Dynamic Range Research Articles

Software Integrated Personalized Biosensing Device for Serum Creatinine Detection Based on Boron doped MXene Nanohybrid.

In recent years, an increase in the number of chronic kidney disease (CKD) cases has led to a global health burden majorly affecting underdeveloped and developing nations. A key biomarker for assessing the kidneys' normal functioning is creatinine, which is filtered out from the blood by the kidney. Thus, timely and specific detection of creatinine becomes necessary for diagnosis and subsequent treatment of CKD. Hence, in this study, we have tried to develop a field-deployable, software-integrated immunosensor for the detection of creatinine in a serum sample. The immunosensor was developed by incorporating gold nanoparticles, boron doped MXene, polyaniline, and anticreatinine antibody using an appropriate bioconjugation reaction. The developed sensor was able to detect creatinine in a linear dynamic range of 10 nM to 0.1 M with a limit of detection of 1.72 (±0.07) nM. The sensor was integrated with an indigenously developed software named "CretCheck" which simplifies the process of data analysis. The software integrated personalized biosensing device was used to find the creatinine concentrations directly from the obtained analytical signals. The developed immunosensor with the integrated software can also be implemented directly in primary health care facilities for creatinine detection in the future.

B-310 Freezing and thawing serum without mixing prior to analysis causes false low Thyroglobulin results

Abstract Background Thyroglobulin (Tg), a glycoprotein that is synthesized in follicular cells of the thyroid gland, is the precursor of Thyroxin (T4) and Triiodothyronine (T3). Tg is a biomarker used for many clinical conditions, including monitoring for recurrence in patients with differentiated thyroid carcinoma. Typically, Tg levels drop to very low or undetectable levels after surgical excision and/or radioiodine ablation of the thyroid, with post-operative levels greater than 1-2 ng/ml indicating potential disease recurrence. Discordant Tg results in a patient sample were identified during a quality check of Tg results. This study investigates the root of cause of the discrepant Tg results. Given that: 1) Tg analyses were performed twice a week at our laboratory due to low daily test volume and patients’ samples received on an unanalytical day were stored at -20°C until analysis; 2) Tg analyses were performed by various medical technologists; 3) sample mixation prior to analysis was not routine practice for our automated laboratory, we hypothesized that the discrepancy was due to inconsistent sample handling, e.g., mixation vs unmixation prior to analysis. Methods Analysis of the daily QC and PT results in the period of the incident occurence ruled out causes in analytical phase. We split 52 de-identified patient serum samples into two equal aliquots and subsequently stored both aliquots at -20°C for 48 hours. Both aliquots of each sample were thawed at room temperature for 1 hour. One of the aliquots was analyzed for Tg without mixing, and the other was analyzed after mixing using a Vortexer for 4 seconds at 250 xg. To investigate if Tg concentrations form a gradient from the top to the bottom of a red-top vacutainer tube, five patient samples with Tg at 2.59, 2.79, 2.92, 52.37 and 144.12 ng/mL were thawed without mixing following storage at -20°C for 48 hours. Five layer (600 μl/layer) aliquots were carefully and sequentially taken from top to bottom for each specimen, and the Tg concentration in the aliquot of each layer was determined using the Beckman Coulter Access-2 Immunoassay. Results Of the 52 patients samples, 14 Tg results were excluded from statistical analysis due to exceeding the assay dynamic range (2 above and 12 below the upper and low limits, respectively). Analysis of the remaining 38 patient samples showed the mean of Tg concentrations was 22.8% (SD 18%) higher in mixed samples than the un-mixed samples. Regression analysis showed an R2 = 0.9976 (Mixed Tg = 1.1523 x Un-mixed + 0.4174, range 0.1 - 275.7 ng/mL, intercept 95%CI -0.721 to 1.556, slop 95%CI 1.1331 to 1.1715, p-value <0.001). Results of Tg gradient analysis showed significant higher Tg values in the 2nd, 3rd, 4th and 5th than the 1st layer by 26% (SD 11%), 63% (26%), 112% (57%), and 160% (76%), respectively. Conclusions False Tg values were found in samples without mixing before analysis after thawing from frozen state, due to formation of Tg concentration gradient in test tube. For obtaining reliable results, samples must be mixed before analysis when thawed from frozen storage.

Chemical mapping of the surface interactome of PIEZO1 identifies CADM1 as a modulator of channel inactivation

The propeller-shaped blades of the PIEZO1 and PIEZO2 ion channels partition into the plasma membrane and respond to indentation or stretching of the lipid bilayer, thus converting mechanical forces into signals that can be interpreted by cells, in the form of calcium flux and changes in membrane potential. While PIEZO channels participate in diverse physiological processes, from sensing the shear stress of blood flow in the vasculature to detecting touch through mechanoreceptors in the skin, the molecular details that enable these mechanosensors to tune their responses over a vast dynamic range of forces remain largely uncharacterized. To survey the molecular landscape surrounding PIEZO channels at the cell surface, we employed a mass spectrometry-based proteomic approach to capture and identify extracellularly exposed proteins in the vicinity of PIEZO1. This PIEZO1-proximal interactome was enriched in surface proteins localized to cell junctions and signaling hubs within the plasma membrane. Functional screening of these interaction candidates by calcium imaging and electrophysiology in an overexpression system identified the adhesion molecule CADM1/SynCAM that slows the inactivation kinetics of PIEZO1 with little effect on PIEZO2. Conversely, we found that CADM1 knockdown accelerates inactivation of endogenous PIEZO1 in Neuro-2a cells. Systematic deletion of CADM1 domains indicates that the transmembrane region is critical for the observed effects on PIEZO1, suggesting that modulation of inactivation is mediated by interactions in or near the lipid bilayer.

LC-MS/MS Quantification of Endocannabinoids in Tissues.

Endocannabinoids (ECBs) are lipid-derived endogenous molecules with important physiological roles such as regulation of energy balance, immunity, or neural development. Quantitation of ECBs helps better understand their physiological role and modulation of biological processes. This chapter presents the simultaneous quantification of 14 ECBs and related molecules in the brain, liver, and muscle, as well as white and brown adipose tissue using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The dynamic range of the method has been tuned to cover the endogenous concentrations of these analytes given the fact that they are endogenously present at different orders of magnitude. Specifically, three groups are established: 0.5-5000ng/mL for 2-oleoyl- and 2-linoleoylglycerol and arachidonic acid, 0.05-500ng/mL for 2-arachidonoylglycerol, and 0.0005-0.5ng/mL for anandamide, palmitoyl-, palmitoleoyl-, stearoyl-, oleoyl-, linoleoyl-, alpha-linolenoyl-, dihomo-gamma-linolenoyl-, docosahexaenoyl-, and pentadecanoylethanolamide.

Rapid Assessment of Biomarkers on Single Extracellular Vesicles Using "Catch and Display" on Ultrathin Nanoporous Silicon Nitride Membranes.

Extracellular vesicles (EVs) are particles released from cells that facilitate intercellular communication and have tremendous diagnostic and therapeutic potential. Bulk assays lack the sensitivity to detect rare EV subsets relevant to disease, and while single EV analysis techniques remedy this, they are often undermined by complicated detection schemes and prohibitive instrumentation. To address these issues, a microfluidic technique for EV characterization called "catch and display for liquid biopsy (CAD-LB)" is proposed. In this method, minimally processed samples are pipette-injected and fluorescently labeled EVs are captured in the nanopores of an ultrathin membrane. This enables the rapid assessment of EV number and biomarker colocalization by light microscopy. Here, nanoparticles are used to define the accuracy and dynamic range for counting and colocalization. The same assessments are then made for purified EVs and for unpurified EVs in plasma. Biomarker detection is validated using CD9 and Western blot analysis to confirm that CAD-LB accurately reports relative protein expression levels. Using unprocessed conditioned media,CAD-LB captures the known increase in EV-associated ICAM-1 following endothelial cell cytokine stimulation. Finally, to demonstrate CAD-LB's clinical potential, EV biomarkers indicative of immunotherapy responsiveness are successfully detected in the plasma of bladder cancer patients treated with immune checkpoint blockade.

High-Throughput RPLC-MS/MS Quantification of Short- and Medium-Chain Fatty Acids.

Short- and medium-chain fatty acids (SMCFA) are monocarboxylic acids with a carbon chain length of 1-12 carbon atoms. They are mainly produced in humans by the gut microbiota, play crucial metabolic roles, are vital for intestinal health, and have multifaceted impact on immune and neurological functions. Accurate detection and quantification of SMCFA in different human biofluids is achieved using 3-nitro phenylhydrazine (3-NPH) derivatization of the free fatty acids followed by reverse phase liquid chromatography (RPLC) separation and detection by tandem mass spectrometry (MS/MS). Here, we describe the simultaneous measurement of 14 SMCFA and lactate in detail. All 3-NPH-SMCFA-hydrazones are separated in less than 5min with an 8-min total run time (injection-to-injection). Linear dynamic range over 0.1-500μM is achieved for most SCFAs, while it is 0.05-100μM for MCFAs. Validation of the procedure depicts good linearity (R2>0.98) and repeatability (CV≤20%). The lower limit of detection (LLOD) is 10-30nM. The lower limit of quantification (LLOQ) is 50-100nM for most analytes, while it is 0.5μM for acetate. In conclusion, the method offers several benefits compared to alternative methods regarding throughput, selectivity, sensitivity, and robustness.

Large-Angle Rocking Beam Electron Diffraction of Large Unit Cell Crystals Using Direct Electron Detector.

We report a large-angle rocking beam electron diffraction (LARBED) technique for electron diffraction analysis. Diffraction patterns are recorded in a scanning transmission electron microscope (STEM) using a direct electron detector with large dynamical range and fast readout. We use a nanobeam for diffraction and perform the beam double rocking by synchronizing the detector with the STEM scan coils for the recording. Using this approach, large-angle convergent beam electron diffraction (LACBED) patterns of different reflections are obtained simultaneously. By using a nanobeam, instead of a focused beam, the LARBED technique can be applied to beam-sensitive crystals as well as crystals with large unit cells. This paper describes the implementation of LARBED and evaluates the performance using silicon and gadolinium gallium garnet crystals as test samples. We demonstrate that our method provides an effective and robust way for recording LARBED patterns and paves the way for quantitative electron diffraction of large unit cell and beam-sensitive crystals.

A-306 High Sensitivity Capability of an Anti-müllerian Hormone Assay on the Beckman Coulter DxI 9000 Immunoassay Analyzer*, a Next Step Toward Enabling Ovarian Failure Staging?

Abstract Background Measurement of anti-müllerian hormone (AMH) has proven value in the evaluation of ovarian reserve using assays such as the Beckman Coulter Access AMH assay. If improved sensitivity of AMH measurement can be achieved, enhanced clinical utility during the assessment of reproductive aging and ovarian response to enable staging of ovarian failure is possible (Practice Committee of the American Society of Reproductive Medicine 2020, Cappola et al. 2023). The Beckman Coulter DxI 9000 Immunoassay Analyzer* has been designed with new technology that can be leveraged to improve assay sensitivity. Such technological advancements include the new Lumi-Phos PRO chemiluminescent substrate which yields markedly increased signal-to-noise, a new luminometer with increased dynamic range, and improved low-volume pipetting capabilities. Data herein summarize results from analytical verification studies of the Access AMH assay on the DxI 9000 Immunoassay Analyzer. Results demonstrate an example of DxI 9000 technologies enabling sensitivity claims that are up to 20-fold improved. * The official name is DxI 9000 Access Immunoassay Analyzer. Methods A method comparison study was performed based on CLSI guideline EP09c, 3rd ed. to compare results for the Access AMH assay on DxI 9000 to the predicate device, the Access AMH assay on the Access 2 Immunoassay System. Within-laboratory precision was also evaluated following CLSI EP05-A3. Finally, performance at low analyte levels was evaluated following CLSI EP17-A2, and linearity was evaluated following CLSI EP06-Ed2. Results Method comparison of the Access AMH assay on DxI 9000 compared to the Access AMH assay on the Access 2 yielded excellent agreement with a Passing-Bablok slope of 1.02 for N=126 samples. Further, bias estimates for a number of key medical decision points suggest minimal bias (≤ 2%) across the assay range, and minimal non-linearity was observed. 20-day imprecision studies yielded CV’s between 2 and 5% across a broad range of concentrations evaluated. Sensitivity studies yielded estimates of limit of quantitation (LoQ) between 0.001 and 0.003 ng/mL. This represents an approximately 10- to 20-fold improvement in sensitivity claims compared to the AMH assay on the Access 2 and other commercially available automated immunoassay analyzers. Conclusions The data herein present performance data for the Access AMH assay on the DxI 9000 Immunoassay Analyzer. The assay demonstrates excellent accuracy relative to the predicate device, while showing good linearity and imprecision. Of note, the Access AMH assay exhibits exceptional low-end performance on the DxI 9000 analyzer as demonstrated by the ability to enable sensitivity claims that are up to 20-fold improved in comparison to existing immunoassays for the measurement of AMH. The sensitivity capabilities of the Access AMH assay on DxI 9000 suggest an opportunity for the addition of further intended uses for scenarios where extremely low AMH measurements can provide additional value of clinical significance. Further studies are needed to fully understand additional clinical utilities of the Access AMH assay with high sensitivity capability on DxI 9000, including the assessment of reproductive aging for menopause diagnosis or ovarian response for fertility treatment.

Towards Interpretable Physical‐Conceptual Catchment‐Scale Hydrological Modeling Using the Mass‐Conserving‐Perceptron

AbstractWe investigate the applicability of machine learning technologies to the development of parsimonious, interpretable, catchment‐scale hydrologic models using directed‐graph architectures based on the mass‐conserving perceptron (MCP) as the fundamental computational unit. Here, we focus on architectural complexity (depth) at a single location, rather than universal applicability (breadth) across large samples of catchments. The goal is to discover a minimal representation (numbers of cell‐states and flow paths) that represents the dominant processes that can explain the input‐state‐output behaviors of a given catchment, with particular emphasis given to simulating the full range (high, medium, and low) of flow dynamics. We find that a “HyMod Like” architecture with three cell‐states and two major flow pathways achieves such a representation at our study location, but that the additional incorporation of an input‐bypass mechanism significantly improves the timing and shape of the hydrograph, while the inclusion of bi‐directional groundwater mass exchanges significantly enhances the simulation of baseflow. Overall, our results demonstrate the importance of using multiple diagnostic metrics for model evaluation, while highlighting the need for properly selecting and designing the training metrics based on information‐theoretic foundations that are better suited to extracting information across the full range of flow dynamics. This study sets the stage for interpretable regional‐scale MCP‐based hydrological modeling (using large sample data) by using neural architecture search to determine appropriate minimal representations for catchments in different hydroclimatic regimes.

Flame Photometry: For the Determination of Alkali Metals in Commercially Sold Fireworks

The alkali and alkaline earth metals such as potassium, sodium, barium and strontium are generally used as oxidizer in fireworks. The arbitrary use of these chemicals in fireworks is an acute issue responsible for higher emissions. Hence, efforts are underway to monitor these chemicals in fireworks. This work reports the precise determination of potassium and sodium in fireworks samples by flame photometry. The average deviation by flame photometry analysis was 7 to 8 % and 3 to 4 % for potassium and sodium, respectively, when the concentration of the respective metal nitrates in fireworks composition was less than 50%. The effect of different components in fireworks mixture, such as nitrate and metal precursor, were also studied to understand their impact on results. A brief study in terms of limit of detection (LOD), limit of quantification (LOQ) and dynamic range was also performed, which showed 0.42 and 3.26 mg/L as LOD and 1.29 and 9.88 mg L-1 as LOQ for the analysis of sodium and potassium, respectively. In summary, the study proved the prospective of flame photometry for determining sodium and potassium in fireworks samples.

Ultrafast metaproteomics for quantitative assessment of strain isolates and microbiomes

BackgroundMicrobial communities are essential in human health and environmental regulation, but present a challenge for the analytical science due to their diversity and dynamic range. Tandem mass spectrometry provides functional insights on microbial life cycle, but is time-consuming. MALDI TOF excels in rapid species identification, but not functional assessment. To address critical challenges in human health and environmental sustainability, microbiology needs advanced mass spectrometry methods and bioinformatic tools enabling both rapid identification and accurate assessment of functional activity of microbial communities. ResultsWe show for the first time that both identity and functional activity of microorganisms and their communities can be accurately determined in experiments as short as 7 min per sample, using the basic Orbitrap MS configuration without peptide fragmentation. The approach was validated using strain isolates, mock microbiomes composed of bacteria spiked at known concentrations and human fecal microbiomes. Our new bioinformatic algorithm identifies the bacterial species with an accuracy of 95 %, when no prior information on the sample is available. Microbiome composition was resolved at the genus level with the mean difference between the actual and identified components of 12 %. For mock microbiomes, Pearson coefficient of up to 0.97 was achieved in estimates of strain biomass change. By the example of Rhodococcus biodegradation of n-alkanes, phenols and its derivatives, we showed the accurate assessment of functional activity of strain isolates, compared with the standard label-free and label-based approaches. SignificanceOur approach makes microbial proteomics fast, functional and insightful using the Orbitrap instruments even without employing peptide fragmentation technology. The approach can be applied to any microorganisms and can take a niche in routine functional assessment of microbial pathogens and consortiums in clinical diagnostics together with MALDI TOF MS and 16S rRNA gene sequencing.

Quantification measurement of hemoglobin with large dynamic range and low detection limit via an optical fiber optofluidic laser with enzyme-catalyzed reaction

Quantitative measurement of hemoglobin (Hb) levels is an essential part of routine medical examinations, disease diagnosis and health status monitoring. In this study, we introduced optical fiber optofluidic laser (FOFL) technology combined with catalytic oxidation reaction to design a laser sensor for sensitive Hb detection. For the H2O2-rhodamine B (RhB) oxidation system, radially emitting FOFL was achieved with a thin-walled hollow optical fiber (HOF) as an optical microcavity and amplified the concentration change of RhB during oxidation by H2O2. Hb was employed as peroxide-mimicking enzyme to catalyze the oxidation system, which sped up the reaction, resulting in an earlier laser extinction time. With the laser extinction time as sensing signal, the Hb sensor achieved a dynamic range of five orders of magnitude and a limit of detection (LOD) of 46.0 pM at an assay time of 40 min. The developed method provides ideas for the exploitation of FOFL biosensing based on catalytic oxidation reactions.

Spatiotemporal Dynamics of an Intraguild Predation Model with Intraspecies Competition

Different species in the environment compete with one another for shared resources and suitable habitats. As a result, it becomes crucial to identify the essential components involved in preserving biodiversity. This paper describes the emergence of a wide range of temporal and spatiotemporal dynamics of an intraguild predation (IGP) model with intraspecies competition and Holling type-II response function between the IG-prey and IG-predator. To explore the dynamics of the temporal model, we study the local stability of all the biologically feasible steady states, global stability of the interior steady state, and Hopf bifurcation. Performing partial rank correlation coefficient (PRCC) sensitivity analysis, we picked more sensitive parameters and plotted the stability regions in two-parameter spaces. The dynamics exhibited by the system can demonstrate some important hallmarks noticed in the environments, such as the existence and nonexistence of oscillatory behavior in the IGP model. The analytical formulations for the stability and bifurcation of the coexistence of the steady-state are not easy to obtain, but we have verified numerically that the limit cycle bifurcates from the coexistence of the steady-state and there eventually emerges a chaotic behavior through period-doubling bifurcations. By plotting the largest Lyapunov exponent (LLE), we have verified that the temporal system experiences chaotic behavior. It is demonstrated that in the case of a diffusive system, diffusion may cause the coexistence of the steady state, which is otherwise stable, to become unstable. Criteria for the occurrence of Turing instability connected to the IGP model are derived. Our numerical illustrations demonstrate that diffusion-driven instability develops different stationary patterns based on the different initial conditions and diffusion parameters. The spatiotemporal patterns are observed in the Turing, Hopf–Turing, and Hopf regions.

Posterior comparison of model dynamics in several hybrid turbulence model forms

Hybrid turbulence models that can accurately reproduce unsteady three-dimensional flow physics across the entire range of grid scales and turbulence dynamics from Reynolds-averaged Navier–Stokes (RANS), through large-eddy simulation (LES), down to direct numerical simulations (DNS) are of increasing interest to the turbulence modeling community. However, despite decades of research and development, the basic tasks of eliminating poor-performing hybrid RANS-LES models and accelerating adoption of superior models through well-designed validation and verification have yet to occur. As a step in this direction, in this work we evaluate thirteen different hybrid RANS-LES models via systematic grid refinement of decaying homogeneous isotropic turbulence. We further derive a novel mathematical framework for assessing the energy partitioning dynamics of each Hybrid RANS-LES model, wherein model-to-model variations in energy partitioning can be interpreted as different feedback mechanisms operating on a low-dimensional nonlinear dynamical system. We found that model forms similar to the flow simulation methodology—also often termed very-large eddy simulation—are dynamically inconsistent with DNS at all resolutions. Additionally, we found a strong dynamical similarity in the feedback mechanisms of all models related to detached eddy simulation and partially averaged Navier–Stokes that is inherent to their general model forms.

Building Krylov complexity from circuit complexity

Krylov complexity has emerged as a probe of operator growth in a wide range of nonequilibrium quantum dynamics. However, a fundamental issue remains in such studies: the definition of the distance between basis states in Krylov space is ambiguous. Here we show that Krylov complexity can be rigorously established from circuit complexity when dynamical symmetries exist. Whereas circuit complexity characterizes the geodesic distance in a multidimensional operator space, Krylov complexity measures the height of the final operator in a particular direction. The geometric representation of circuit complexity thus unambiguously designates the distance between basis states in Krylov space. This geometric approach also applies to time-dependent Liouvillian superoperators, where a single Krylov complexity is no longer sufficient. Multiple Krylov complexity may be exploited jointly to fully describe operator dynamics. Published by the American Physical Society 2024

Simulating the Universe from the cosmological horizon to halo scales

Ultra-large scales close to the cosmological horizon will be probed by the upcoming observational campaigns. They hold the promise to constrain single-field inflation as well as general relativity, but in order to include them in the forthcoming analyses, their modelling has to be robust. In particular, general relativistic effects may be mistaken for primordial signals, and no consensus has emerged either from analytical modelling nor from the numerical route, obstructed by the large dynamical range to be simulated. In this work, we present a numerical technique to overcome the latter limitation: we compute the general relativistic displacement field with the N-body relativistic code gevolution and combine it with the accurate Newtonian simulation Gadget-4. This combination leads to an effective simulation reproducing the desired behaviour at the level of the matter power spectrum and bispectrum. We then measure, for the first time in a simulation, the relativistic scale-dependent bias in Poisson gauge; at redshift z = 0, we find b 1 GR = -8.1 ± 2.8. Our results at the field level are only valid in the Poisson gauge and need to be complemented with a relativistic ray tracing algorithm to compute the number count observable.

"Seeing" ENF From Neuromorphic Events: Modeling and Robust Estimation.

Most artificial lights exhibit subtle fluctuations in intensity and frequency in response to the influence of the grid's alternating current, providing the potential to estimate the Electric Network Frequency (ENF) from conventional frame-based videos. Nevertheless, the performance of Video-based ENF (V-ENF) estimation largely relies on the imaging quality and thus may suffer from significant interference caused by non-ideal sampling, scene diversity, motion interference, and extreme lighting conditions. In this paper, we show that the ENF can be extracted without the above limitations from a new modality provided by the so-called event camera, a neuromorphic sensor that encodes the light intensity variations and asynchronously emits events with extremely high temporal resolution and high dynamic range. Specifically, we formulate and validate the physical mechanism for the ENF captured in events and then propose a simple yet robust Event-based ENF (E-ENF) estimation method through mode filtering and harmonic enhancement. To validate the effectiveness, we build the first Event-Video ENF Dataset (EV-ENFD) and its extension EV-ENFD+ with diverse scenarios, including static, dynamic, and extreme lighting scenes. Comprehensive experiments have been conducted on our proposed datasets, showcasing that our proposed E-ENF significantly outperforms the V-ENF in extracting accurate ENF traces, especially in challenging environments.

A Novel Accurate Peak Extraction Algorithm of Mass Spectrometry Based on Iterative Adaptive Curve Fitting.

In the analysis of mass spectrometry, the peak identification from the overlapped region is necessary yet difficult. Although various methods have been developed to identify these peaks, especially the continuous wavelet transformation, their applications are still limited and it is hard to deal with the complex overlapped peaks. In this study, a novel peak extraction algorithm of mass spectrometry based on iterative adaptive curve fitting is proposed to address these challenges. It fully utilizes the global optimization characteristics of adaptive curve fitting. Initial peak parameters are obtained using a window searching method, and the residuals between the adaptive fitting peak and the original data indicate the fit's effectiveness and provide information about the peaks in overlap. Using this information, we performed iterative adaptive fitting, continuously updating the overlapped peaks until the residuals met the completion criteria. All of the peaks within the overlapped region can be successfully extracted by the final fitting. The proposed method is evaluated by the simulated data, the real signal from a public data set, and the spectra of two different mass spectrometry instruments. The results demonstrate that this method can more effectively extract peaks with severe overlap and multiple overlapped peaks, resist noise interference, and offer the potential to process peaks with a high dynamic range. More importantly, the proposed method accurately identifies overlapped peaks in the actual spectra from various mass spectrometry instruments, which helps the qualitative and quantitative analyses to a great extent.

Re-configurable digital bandwidth interleaved sampling system based on fast spectrum sensing.

The complexity of systems with parallel acquisition architectures has increased sharply with the continuous growth of signal bandwidth, and sampling precision has been greatly challenged. Considering that the signal to be measured usually exhibits sparsity in the frequency domain, this paper proposes a re-configurable bandwidth interleaved acquisition architecture to maximize test flexibility and accuracy. The sampling process is divided into two stages: sensing and re-configurable acquisition. In the sensing stage, the signal spectrum distribution is roughly understood using a sparse Fourier transform. Based on the spectrum sensing results, the subband selection and the adaptive adjustment of the mixing local oscillator in the acquisition system are performed. Ultimately, these steps enhance sampling accuracy. This paper verifies the effectiveness of this method on a 10GHz acquisition system, demonstrating that it can significantly reduce data redundancy. In addition, it improves acquisition accuracy compared to traditional bandwidth interleaved systems. The experimental results indicate that re-configurable sampling can significantly improve the quality of sampling results. This is evidenced by a signal-to-noise ratio improvement of over 7.4 dB and a spurious-free dynamic range improvement of over 4.7 dB compared to traditional sampling results.

Application of a Novel Disposable Flow Cell for Spectroscopic Bioprocess Monitoring

The evaluation of the analytical capabilities of a novel disposable flow cell for spectroscopic bioprocess monitoring is presented. The flow cell is presterilized and can be connected to any kind of bioreactor by weldable tube connections. It is clamped into a reusable holder, which is equipped with SMA-terminated optical fibers or an integrated light source and detection unit. This modular construction enables spectroscopic techniques like UV-Vis spectroscopy or turbidity measurements by scattered light for modern disposable bioreactors. A NIR scattering module was used for biomass monitoring in different cultivations. A high-cell-density fed-batch cultivation with Komagataella phaffii and a continuous perfusion cultivation with a CHO DG44 cell line were conducted. A high correlation between the sensor signal and biomass or viable cell count was observed. Furthermore, the sensor shows high sensitivity during low turbidity states, as well as a high dynamic range to monitor high turbidity values without saturation effects. In addition to upstream processing, the sensor system was used to monitor the purification process of a monoclonal antibody. The absorption module enables simple and cost-efficient monitoring of downstream processing and quality control measurements. Recorded absorption spectra can be used for antibody aggregate detection, due to an increase in overall optical density.