Exceptions to Fourier's Law at the Macroscale.

The usual basis to analyze heat transfer within materials is the equation formulated 200 years ago, Fourier's law, which is identical mathematically to the mass diffusion equation, Fick's law. Revisiting this assumption regarding heat transport within translucent materials, performing the experiments in vacuum to avoid air convection, we compare the model predictions to infrared-based measurements with nearly mK temperature resolution. After heat pulses, we find macroscale non-Gaussian tails in the surface temperature profile. At steady state, we find macroscale anomalous hot spots when the sample is topographically rough, and this is validated by using two additional independent methods to measure surface temperature. These discrepancies from Fourier's law for translucent materials suggest that internal radiation whose mean-free-path is millimeters interacts with defects to produce small heat sources that by secondary emission afford an additional, non-local mode of heat transport. For these polymer and inorganic glass materials, this suggests unique strategies of heat management design.

Mechanical Fourier transform for programmable metamaterials.

Proactively programming materials toward target nonlinear mechanical behaviors is crucial to realize customizable functions for advanced devices and systems, which arouses persistent explorations for rapid and efficient inverse design strategies. Herein, we propose a "mechanical Fourier transform" strategy to program mechanical behaviors of materials by mimicking the concept of Fourier transform. In this strategy, an arbitrary target force-displacement curve is decomposed into multiple cosine curves and a constant curve, each of which is realized by a rationally designed multistable module in an array-structured metamaterial. Various target curves with distinct shapes can be rapidly programmed and reprogrammed through only amplitude modulation on the modules. Two exemplary metamaterials are demonstrated to validate the strategy with a macroscale prototype based on magnet lattice and a microscale prototype based on an etched silicon wafer. This strategy applies to a variety of scales, constituents, and structures, and paves a way for the property programming of materials.

Coupling and regulation mechanisms of the flavin-dependent halogenase PyrH observed by infrared difference spectroscopy.

Flavin-dependent halogenases are central enzymes in the production of halogenated secondary metabolites in various organisms and they constitute highly promising biocatalysts for regioselective halogenation. The mechanism of these monooxygenases includes formation of hypohalous acid from a reaction of fully reduced flavin with oxygen and halide. The hypohalous acid then diffuses via a tunnel to the substrate-binding site for halogenation of tryptophan and other substrates. Oxidized flavin needs to be reduced for regeneration of the enzyme, which can be performed in vitro by a photoreduction with blue light. Here, we employed this photoreduction to study characteristic structural changes associated with the transition from oxidized to fully reduced flavin in PyrH from Streptomyces rugosporus as a model for tryptophan-5-halogenases. The effect of the presence of bromide and chloride or the absence of any halides on the UV-vis spectrum of the enzyme demonstrated a halide-dependent structure of the flavin-binding pocket. Light-induced FTIR difference spectroscopy was applied and the signals assigned by selective isotope labeling of the protein moiety. The identified structural changes in α-helix and ß-sheet elements were strongly dependent on the presence of bromide, chloride, the substrate tryptophan, and the product 5-chloro-tryptophan, respectively. We identified a clear allosteric coupling in solution at ambient conditions between cofactor-binding site and substrate-binding site that is active in both directions, despite their separation by a tunnel. We suggest that this coupling constitutes a fine-tuned mechanism for the promotion of the enzymatic reaction of flavin-dependent halogenases in dependence of halide and substrate availability.

Nanoscale Infrared Spectroscopic Characterization of Extended Defects in 4H-Silicon Carbide.

Extended defects in wide-bandgap semiconductors have been widely investigated using techniques providing either spectroscopic or microscopic information. Nano-Fourier transform infrared spectroscopy (nano-FTIR) is a nondestructive characterization method combining FTIR with nanoscale spatial resolution (∼20 nm) and topographic information. Here, we demonstrate the capability of nano-FTIR for the characterization of extended defects in semiconductors by investigating an in-grown stacking fault (IGSF) present in a 4H-SiC epitaxial layer. We observe a local spectral shift of the mid-infrared near-field response, consistent with the identification of the defect stacking order as 3C-SiC (cubic) from comparative simulations based on the finite dipole model (FDM). This 3C-SiC IGSF contrasts with the more typical 8H-SiC IGSFs reported previously and is exemplary in showing that nanoscale spectroscopy with nano-FTIR can provide new insights into the properties of extended defects, the understanding of which is crucial for mitigating deleterious effects of such defects in alternative semiconductor materials and devices.

Evolution of Plumage Patterns in a Pattern Morphospace: A Phylogenetic Analysis of Melanerpine Woodpeckers.

AbstractPlumage patterns of melanerpine (Melanerpes-Sphyrapicus) woodpeckers are strikingly diverse. Understanding the evolution and function of this diversity is challenging because of the difficulty of quantifying plumage patterns. We use a three-dimensional space to characterize the evolution of melanerpine achromatic plumage patterns. The axes of the space are three pattern features (spatial frequency, orientation, and contrast) quantified using two-dimensional fast Fourier transformation of museum specimen images. Mapping plumage in pattern space reveals differences in how species and subclades occupy the space. To quantify these differences, we derive two new measures of pattern: pattern diversity (diversity across plumage patches within a species) and pattern uniqueness (divergence of patterns from those of other species). We estimate that the melanerpine ancestor had mottled plumage and find that pattern traits across patches and subclades evolve at different rates. We also find that smaller species are more likely to display horizontal face patterning. We promote pattern spaces as powerful tools for investigating animal pattern evolution.

Connectome spectrum electromagnetic tomography: A method to reconstruct electrical brain source networks at high-spatial resolution.

Connectome spectrum electromagnetic tomography (CSET) combines diffusion MRI-derived structural connectivity data with well-established graph signal processing tools to solve the M/EEG inverse problem. Using simulated EEG signals from fMRI responses, and two EEG datasets on visual-evoked potentials, we provide evidence supporting that (i) CSET captures realistic neurophysiological patterns with better accuracy than state-of-the-art methods, (ii) CSET can reconstruct brain responses more accurately and with more robustness to intrinsic noise in the EEG signal. These results demonstrate that CSET offers high spatio-temporal accuracy, enabling neuroscientists to extend their research beyond the current limitations of low sampling frequency in functional MRI and the poor spatial resolution of M/EEG.

Enhanced extracellular vesicles mediated uttroside B (Utt-B) delivery to Hepatocellular carcinoma cell: Pharmacokinetics based on PBPK modelling.

Our prior investigation has confirmed that the anti-hepatocellular carcinoma activity of the plant saponin, specifically Uttroside B (Utt-B), derived from the leaves of Solanum nigrum Linn. This study concentrated on formulating a novel biocompatible nanocarrier utilizing Extracellular vesicles (EVs) to enhance the delivery of plant saponin into cells. The physicochemical attributes of Extracellular Vesicles/UttrosideB (EVs/Utt-B) were comprehensively characterized through techniques such as Transmission Electron Microscopy (TEM) and Fourier-transform infrared spectroscopy (FTIR). Despite the promising therapeutic potential of this uttroside B, mechanistic know-how about its entry into cells is still in its infancy. Our research sheds light on the extracellular vesicle-mediated mechanism facilitating the entry of the saponin into cells, a phenomenon confirmed through the use of by confocal microscopy. We further analysed drug-releasing kinetics and simulated the Pharmacokinetics by PBPK modelling. The simulated pharmacokinetics revealed the bioavailability of Uttroside-B in oral administration against intravenous administration.

Attenuated total reflection Fourier-transform infrared spectroscopy reveals environment specific phenotypes in clonal Japanese knotweed.

BACKGROUND: Japanese knotweed (Reynoutria japonica var. japonica), a problematic invasive species, has a wide geographical distribution. We have previously shown the potential for attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy and chemometrics to segregate regional differentiation between Japanese knotweed plants. However, the contribution of environment to spectral differences remains unclear. Herein, the response of Japanese knotweed to varied environmental habitats has been studied. Eight unique growth environments were created by manipulation of the red: far-red light ratio (R: FR), water availability, nitrogen, and micronutrients. Their impacts on plant growth, photosynthetic parameters, and ATR-FTIR spectral profiles, were explored using chemometric techniques, including principal component analysis (PCA), linear discriminant analysis, support vector machines (SVM) and partial least squares regression. Key wavenumbers responsible for spectral differences were identified with PCA loadings, and molecular biomarkers were assigned. Partial least squared regression (PLSR) of spectral absorbance and root water potential (RWP) data was used to create a predictive model for RWP. RESULTS: Spectra from plants grown in different environments were differentiated using ATR-FTIR spectroscopy coupled with SVM. Biomarkers highlighted through PCA loadings corresponded to several molecules, most commonly cell wall carbohydrates, suggesting that these wavenumbers could be consistent indicators of plant stress across species. R: FR most affected the ATR-FTIR spectra of intact dried leaf material. PLSR prediction of root water potential achieved an R2 of 0.8, supporting the potential use of ATR-FTIR spectrometers as sensors for prediction of plant physiological parameters. CONCLUSIONS: Japanese knotweed exhibits environmentally induced phenotypes, indicated by measurable differences in their ATR-FTIR spectra. This high environmental plasticity reflected by key biomolecular changes may contribute to its success as an invasive species. Light quality (R: FR) appears critical in defining the growth and spectral response to environment. Cross-species conservation of biomarkers suggest that they could function as indicators of plant-environment interactions including abiotic stress responses and plant health.

Accelerating wavepacket propagation with machine learning.

In this work, we discuss the use of a recently introduced machine learning (ML) technique known as Fourier neural operators (FNO) as an efficient alternative to the traditional solution of the time-dependent Schrödinger equation (TDSE). FNOs are ML models which are employed in the approximated solution of partial differential equations. For a wavepacket propagating in an anharmonic potential and for a tunneling system, we show that the FNO approach can accurately and faithfully model wavepacket propagation via the density. Additionally, we demonstrate that FNOs can be a suitable replacement for traditional TDSE solvers in cases where the results of the quantum dynamical simulation are required repeatedly such as in the case of parameter optimization problems (e.g., control). The speed-up from the FNO method allows for its combination with the Markov-chain Monte Carlo approach in applications that involve solving inverse problems such as optimal and coherent laser control of the outcome of dynamical processes.

Investigating proton tunneling dynamics in the time-dependent Schrödinger equation.

Understanding the temporal evolution of the wave function in the proton tunneling reactions allows us to make theoretical predictions on the possible femtosecond spectroscopy patterns. However, the analytical solution of the time-dependent Schrödinger equation of complex molecules is challenging and requires a high computational cost. In this study, we solve the time-dependent Schrödinger equation using the Fourier grid Hamiltonian method, highlighting its simplicity of calculation, even for multidimensional tunneling reactions. The obtained model is applied to studying malonaldehyde's two-dimensional intramolecular proton tunneling, comparing the results with those obtained using other computational methods.

Sleep alterations as a function of 88 health indicators.

BACKGROUND: Alterations in sleep have been described in multiple health conditions and as a function of several medication effects. However, evidence generally stems from small univariate studies. Here, we apply a large-sample, data-driven approach to investigate patterns between in sleep macrostructure, quantitative sleep EEG, and health. METHODS: We use data from the MrOS Sleep Study, containing polysomnography and health data from a large sample (N = 3086) of elderly American men to establish associations between sleep macrostructure, the spectral composition of the electroencephalogram, 38 medical disorders, 2 health behaviors, and the use of 48 medications. RESULTS: Of sleep macrostructure variables, increased REM latency and reduced REM duration were the most common findings across health indicators, along with increased sleep latency and reduced sleep efficiency. We found that the majority of health indicators were not associated with objective EEG power spectral density (PSD) alterations. Associations with the rest were highly stereotypical, with two principal components accounting for 85-95% of the PSD-health association. PC1 consists of a decrease of slow and an increase of fast PSD components, mainly in NREM. This pattern was most strongly associated with depression/SSRI medication use and age-related disorders. PC2 consists of changes in mid-frequency activity. Increased mid-frequency activity was associated with benzodiazepine use, while decreases were associated with cardiovascular problems and associated medications, in line with a recently proposed hypothesis of immune-mediated circadian demodulation in these disorders. Specific increases in sleep spindle frequency activity were associated with taking benzodiazepines and zolpidem. Sensitivity analyses supported the presence of both disorder and medication effects. CONCLUSIONS: Sleep alterations are present in various health conditions.

Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing.

The reliability of Fourier-transform infrared (FT-IR) spectroscopy for Klebsiella pneumoniae typing and outbreak control has been previously assessed, but issues remain in standardization and reproducibility. We developed and validated a reproducible FT-IR with attenuated total reflectance (ATR) workflow for the identification of K. pneumoniae lineages. We used 293 isolates representing multidrug-resistant K. pneumoniae lineages causing outbreaks worldwide (2002-2021) to train a random forest classification (RF) model based on capsular (KL)-type discrimination. This model was validated with 280 contemporaneous isolates (2021-2022), using wzi sequencing and whole-genome sequencing as references. Repeatability and reproducibility were tested in different culture media and instruments throughout time. Our RF model allowed the classification of 33 capsular (KL)-types and up to 36 clinically relevant K. pneumoniae lineages based on the discrimination of specific KL- and O-type combinations. We obtained high rates of accuracy (89%), sensitivity (88%), and specificity (92%), including from cultures obtained directly from the clinical sample, allowing to obtain typing information the same day bacteria are identified. The workflow was reproducible in different instruments throughout time (>98% correct predictions). Direct colony application, spectral acquisition, and automated KL prediction through Clover MS Data analysis software allow a short time-to-result (5 min/isolate). We demonstrated that FT-IR ATR spectroscopy provides meaningful, reproducible, and accurate information at a very early stage (as soon as bacterial identification) to support infection control and public health surveillance. The high robustness together with automated and flexible workflows for data analysis provide opportunities to consolidate real-time applications at a global level. IMPORTANCE We created and validated an automated and simple workflow for the identification of clinically relevant Klebsiella pneumoniae lineages by FT-IR spectroscopy and machine-learning, a method that can be extremely useful to provide quick and reliable typing information to support real-time decisions of outbreak management and infection control. This method and workflow is of interest to support clinical microbiology diagnostics and to aid public health surveillance.

New insights on collagen structural organization and spatial distribution around dental implants: a comparison between machined and laser-treated surfaces.

BACKGROUND: One of the main factors for the osseointegration of dental implants is the development of an adequate soft tissue barrier, mainly composed by collagen, which protects the implant from bacterial development. The structural features of the peri-implant collagen are influenced by the implant components and, in particular, by the type of the surface. In the clinical practice, healing abutments are characterized by smooth surfaces, named machined. Recently, a new laser technique, Synthegra, has been developed to obtain a topography-controlled surface with micrometric regular pores that seems reducing the risk of peri-implantitis. Based on this background, this study aims investigating the structural organization and spatial distribution of collagen surrounding healing abutments characterized by laser-treated and machined surfaces. METHODS: Gingiva portions surrounding custom-made healing abutments (HA), characterized by alternated laser-treated and machined surfaces, were collected and analyzed by combining Fourier Transform InfraRed Imaging (FTIRI) spectroscopy, a non-invasive and high-resolution bidimensional analytical technique, with histological and multivariate analyses. RESULTS: Masson's trichrome staining, specific for collagen, highlighted a massive presence of collagen in all the analyzed samples, evidencing a surface-related spatial distribution. The nature of collagen, investigated by the FTIRI spectroscopy, appeared more abundant close to the laser-treated surface, with a perpendicular disposition of the bundles respect to the HA; conversely, a parallel distribution was observed around the machined surface. A different secondary structure was also found, with a higher amount of triple helices and a lower quantity of random coils in collagen close to the laser treated surfaces. CONCLUSIONS: FTIRI spectroscopy demonstrates that the use of a laser treated transmucosal surface can improve the morphological organization of the peri-implant collagen, which presents a distribution more similar to that of natural teeth. TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov Identifier: (Registration Number: NCT05754970). Registered 06/03/2023, retrospectively registered, https://clinicaltrials.gov/show/NCT05754970 .

Simultaneous brain and neck time-of-flight MRA using spiral multiband with localized quadratic encoding.

PURPOSE: To develop a method that achieves simultaneous brain and neck time-of-flight (ToF) magnetic resonance angiography (MRA) within feasible scan timeframes. METHODS: Localized quadratic (LQ) encoding is efficient for both signal-to-noise ratio (SNR) and in-flow enhancement. We proposed a spiral multiband LQ method to enable simultaneous intracranial and carotid ToF-MRA within a single scan. To address the venous signal contamination that becomes a challenge with multiband (MB) ToF, tilt-optimized non-saturated excitation (TONE) and partial-Fourier slice selection (PFSS) were further introduced in the LQ framework to mitigate the venous signal and improve artery contrast. A sequential spiral MB and LQ reconstruction pipeline was employed to obtain the brain-and-neck image volumes. RESULTS: The proposed MB method was able to achieve simultaneous brain and neck ToF-MRA within a 2:50-min scan. The complementarily boosted SNR-efficiency by MB and LQ acquisitions allows for the increased spatial coverage without increase in scan time or noticeable compromise in SNR. The incorporation of both TONE and PFSS effectively alleviated the venous contamination with improved small vessel sensitivity. Selection of scan parameters such as the LQ factor and flip angle reflected the trade-off among SNR, blood contrast, and venous suppression. CONCLUSIONS: A novel MB spiral LQ approach was proposed to enable fast intracranial and carotid ToF-MRA with minimized venous corruption. The method has shown promise in MRA applications where large spatial coverage is necessary.

Investigation of miltefosine-model membranes interactions at the molecular level for two different PS levels modeling cancer cells.

Miltefosine (MLT) is a broad-spectrum drug included in the alkylphospholipids (APL) used against leishmania and various types of cancer. The most crucial feature of APLs is that they are thought to only kill cancerous cells without harming normal cells. However, the molecular mechanism of action of APLs is not completely understood. The increase in the phosphatidylserine (PS) ratio is a marker showing the stage of cancer and even metastasis. The goal of this research was to investigate the molecular effects of miltefosine at the molecular level in different PS ratios. The effects of MLT on membrane phase transition, membrane orders, and dynamics were studied using DPPC/DPPS (3:1) and DPPC/DPPS (1:1) multilayer (MLV) vesicles mimicking DPPS ratio variation, Differential Scanning Calorimetry (DSC), and Fourier Transform Infrared spectroscopy (FTIR). Our findings indicate that miltefosine is evidence at the molecular level that it is directed towards the tumor cell and that the drug's effect increases with the increase of anionic lipids in the membrane depending on the stage of cancer.

Advances in high-resolution mass spectrometry techniques for analysis of high mass-to-charge ions.

A major challenge in modern mass spectrometry (MS) is achieving high mass resolving power and accuracy for precision analyses in high mass-to-charge (m/z) regions. To advance the capability of MS for increasingly demanding applications, understanding limitations of state-of-the-art techniques and their status in applied sciences is essential. This review summarizes important instruments in high-resolution mass spectrometry (HRMS) and related advances to extend their working range to high m/z regions. It starts with an overview of HRMS techniques that provide adequate performance for macromolecular analysis, including Fourier-transform, time-of-flight (TOF), quadrupole-TOF, and related data-processing techniques. Methodologies and applications of HRMS for characterizing macromolecules in biochemistry and material sciences are summarized, such as top-down proteomics, native MS, drug discovery, structural virology, and polymer analyses.

Plasma Volume Oscillations during Fluid Therapy in Humans.

INTRODUCTION: Oscillations are frequently observed on plasma dilution curves during intravenous fluid therapy. This study aimed to examine how common these oscillations are and what they represent. METHODS: Fourier transforms were used to analyze the residuals obtained during fitting of a volume kinetic model to 269 plasma dilution curves. Oscillating patterns were identified in two-thirds of the fluid infusion experiments. RESULTS: The wave frequency usually had a dominating frequency of 1 h or multiples thereof. The wave amplitudes varied between 1% and 4% of the plasma volume. The "peak-to-peak" amplitudes were then twice as large, which corresponded to blood volume changes of 60-240 mL. A population kinetic analysis of the distribution of infused fluid between body fluid compartments was then applied to search for clues that could explain the oscillations. This analysis showed that amplitudes >1.5% were associated with doubled turnover of fluid in a fast-exchange interstitial fluid compartment and, together with data on plasma albumin, suggested that oscillations might represent bursts of efferent lymph. CONCLUSIONS: Oscillations with very low frequency were often observed on plasma dilution-time curves obtained during fluid therapy. They were associated with fast turnover of interstitial fluid and can possibly have resulted from accelerated lymphatic flow.

Sequence comparison of spoiled gradient echo and balanced steady-state free precession for pulmonary free-breathing proton MRI in patients and healthy volunteers: Correspondence, repeatability, and validation with dynamic contrast-enhanced MRI.

Phase-resolved functional lung (PREFUL) MRI is a proton-based, contrast agent-free technique derived from the Fourier decomposition approach to measure regional ventilation and perfusion dynamics during free-breathing. Besides the necessity of extensive PREFUL postprocessing, the utilized MRI sequence must fulfill specific requirements. This study investigates the impact of sequence selection on PREFUL-MRI-derived functional parameters by comparing the standard spoiled gradient echo (SPGRE) sequence with a lung-optimized balanced steady-state free precession (bSSFP) sequence, thereby facilitating PREFULs clinical application in pulmonary disease assessment. This study comprised a prospective dataset of healthy volunteers and a retrospective dataset of patients with suspected chronic thromboembolic pulmonary hypertension. Both cohorts underwent PREFUL-MRI with both sequences to assess the correspondence of PREFUL ventilation and perfusion parameters (A). Additionally, healthy subjects were scanned a second time to evaluate repeatability (B), whereas patients received dynamic contrast-enhanced (DCE)-MRI, considered the perfusion gold standard for comparison with PREFUL-MRI (C). Signal-to-noise ratio (SNR), calculated from the unprocessed images, was compared alongside median differences of PREFUL-MRI-derived parameters using a paired Wilcoxon signed rank test. Further evaluations included calculation of the Pearson correlation, intraclass-correlation coefficient for repeatability assessment, and spatial overlap (SO) for regional comparison of PREFUL-MRI and DCE-MRI. bSSFP showed a clear SNR advantage over SPGRE (median: 23 vs. 9, p < 0.001). (A) Despite significant differences, parameter values were strongly correlated (r ≥ 0.75). After thresholding, binary maps showed high healthy overlap across both cohorts (SOHealthy > 86%) and high defect overlap in the patient cohort (SODefect ≥ 48%). (B) bSSFP demonstrated slightly higher repeatability across most parameters. (C) Both sequences demonstrated comparable correspondence to DCE-MRI, with SPGRE excelling in absolute quantification and bSSFP in spatial agreement. Although bSSFP showed superior SNR results, both sequences displayed spatial defect concordance and highly correlated PREFUL parameters with deviations regarding repeatability and alignment with DCE-MRI.

Motion-induced phase-corrected homodyne reconstruction for partial Fourier single-shot diffusion-weighted echo planar imaging of the liver.

Partial Fourier encoding is popular in single-shot (ss) diffusion-weighted (DW) echo planar imaging (EPI) because it enables a shorter echo time (TE) and, hence, improves the signal-to-noise-ratio. Motion during diffusion encoding causes k-space shifting and dispersion, which compromises the quality of the homodyne reconstruction. This work provides a comprehensive understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data in the presence of motion-induced phase and proposes the motion-induced phase-corrected homodyne (mpc-hdyne) reconstruction method to ameliorate these artifacts. Simulations with different types of motion-induced phase were performed to provide an understanding of the potential artifacts that occur in the homodyne reconstruction of partial Fourier ss-DW-EPI data. To correct for the artifacts, the mpc-hdyne reconstruction is proposed. The algorithm recenters k-space, updates the partial Fourier factor according to detected global k-space shifts, and removes low-resolution nonlinear phase before the conventional homodyne reconstruction. The mpc-hdyne reconstruction is tested on both simulation and in vivo data. Motion-induced phase can cause signal overestimation, worm artifacts, and signal loss in partial Fourier ss-DW-EPI data with the conventional homodyne reconstruction. Simulation and in vivo data showed that the proposed mpc-hdyne reconstruction ameliorated artifacts, yielding higher quality DW images compared with conventional homodyne reconstruction. Based on the understanding of the artifacts in homodyne reconstruction of partial Fourier ss-DW-EPI data, the mpc-hdyne reconstruction was proposed and showed superior performance compared with the conventional homodyne reconstruction on both simulation and in vivo data.

A comparative analysis of univariate versus multivariate eco-friendly spectrophotometric manipulations for resolving severely overlapped spectra of vonoprazan and amoxicillin new combination.

Vonoprazan and amoxicillin are pharmacological combinations that demonstrate synergistic effects in treating Helicobacter pylori (H. pylori), a global public health concern associated with peptic ulcer disease and gastric cancer. Four spectrophotometric methods were developed, including two univariate techniques (Fourier self-deconvolution and ratio difference) and two multivariate chemometric approaches (partial least squares and principal component regression). These methods provide innovative solutions for effectively resolving and accurately quantifying the overlapping spectra of vonoprazan and amoxicillin. The concentration ranges covered were 3-60 µg ml-1 for vonoprazan and 5-140 µg ml-1 for amoxicillin. To assess the environmental sustainability of the methodologies, various measures such as the Green Analytical Procedure Index (GAPI), National Environmental Method Index (NEMI), Analytical GREEnness Calculator, and Analytical Eco-scale, as well as RGB12 and hexagon toll were implemented. The validation of the developed techniques was carried out in compliance with ICH standards. The present study is highly significant because it is the first time that the mixture has been determined using the current approaches. The comparative analysis demonstrated no significant difference in terms of accuracy and precision compared to reference HPLC method (p = 0.05). The established spectrophotometric methods offer a straightforward, rapid, and cost-effective alternative to complex analytical techniques for determining the vonoprazan and amoxicillin mixture. They show potential for routine analysis in research laboratories and pharmaceutical industries.