Scattering Technique Research Articles

Effect of AML-exosomes on the cellular and molecular properties of bone marrow mesenchymal stromal cells: Expression of JAK/STAT signaling genes

Purpose of studyDespite the various therapeutic options introduced for AML treatment, therapy resistance and relapse are still the main obstacles. It is well known that alterations in the bone marrow microenvironment (BMM) play a crucial role in leukemia growth and the treatment failure of AML. Evidence shows that exosomes alter the components of BMM in a way that support leukemia survival, leading to chemoresistance. In this study, we evaluated the effect of AML exosomes on the biological functions of human bone marrow mesenchymal stromal cells (h BM-MSCs), especially alteration in the expression of the JAK/STAT signaling genes, as a leukemia-favoring pathway. MethodExosomes were isolated from the HL-60 cell line and characterized using flow cytometry, Transmission Electron Microscopy (TEM), and Dynamic Light Scattering (DLS) technique. The exosome protein content was assessed using a bicinchoninic acid (BCA) protein assay kit in order to determine the concentration of exosomes. Subsequently, MSCs were treated with varying concentrations of AML exosomes, and data was obtained using MTT, cell cycle, apoptosis, and ki67 assays. Additionally, gene expression analysis was conducted through qRT-PCR. ResultAML exosomes regulated the viability and survival of MSCs in a concentration-dependent manner. The qRT-PCR data revealed that treatment with AML exosomes at a concentration of 50 μg/mL led to a significant upregulation of JAK2, STAT3, and STAT5 genes in MSCs. ConclusionBecause the JAK/STAT signaling pathway has been shown to play a role in the proliferation and survival of leukemic cells, our results suggest that AML exosomes stimulate MSCs to activate this pathway. This activation may impede AML cell apoptosis, potentially leading to chemoresistance and relapse.

A novel green synthesis of silver nanoparticles from Anisosciadium seeds extract as sensitive fluorescent nanosensors for determination of esomeprazole and lansoprazole in dosage forms and human plasma

This study introduces a novel and eco-friendly method for the spectrofluorimetric determination of two important anti-GERD drugs, esomeprazole and lansoprazole. The study depends on synthesis of silver nanoparticles from Anisosciadium seeds extract as a reducing agent, for the first time. The synthesized silver nanoparticles were characterized by applying various microscopic and spectroscopic methods, including Fourier Transform Infrared, High Resolution Transmission Electron Microscopy, Energy-Dispersive X-Ray Analysis, Dynamic Light Scattering technique, Ultraviolet–Visible spectrophotometry, and spectrofluorimetry. The produced silver nanoparticles demonstrated an emission band at 311 nm if excited at 222 nm, and showed powerful blue fluorescence when exposed to UV light. The obtained silver nanoparticles were employed as fluorescent nanoprobes for the determination of esomeprazole and lansoprazole spectrofluorimetrically, depending on their quenching of the native fluorescence of silver nanoparticles quantitatively. This study is the first spectrofluorimetric strategy for the determination of the investigated medications with the use of silver nanoparticles without the requirement for any pre-derivatization stages or large volumes of organic solvents. As investigated medications don’t display native fluorescent characteristics; the importance of the presented method increases. The suggested study demonstrated excellent linearity over the ranges of 1.0–10.0 μg/mL and 0.1–1.0 μg/mL with detection limits of 0.17 μg/mL and 0.015 μg/mL for esomeprazole and lansoprazole, respectively. The presented study was employed for the determination of esomeprazole and lansoprazole in human plasma samples and dosage forms with low % relative standard deviation and high % recoveries values. Greenness profile of the suggested method was assessed utilizing two various metrics, including Green Analytical Procedure Index (GAPI) and Analytical GREENNESS metric approach (AGREE), verifying lower environmental impact of the method and excellent eco-friendliness. The proposed strategy was validated in accordance with International Council for Harmonization(ICH) Q2 (R2) guidelines.

Particle Matter determination in Biosimilar Parenteral Product by the Application of Dynamic Light Scattering (DLS) Followed by Statistical Evaluation

Particulate matter in parenteral dosage forms can emerge from numerous causes, external, intrinsic, as well as inherent within the product, with a special emphasis on biopharmaceuticals. Aqueous impurities, pharmaceutical precipitates, dirt, glass, rubber, pollutants from the environment, fibres, and various other insoluble materials are all common sources of particulates. When assessing the possible harm to patients, particulate matter size is a crucial issue to consider. Particles as fine as 2 μm overall diameter were found related with microthrombi development. The DLS (Dynamic Light Scattering) technique has been used to measure and control the subvisible particulate particles in biopharmaceutical parenteral drug products since the technique can measure the submicron particle size in the parenteral formulation. The purpose of using DLS is to measure and control the subvisible particles in a biopharmaceutical formulation. A generic biopharmaceutical product viz. Calcitonin Salmon injection was used for particulate matter analysis by using Dynamic Light Scattering. DLS is a non-invasive method for detecting the size of suspended particles as well as molecules which is used for the control and optimization of processes, and the improvement of product quality and performance by analysing the time-dependence in regard to intensity of the dispersed light (auto correlation) to determine the diffusion speed (Brownian motion) of particles/molecules, and subsequently determine the hydrodynamic size. Keywords: Particulate matter; DLS; Biosimilars; Parenteral dosage forms

2D3C Measurement Of Velocity, Pressure And Temperature Fields In A Intake Flow Of An Air Turbine By Filtered Rayleigh Sattering (FRS) And Validation With LDV And PIV

A Filtered Rayleigh Scattering Technique is implemented in two different experimental setups and compared to the established velocity measurement techniques Laser Doppler Anemometry (LDA) and Particle Image Velocimetry (PIV). The Frequency Scanning Filtered Rayleigh Scattering Method employed uses an imagefiber bundle which allows for the simultaneous observation of the flow situation from six independent perspectives, utilizing only one sCMOS camera. A testrig with a nominal diameter of 80 mm was implemented by ILA R&D GmbH. Here measurements with straight pipe flow and a swirl generator were realised, as well as comparisions with LDA. A second experiment utilized Cranfields University’s Complex Intake Facility (CCITF), enabling the simulation of the flow field for an engine intake as observed behind an S-Duct diffuser. The diameter in the measuring plane was 160 mm. Measurements up to a mach number of 0.4 were performed and compared with HighSpeed Stereo-PIV (S-PIV) measurements. Good agreement was achieved in respect to both the absolute magnitude of the velocity measurements as well as to the resolution of complex flow structures. The developed FRS multi-view Setup is able to simultaneously determine the 3D velocity components, the pressure and the temperature on a measurement plane with high resolution and without seeding. After calibration the FRS system yields the pressure and temperature within 3 percent respectively 0.8 percent of the reference values. The measured velocity was within 1-2 m/s of the reference.

Study of the Structure of Zn and Na Borophosphate Glasses Using X-ray and Neutron Scattering Techniques

The atomic structures of Zn and Na borophosphate glasses were studied using X-ray and neutron scattering techniques. Peaks assigned to the B−O, P−O, and O−O distances confirm that only BO4 units co-exist with the PO4 tetrahedra. The Zn−O and Na−O coordination numbers are found to be a little larger than four. The narrowest peaks of the Zn−O first-neighbor distances exist for the glasses along a line connecting the Zn(PO3)2 and BPO4 compositions (50 mol% P2O5), which is explained by networks of ZnO4, BO4, and PO4 tetrahedra with twofold coordinated oxygens. The calculated amounts of available oxygen support this interpretation. Broadened peaks occur for glasses with lower P2O5 contents, which is consistent with the presence of threefold coordinated oxygens. The two distinct P−O peak components of the Zn and Na borophosphate glasses differ in their relative abundances. This is interpreted as follows: Na+ cations coordinate oxygens in some P−O−B bridges, which is something not seen for the Zn2+ ions.

USP’s characterization of commercial poly(lactic-co-glycolic acid) utilizing SEC-Multi-Angle Light Scattering and Refractive Index techniques via Absolute Method approach

This research focuses on evaluating the data quality and reliability of Size Exclusion Chromatography with Multi-Angle Light Scattering and Refractive Index (SEC-MALS/RI) chromatography in determining molecular weight-related parameters in poly(lactic-co-glycolic) acid (PLGA) polymers. The study utilizes key metrics, particularly percent relative standard deviation (%RSD), to evaluate the precision across different data processing conditions. Exploring baseline selection of the chromatograms reveals that selection of the baseline based on the intrinsic shape of the chromatogram, rather than relying on elution peaks, improves consistency. The study emphasizes the critical role of result fitting in addressing systematic errors and sample heterogeneity, recommending the minima of the elution peak selection range for realistic molecular weight distribution representation. Analysis of light-scattering (LS) detector chromatograms highlights varying effects on different PLGA polymers, emphasizing the need for careful assessment and potential exclusion for precision improvement, especially in the presence of experimental artifacts. Across diverse PLGA polymers, the utilization of different column types, along with considerations such as baseline determination and peak selection, shows minimal variations in Mn, Mw, and polydispersity index (PDI), affirming the consistency of the methodology. The %RSD analysis further supports the methodology's precision, with values well within acceptable limits. In summary, this comprehensive evaluation of methodological conditions, including baseline selection, result fitting, LS detector data management, and column types, establishes a reliable SEC-MALS/RI chromatographic approach by Absolute Method for determining molecular weight parameters in PLGA polymers.

Integrating machine learning with -SAS for enhanced structural analysis in small-angle scattering: applications in biological and artificial macromolecular complexes.

Small-Angle Scattering (SAS), encompassing both X-ray (SAXS) and Neutron (SANS) techniques, is a crucial tool for structural analysis at the nanoscale, particularly in the realm of biological macromolecules. This paper explores the intricacies of SAS, emphasizing its application in studying complex biological systems and the challenges associated with sample preparation and data analysis. We highlight the use of neutron-scattering properties of hydrogen isotopes and isotopic labeling in SANS for probing structures within multi-subunit complexes, employing techniques like contrast variation (CV) for detailed structural analysis. However, traditional SAS analysis methods, such as Guinier and Kratky plots, are limited by their partial use of available data and inability to operate without substantial a priori knowledge of the sample's chemical composition. To overcome these limitations, we introduce a novel approach integrating -SAS, a computational method for simulating SANS with CV, with machine learning (ML). This approach enables the accurate prediction of scattering contrast in multicomponent macromolecular complexes, reducing the need for extensive sample preparation and computational resources. -SAS, utilizing Monte Carlo methods, generates comprehensive datasets from which structural invariants can be extracted, enhancing our understanding of the macromolecular form factor in dilute systems. The paper demonstrates the effectiveness of this integrated approach through its application to two case studies: Janus particles, an artificial structure with a known SAS intensity and contrast, and a biological system involving RNA polymerase II in complex with Rtt103. These examples illustrate the method's capability to provide detailed structural insights, showcasing its potential as a powerful tool for advanced SAS analysis in structural biology.

Non-specific/specific SERS spectra concatenation for precise bacteria classifications with few samples using a residual neural network

Deep learning neural network incorporating surface enhancement Raman Scattering technique (SERS) is becoming as a powerful tool for the precise classifications and diagnosis of bacterial infections. However, the large amount of sample requirement and time-consuming sample collection severely hinder its applications. We herein propose a spectral concatenation strategy for residual neural network using non-specific and specific SERS spectra for the training data augmentation, which is accessible to acquiring larger training dataset with same number of SERS spectra or same size of training dataset with fewer SERS spectra, compared with pure non-specific SERS spectra. With this strategy, the training loss exhibit rapid convergence, and an average accuracy up to 100% in bacteria classifications was achieved with 50 SERS spectra for each kind of bacterium; even reduced to 20 SERS spectra per kind of bacterium, classification accuracy is still > 95%, demonstrating marked advantage over the results without spectra concatenation. This method can markedly improve the classification accuracy under fewer samples and reduce the data collection workload, and can evidently enhance the performance when used in different machine learning models with high generalization ability. Therefore, this strategy is beneficial for rapid and accurate bacteria classifications with residual neural network.

Synchrotron radiation SAXS study of the species structure evolution in the synthesis process of MCM-56 zeolite

In the process of synthesizing zeolite, the evolution behavior of aluminosilicate species is crucial for investigating the crystallization mechanism and controlling the structure of desired zeolite. Herein, the synthesis process of MCM-56 zeolite was investigated by using the synchrotron radiation Small Angle X-ray Scattering (SAXS) technique. Based on the distance distribution function curves and Porod analysis, the particle distribution of the sol in the synthesis system transformed from a monodisperse spherical particle to a polydisperse lamellar structure. The results indicated that the particle size distribution, fractal dimension, and the evolution behavior of particles in sol vary with the variation of crystallization time. Specifically, the initial step involves the depolymerization of particles forming small particles approximately 1 nm. Subsequently, these small particles polymerize to form structural units ranging in size from 1 to 5 nm, and finally grow to form MCM-56 zeolite crystal by consuming aluminosilicate species. The SAXS results in conjunction with the XRD, SEM, FT-IR, and N2 adsorption-desorption analysis elucidate the evolution of aluminosilicate species and the crystallization process of MCM-56 zeolite at three stages, including the induction/nucleation period (0–84 h), the crystal growth period (84–108 h) and the crystal stability period (108–168 h). By virtue of the understanding for the structural evolution of the sol species, this work is expected to highlight the controllable synthesis of MCM-56 zeolite.

Large-scale PANDA facility – radiation experiments and CFD calculations

Abstract CFD modelling of the thermo-hydraulic phenomena in the containment during the various phases of a severe accident necessarily requires consideration of radiative heat transfer – in the presence of steam. These radiative phenomena include (i) energy transfer within the gas mixture and (ii) between the gas and surrounding structures. Preliminary calculations carried out for these types of experiments within the OECD/NEA HYMERES-2 project with the CFD code containmentFOAM using a Monte Carlo solver for thermal radiation, demonstrated that the radiative heat transfer is significant even for very small amounts of vapour in the range of ≈0.1 % to ≈2 %. For this reason, the test matrix was tailored to the two opposite extremes: either gas compositions with a low vapour/steam content, where radiative heat transfer can be neglected, or gas mixtures with higher vapour contents, so that radiative heat transfer plays a dominant role. For the selected experiments of the H2P2 series and the corresponding CFD calculations, a vessel with a diameter of 4 m and a height of 8 m was preconditioned with different air-vapour mixtures (a) at room temperature and (b) elevated temperatures. A stable helium layer was then built-up in the upper part of the vessel. The gas was then compressed by injecting helium from above which resembles with best efforts a compression with a piston in a cylinder. This results in a height-dependent and transient increase of the gas temperature. These experiments and the associated CFD calculations were developed to isolate the phenomena of thermal radiation as good as possible from convective and diffusive effects – within the always present experimental limitations. For the reference experiment with ‘dry conditions’ corresponding to the lowest experimentally possible humidity of ≈0.1 %, we show that the use of a model without radiation provides the best agreement between the experimental and numerical results. For the much higher steam content of ≈60 %, the statistical narrow band correlated-k model (SNBCK), non-gray gas model, is the best candidate for future calculations – with computationally forgivable additional effort. We also provide with the Filtered Rayleigh Scattering technique (FRS) an outlook for a possible future instrumentation approach to better meet the requirements of the CFD community.

Evaluation and Comparison of Fullerene (C60) Aqueous Suspension Administration Effects with Memantine HCL in Rat Model of Alzheimer’s Disease Considering Behavioral Patterns and Spatial Memory

: Alzheimer's disease (AD) is among the most prevalent neurodegenerative disorders leading to dementia in the elderly. The accumulation of amyloid-beta (Aβ) plaques and the formation of tau protein tangles are primary contributors to AD, which induce oxidative stress. Fullerene C60, a nanoscale carbon allotrope with a diameter of 0.7 nanometers, stands out due to its structure rich in double bonds, making these nanoparticles effective radical scavengers. This property nominates them for potential use in treating neurodegenerative diseases like AD. In this study, unmodified pristine fullerene (C60), a highly hydrophobic molecule, was dispersed in water and administered intraperitoneally (1 mL, BID) to rats after inducing an AD-like condition with scopolamine hydrobromide (2mg/kg, i.p.). The aim was to assess the impact of fullerene (C60) treatment on cognitive behavior and spatial memory in rats, compared to the standard treatment with memantine HCL, using the Morris water maze method. The fullerene aqueous suspension (FAS) was prepared using a solvent exchange method involving a toluene/water mixture and ultrasonication. The concentration of fullerene particles in water was determined by high-performance liquid chromatography (HPLC) to be 21 µg/mL. The Dynamic Light Scattering (DLS) technique measured the average size and zeta potential of the nanoparticles as 119.14 ± 3.38 nm and -12.22 ± 5.98 mV, respectively. Treatment with FAS significantly improved memory impairment in rats compared to memantine HCL (10 mg/kg, i.p.) treatment. All rats survived until the end of the study, indicating no acute toxicity from FAS administration. These results may offer new insights into combating AD by introducing fullerene C60 as a promising nanoparticle with beneficial effects on behavioral patterns.

Dimensions of Cellulose Nanocrystals from Cotton and Bacterial Cellulose: Comparison of Microscopy and Scattering Techniques.

Different microscopy and scattering methods used in the literature to determine the dimensions of cellulose nanocrystals derived from cotton and bacterial cellulose were compared to investigate potential bias and discrepancies. Atomic force microscopy (AFM), small-angle X-ray scattering (SAXS), depolarized dynamic light scattering (DDLS), and static light scattering (SLS) were compared. The lengths, widths, and heights of the particles and their respective distributions were determined by AFM. In agreement with previous work, the CNCs were found to have a ribbon-like shape, regardless of the source of cellulose or the surface functional groups. Tip broadening and agglomeration of the particles during deposition cause AFM-derived lateral dimensions to be systematically larger those obtained from SAXS measurements. The radius of gyration determined by SLS showed a good correlation with the dimensions obtained by AFM. The hydrodynamic lateral dimensions determined by DDLS were found to have the same magnitude as either the width or height obtained from the other techniques; however, the precision of DDLS was limited due to the mismatch between the cylindrical model and the actual shape of the CNCs, and to constraints in the fitting procedure. Therefore, the combination of AFM and SAXS, or microscopy and small-angle scattering, is recommended for the most accurate determination of CNC dimensions.

Visualization of the Gas Spatial Distribution of the Odor Source by SERS Gas Sensor

Surface‐Enhanced Raman Scattering (SERS) technique is used to fabricate the gas sensor, which is developed for the visualization of the spatial distribution of gas evaporating from odor source. The 3 × 3 SERS sensor array is put on the odor source and then scanned by the home‐made detection system to obtain the Raman spectra of the odor. The intensities of the characteristic peaks from the collected spectra are used to draw a heatmap graph. After the heatmap graph is processed by the noise reduction, the localization of the odor source can be clearly identified through the resulting graph. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Time-Domain Coherent Raman Scattering Techniques (Invited)

Time-Domain Coherent Raman Scattering Techniques (Invited)

Introducing a Novel Light Scattering Technique for Visualising Operando State-of-Charge Changes Within Individual Active Particles and Across the Electrode

In our presentation we will demonstrate the application of a recently developed operando optical microscopy technique to mechanistic studies of lithium-ion battery electrodes and active material characterisation. Our technique probes state-of-charge (SoC) changes in the active particles within the electrode during battery operation, based on the intensity variation of scattered light across each active particle. This enables detailed spatially resolved data on an individual particle level to be utilised for furthering mechanistic understanding of battery capability and degradation, and it also allows global statistics to be established for the optimisation and screening of new electrode materials. The technique is agnostic to the underlying battery chemistry, so in principle can be applied to study any battery electrode.In this talk, we will demonstrate how our technique can be used in the study of two key dynamic processes, solid-state ion transport and mechanical degradation. The ability to quantify ion transport during battery operation helps to provide insights into how lithium-ion dynamics affect the (de)lithiation mechanisms and degradation mechanisms of battery electrodes, which is crucial to improving their electrochemical performance. Using lithium cobalt oxide (LCO) as a case study, we will show how ion-transport mechanisms can be deduced by observing moving phase boundaries within particles during cycling.We will then demonstrate how local SoC changes within Ni-rich nickel manganese cobalt oxide (NMC) active particles can be visualised during operation, and how the intra-particle ion gradients identified can be used to determine the mechanistic origins of first-cycle capacity losses. Building on this, we will highlight how variation in the rates of (dis)charge between a population of active particles could be used to characterise the performance of new electrode compositions.In addition, we will highlight how lithium-ion concentration gradients can also be identified in high-rate niobium tungsten oxide (NWO) anode materials during initial lithiation and under initial rapid delithiation conditions and demonstrate how this can lead to particle cracking. Expanding on this, we illustrate how the proportion of cracked particles within an electrode can be quantified and then monitored over successive cycles as a potential metric for screening the stability of new electrode materials.

Conquering Metal–Organic Frameworks by Raman Scattering Techniques

AbstractMetal–organic frameworks (MOFs) have emerged as a versatile class of materials. Understanding the structural and chemical properties of MOFs is essential for tailoring their performance to suit specific applications. In recent years, Raman spectroscopy, a non‐destructive vibrational spectroscopic technique, has evolved into a powerful tool for characterizing MOFs. Beyond spontaneous Raman scattering, numerous advanced Raman techniques have been developed to amplify the inherently weak Raman signal. These innovations have significantly enhanced the spatial resolution, frame rate, and sensitivity of Raman imaging, thereby opening up new possibilities for applications, such as label‐free sensing. This tutorial work is designed to demystify the fundamental theory and instrumentation of Raman spectroscopy, elucidating the differences between commonly used Raman techniques. Particular emphasis is placed on their advantages and limitations when applied to MOF materials. Furthermore, this work showcases how Raman techniques are employed in studying MOF systems to address societal needs and explore future directions. Ultimately, this review emphasizes the crucial role of Raman spectroscopy and the development of novel Raman‐based in situ techniques to conquer the field of MOFs.

Device-Free Localization Techniques: A Review

Device-free localization (DFL) has emerged as a transformative technology for tracking objects and individuals without requiring them to carry electronic devices. This paper reviews two pivotal techniques of DFL: Link Quality Measurement and Link Scattering techniques. Link Quality Measurement focuses on evaluating the quality of wireless links through metrics like Received-Signal-Strength and Channel-State-Information, offering simplicity and reliability. Meanwhile, Link Scattering harnesses signal reflections and diffractions caused by environmental obstacles to estimate device-free target positions. This review provides insights of Link Quality Measurement, Link Scattering methods and highlighting DFL metrics. By shedding light on these critical aspects, it offers valuable insights into the current state of DFL technology and its potential in diverse domains, ranging from smart environments to security systems.

Dispersion stability analysis of copper sulphide nanoparticles in different medium

Nanoparticles (NPs) of covellite CuS have been synthesised using a modified polyol method at 160ºC - 165ºC without adding any extra surfactant. These NPs were charecterized by X-ray diffraction (XRD), Raman spectroscopy, Field Emission Scanning Electron Microscope (FESEM), Energy Dispersive Analysis of X-ray (EDAX), Zeta potential and Dynamic Light Scattering (DLS) techniques. XRD data and three Raman modes confirm P63/mmc space group and hexagonal crystal structure of CuS NPs. EDAX data of Cu:S was slight differed from nominal 1:1 ratio due to extra S taken in synthesis. FESEM images show sheet-like NPs. The zeta potential (ξ) data analysis shows that the stability of the NPs is dependent on the dispersion medium, with high stability observed above pH 8.93 in an acidic medium. At pH 10.95, a highest ξ value of -37.64 mV is recorded in de-ionized water (DIW), while the nanoparticles are found to be unstable in ethanol and propanol as dispersion mediums. According to the hydrodynamic diameter (HD) data, the particles tend to agglomerate more quickly in ethanol and propanol compared to DIW. These findings are expected to be useful in various applications such as pigments in paints, batteries, pharmaceuticals, ceramics, and waste water treatment.

Salmonella YqiC exerts its function through an oligomeric state.

Protein oligomerization occurs frequently both in vitro and in vivo, with specific functionalities associated with different oligomeric states. The YqiC protein from Salmonella Typhimurium forms a homotrimer through its C-terminal coiled-coil domain, and the protein is closely linked to the colonization and invasion of the bacteria to the host cells. To elucidate the importance of the oligomeric state of YqiC in vivo and its relation with bacterial infection, we mutated crucial residues in YqiC's coiled-coil region and confirmed the loss of trimer formation using chemical crosslinking and size exclusion chromatography coupled with multiple angle light scattering (SEC-MALS) techniques. The yqiC-knockout strain complemented with mutant YqiC showed significantly reduced colonization and invasion of Salmonella to host cells, demonstrating the critical role of YqiC oligomerization in bacterial pathogenesis. Furthermore, we conducted a protein-protein interaction study of YqiC using a pulled-down assay coupled with mass spectrometry analysis to investigate the protein's role in bacterial virulence. The results reveal that YqiC interacts with subunits of Complex II of the electron transport chain (SdhA and SdhB) and the β-subunit of F0 F1 -ATP synthase. These interactions suggest that YqiC may modulate the energy production of Salmonella and subsequently affect the assembly of crucial virulence factors, such as flagella. Overall, our findings provide new insights into the molecular mechanisms of YqiC's role in S. Typhimurium pathogenesis and suggest potential therapeutic targets for bacterial infections.

Variance analysis of dynamic light scattering data.

We propose a novel method alternative to the classical Dynamic Light Scattering (DLS) technique for performing particle sizing on diluted dispersions of nanosized particles. Differently from DLS, which works by determining the correlation function of the intensity scattered by the sample, our method does not require the use of a correlator because it exploits the behavior of the variance (VAR) of the scattered signal as a function of the sampling time Δt. By using a wide range of sampling times Δtmin ≪ τc ≪ Δtmax, it is possible to recover the correlation time τc of the scattered field and, in turn (by using the Stokes-Einstein relation), the hydrodynamic diameter of the particles. The new method is endowed with an analytical expression for the error bars associated with to the VAR data. Extensive computer simulations carried out on monodisperse and narrow polydisperse samples show that VAR and DLS techniques provide fairly similar performances. The same results were obtained on calibrated polystyrene spheres and fluorescent perovskite nanoparticles tested with different setups and detection schemes.