of brain samples. Here, we demonstrate an approach, epigenomic tomography, that maps spatial epigenomes of mouse brain at the scale of centimeters. We individually profiled neuronal and glial fractions of mouse neocortex slices with 0.5 mm thickness. Tri-methylation of histone 3 at lysine 27 (H3K27me3) or acetylation of histone 3 at lysine 27 (H3K27ac) features across these slices were grouped into clusters based on their spatial variation patterns to form epigenomic brain maps. As a proof of principle, our approach reveals striking dynamics in the frontal cortex due to kainic-acid-induced seizure, linked with transmembrane ion transporters, exocytosis of synaptic vesicles, and secretion of neurotransmitters. Epigenomic tomography provides a powerful and cost-effective tool for characterizing brain disorders based on the spatial epigenome.

Spatiotemporal estimations of temperature rise during electroporation treatments using a deep neural network.

The nonthermal mechanism for irreversible electroporation has been paramount for treating tumors and cardiac tissue in anatomically sensitive areas, where there is concern about damage to nearby bowels, ducts, blood vessels, or nerves. However, Joule heating still occurs as a secondary effect of applying current through a resistive tissue and must be minimized to maintain the benefits of electroporation at high voltages. Numerous thermal mitigation protocols have been proposed to minimize temperature rise, but intraoperative temperature monitoring is still needed. We show that an accurate and robust temperature prediction AI model can be developed using estimated tissue properties (bulk and dynamic conductivity), known geometric properties (probe spacing), and easily measurable treatment parameters (applied voltage, current, and pulse number). We develop the 2-layer neural network on realistic 2D finite element model simulations with conditions encompassing most electroporation applications. Calculating feature contributions, we found that temperature prediction is mostly dependent on current and pulse number and show that the model remains accurate when incorrect tissue properties are intentionally used as input parameters. Lastly, we show that the model can predict temperature rise within ex vivo perfused porcine livers, with error <0.5 °C. This model, using easily acquired parameters, is shown to predict temperature rise in over 1000 unique test conditions with <1 °C error and no observable outliers. We believe the use of simple, readily available input parameters would allow this model to be incorporated in many already available electroporation systems for real-time temperature estimations.

Subpopulation-specific machine learning prognosis for underrepresented patients with double prioritized bias correction.

Background: Many clinical datasets are intrinsically imbalanced, dominated by overwhelming majority groups. Off-the-shelf machine learning models that optimize the prognosis of majority patient types (e.g., healthy class) may cause substantial errors on the minority prediction class (e.g., disease class) and demographic subgroups (e.g., Black or young patients). In the typical one-machine-learning-model-fits-all paradigm, racial and age disparities are likely to exist, but unreported. In addition, some widely used whole-population metrics give misleading results. Methods: We design a double prioritized (DP) bias correction technique to mitigate representational biases in machine learning-based prognosis. Our method trains customized machine learning models for specific ethnicity or age groups, a substantial departure from the one-model-predicts-all convention. We compare with other sampling and reweighting techniques in mortality and cancer survivability prediction tasks. Results: We first provide empirical evidence showing various prediction deficiencies in a typical machine learning setting without bias correction. For example, missed death cases are 3.14 times higher than missed survival cases for mortality prediction. Then, we show DP consistently boosts the minority class recall for underrepresented groups, by up to 38.0%. DP also reduces relative disparities across race and age groups, e.g., up to 88.0% better than the 8 existing sampling solutions in terms of the relative disparity of minority class recall. Cross-race and cross-age-group evaluation also suggests the need for subpopulation-specific machine learning models. Conclusions: Biases exist in the widely accepted one-machine-learning-model-fits-all-population approach. We invent a bias correction method that produces specialized machine learning prognostication models for underrepresented racial and age groups. This technique may reduce potentially life-threatening prediction mistakes for minority populations.

Label-free detection of biomolecular interactions using BioLayer interferometry for kinetic characterization.

The analysis of biomolecular interactions is key in the drug development process. Label-free biosensor methods provide information on binding, kinetics, concentration, and the affinity of an interaction. These techniques provide real-time monitoring of interactions between an immobilized ligand (such as a receptor) to an analyte in solution without the use of labels. Advances in biosensor design and detection using BioLayer Interferometry (BLI) provide a simple platform that enables label-free monitoring of biomolecular interactions without the use of flow cells. We review the applications of BLI in a wide variety of research and development environments for quantifying antibodies and proteins and measuring kinetics parameters.

Matching base-pair number dependence of the kinetics of DNA-DNA hybridization studied by surface plasmon fluorescence spectroscopy.

Two single-stranded DNA oligonucleotides consisting of complementary base-pairs can form double strands. This phenomenon is well studied in solutions, however, in order to clarify the physical mechanism of the hybridization occurring at a solid/solution interface, we studied the kinetics by surface plasmon fluorescence spectroscopy (SPFS): one single-stranded oligo-DNA (probe-DNA) was immobilized on the substrate, the other one (target-DNA) labelled with a fluorescent probe was added to the flow cell. After hybridization, the chromophores could be excited by the surface plasmon mode and their fluorescence detected with high sensitivity. The dependence of the k(on) and k(off) rate constants on the length of the hybridizing oligonucleotides was investigated by using a MM0 series (no mismatch) and the kinetics was found to be well described by a Langmuir adsorption model. From these measurements we found that also in the case of surface hybridization the affinity of the duplexes decreases as the number of matching base-pairs decreases from 15 to 10. In order to show that SPFS is the powerful technique with high sensitivity, the hybridization process for mixed target-oligos was measured by SPFS and analyzed by an expanded Langmuir model in which two components of target-oligo can bind to probe-DNA at the sensor surface competitively. Two sets of the k(on) and k(off) obtained from the experiment are successfully consistent with the k(on) and k(off) obtained from experiments for single (pure) target-DNA.

Surface density dependence of PCR amplicon hybridization on PNA/DNA probe layers.

Surface plasmon field-enhanced fluorescence spectroscopy was employed to extensively investigate the hybridization behaviors of polymerase chain reaction (PCR) amplicons on a peptide nucleic acid (PNA) or DNA probe layer that was previously attached on a streptavidin-modified gold surface via biotin/streptavidin interaction. Despite the neutral backbone of PNA, the hybridization reactions were strongly influenced by the variation of ionic strength. The association rates exhibited a monotonic decrease with ionic strength increase and the maximum hybridization signal was achieved at an intermediate sodium concentration (approximately 100 mM). These effects were mainly ascribed to the electrostatic cross talk among the hybridized DNA molecules and the secondary structure of PCR amplicons. For the negatively charged DNA probes, the hybridization reaction was subjected additionally to the DNA/DNA electrostatic barrier, particularly in lower ionic strength range (e.g., 10 approximately 150 mM Na(+)). The electrostatic cross talk was shown to be largely reduced if the PNA probe layer was sufficiently diluted by following a strategic templated immobilization method. As a consequence, a pseudo-first-order kinetic model was applicable to describe the hybridization kinetics, and affinity constants were derived for evaluating the influence of single nucleotide polymorphisms (SNPs).

Surface plasmon field-enhanced fluorescence spectroscopy in PCR product analysis by peptide nucleic acid probes.

Surface plasmon field-enhanced fluorescence spectroscopy (SPFS) was recently developed for PCR product analysis, which allowed for real-time monitoring of hybridization processes and for the detection of trace amounts of PCR products, with a detection limit of 100 fmol on the peptide nucleic acid (PNA) probe surface, and 500 fmol on the DNA probe surface. By selectively labeling the strands of PCR-amplified DNA, it was shown that the heat denaturation process in combination with the application of low-salt condition substantially reduced the interference from the antisense strands and thus simplified the surface hybridization. Furthermore, SPFS was demonstrated to be capable of quantitatively discriminating the difference induced by single nucleotide substitution, even within one minute of contact time.

Surface plasmon enhanced diffraction for label-free biosensing.

Surface plasmon enhanced evanescent field at a (noble) metal/dielectric interface can be employed to enhance the diffraction efficiency of surface grating structure composed of biomolecules. Based on a Kretschmann configuration, we realized a diffraction biosensor to monitor the dynamic interaction of biological molecules in a label-free way. It was demonstrated by the binding of an anti-biotin antibody to the biotin-functionalized region of a periodically patterned surface, which generated significant optical contrast to diffract the surface plasmon field. With the aid of the synchronic surface plasmon resonance signal, a quadratic dependence of diffraction signal on the amount of bound antibody was found, which coincides with the theoretical expectation. Time-dependent measurements were conducted to estimate the density of biotin thiols on the functional region.

Oligonucleotide hybridization studied by a surface plasmon diffraction sensor (SPDS).

A novel label-free biosensor concept based on surface plasmon-enhanced diffraction by micro- patterned interfaces was applied to the study of hybridization reactions of target DNA oligonucleotides (15mers and 75mers) from solution to probe DNA oligonucleotides attached via streptavidin to the sensor surface. The self-referencing and quadratic signal amplification mechanism of the sensor allowed highly sensitive detection of the hybridization process. Association and dissociation processes of DNA targets could be recorded in real time and used for the quantification of their binding affinities, which differ considerably with a single base pair mismatch. An equilibrium titration approach was also applied in order to obtain the binding affinities for 15mer targets, yielding similar affinity values. The hybridization efficiencies were found to be higher for the 15mers than for the 75mers, although the latter contained the same recognition sequences. The hybridization efficiency was shown to depend on the probe density and reached nearly 100% for the 15mer fully complementary targets at a probe density of approximately 1.2 x 10(12) molecules/cm2. Using the assay as an end-point determination method, the lowest detectable coverage of a 15mer oligonucleotide was at least approximately 1.1 x 10(11) molecules/cm2. The diffraction sensing concept offers a completely novel way to integrate a reference channel in large-scale, label-free screening applications, to improve the stability and to enhance the sensitivity of microarray read-out systems.

Surface plasmon field-enhanced fluorescence spectroscopy studies of the interaction between an antibody and its surface-coupled antigen.

Surface plasmon field-enhanced fluorescence spectroscopy (SPFS) uses the greatly enhanced electromagnetic field of a surface plasmon mode for the excitation of surface-confined fluorophores. The ability to simultaneously monitor the interfacial refractive index changes and the fluorescence signals in real time offers a huge potential for applications of SPFS in surface immunoreaction detection. In this study, gold surfaces were functionalized by mixed self-assembled monolayers exposing an antigen (biotin) at a density that was varied over a wide range. Specific antibody-antigen interactions were observed for anti-biotin antibody solutions passing over the surfaces with a rather high flow speed driven by a home-built liquid-handling system. First, the use of the fluorophores Cy5 and Alexa Fluor 647 in SFPS-based immunoassays was investigated. It was found that Cy5 exhibits strong self-quenching, which makes it rather unsuitable for quantitative measurements. For the in situ measurement of the binding kinetics, an angular "detuning" effect was confirmed to negatively interfere with the fluorescence signal in cases where large SPR signals were detected. An in-depth comparison between the SPR and the fluorescence signal reveals that the fluorescence yield of the dyes depends strongly on the separation distance from the gold surface. And finally, we stress the ability of SPFS to detect binding to surfaces containing extremely diluted antigen density, where the SPR signal failed to follow.