Analytical Guidelines Research Articles

RGB Trichromatic Whiteness Assessment of Bio Analytical Chromatographic Tool Using Fluorescence for Quantitation of Semaglutide: Application to Pharmaceutical Preparations and Spiked Plasma.

Semaglutide (SEMG) is one of the most widely used and trending medications to treat type II diabetes and obesity.This work aimed to develop a liquid chromatography with spectroflourimetric detection (HPLC-flourimetry) analysis of SEMG in both its tablet dosage form and plasma. The power of fluorescence detection coupled with HPLC proved its capability as a bioanalytical tool to assay SEMG in plasma samples owing to its simplicity and sensitivity which reached below the Cmax of SEMG. Separation was done using a C18 column with mobile phase of acetonitrile and water acidified with orthophosphoric acid (pH 3.5) (1.41 × 10-5M) in isocratic mode in ratio 57:43 and 1mL/min flow rate after extraction using protein precipitation. Detection was carried out at λ excitation of 238nm and λ emission of 416 and 307nm for SEMG and the internal standard, respectively. Evaluation of greenness of the proposed method was done using AGREE (Analytical GREEnness Metric Approach), ComplexGAPI (Complementary Green Analytical Procedure Index) & the new algorithm RGB 12 model (Red-Green-Blue). They showed that these methods can be a greener alternative with acceptable sensitivity for analysis of SEMG. The developed seven min-assay was validated per ICH as well as FDA bio analytical methods' guidelines to prove its applicability for routine sample analysis and future pharmacokinetic studies.

Decentralised autonomous organisations: targeting the potential beyond the hype

ABSTRACT Decentralised Autonomous Organisations (DAOs) aim at innovating the organisation forms for business activities. They are complex blockchain-based smart contracts, which allow token holders to participate directly in decision-making processes and decentralised entrepreneurial activities as much as possible. The advocates of this new kind of digital organisation argue that DAOs enjoy significant operational efficiencies and can effectively work outside of any legal recognition. This paper analyses DAOs through the lenses of the economic and legal theories on the firm and on business organisation. The analysis makes three contributions: first, it contributes to the literature on the theory of the firm, looking at the role of digital technology in innovating the organisation of business activities. Second, it enriches the literature on the legally recognised forms of business organisation, analysing the tension between the essential role of the law and the limitations of tamper-resistant technologies, such as the blockchain. Third, it overcomes the largely ideological and dichotomic debate on the promises of DAOs, providing analytical guidelines as to why current forms of sector-specific regulation fail to leverage the potential of DAOs.

Robust PI-PD Controller Design: Industrial Simulation Case Studies and a Real-Time Application

PI-PD controllers have superior performance compared to traditional PID controllers, especially for controlling unstable and integrating industrial processes with time delays. However, computing the four tuning parameters of this type of controller is not an easy task. Recently, there has been significant interest in determining the tuning rules for PI-PD controllers that utilize the stability region. Currently, most tuning rules for the PI-PD controller are presented graphically, which can be time-consuming and act as a barrier to their industrial application. There is a lack of analytical tuning guidelines in the literature to address this shortfall. However, the existing analytical tuning guidelines do not consider a rigorous design approach. This work proposes new robust analytical tuning criteria based on predefined gain and phase margin bounds, as well as the centroid of the stability region. The proposed method has been tested using various simulation studies related to a DC–DC buck converter, a DC motor, and a heat exchanger. The results indicate that the proposed tuning rules exhibit strong performance against parameter uncertainty with minimal overshoots. Furthermore, the suggested technique for simultaneous control of yaw and pitch angles has been tested in a real-time application using the twin rotor multi-input multi-output system (TRMS). Real-time results indicate that, compared to other methods under investigation, the suggested approach provides nearly minimal overshoots.

Association of habitual sleep duration with abnormal bowel symptoms: a cross-sectional study of the 2005–2010 national health and nutrition examination survey

ObjectivesNowadays, few studies have examined the relationships between sleep duration and abnormal gut health. In this study, we used data from the National Health and Nutrition Examination Survey (NHANES) to investigate the correlations between habitual sleep duration and abnormal bowel symptoms in adults.MethodsThis study included 11,533 participants aged ≥ 20 years from the NHANES conducted during 2005–2010. Chronic constipation and chronic diarrhea were defined based on the Bristol Stool Form Scale (BSFS) and frequency of bowel movements. Sleep duration was assessed based on the self-report questionnaire and classified into three groups: short sleep duration (< 7 h), normal sleep duration (7–9 h), and long sleep duration (> 9 h). Weighted data were calculated according to analytical guidelines. Logistic regression models and restricted cubic spline curves (RCS) were used to assess and describe the association between sleep duration and chronic diarrhea and constipation. Univariate and stratified analyses were also performed.ResultsThere were 949 (7.27%) adults aged 20 years and older with chronic diarrhea and 1120 (8.94%) adults with constipation among the 11,533 individuals. A positive association was found between short sleep duration and chronic constipation, with a multivariate-adjusted OR of 1.32 (95% CI: 1.05–1.66). Additionally, long sleep duration was significantly associated with an increased risk of chronic diarrhea (OR: 1.75, 95% CI: 1.08–2.84, P = 0.026). The RCS models revealed a statistically significant nonlinear association (P for non-linearity < 0.05) between sleep duration and chronic diarrhea. Furthermore, obesity was found to modify the association between sleep duration and chronic diarrhea and constipation (p for interaction = 0.044).ConclusionsThis study suggests that both long and short sleep durations are associated with a higher risk of chronic diarrhea and constipation in the general population. Furthermore, a non-linear association between sleep duration and these conditions persists even after adjusting for case complexities.

Analytical Procedure Development and Proposed Established Conditions: A Case Study of a Mass Spectrometry Based NDSRI Analytical Procedure

With the finalization of the ICH Q14 Analytical Procedure Development guideline, how to apply enhanced approaches (such as analytical quality by design (AQbD)) to develop an analytical procedure, and to propose Established Conditions (ECs) and corresponding reporting categories, is increasingly being discussed. To gain practical experience in applying an enhanced approach for method development and identifying ECs, we developed, validated, and implemented an analytical procedure for a nitrosamine drug substance-related impurity (NDSRI). Here, as an example of the application of Q12 Lifecycle Management guideline principles in regards to analytical procedures, we briefly elaborate how: 1) the principles documented in the ICH Q14 guideline for analytical procedure development were applied, with the focus on identifying an Analytical Target Profile (ATP), knowledge management and risk assessment; 2) analytical procedure robustness according to the recommendations in ICH Q2(R2) Validation of Analytical Procedure guideline and Q14, were evaluated; and 3) mass spectrometry ECs and associated proposed reporting categories were proposed.

Cohort-based strategies as an in-house tool to evaluate and improve phenotyping robustness of LC–MS/MS lipidomics platforms

In recent years, instrumental improvements have enabled the spread of mass spectrometry–based lipidomics platforms in biomedical research. In mass spectrometry, the reliability of generated data varies for each compound, contingent on, among other factors, the availability of labeled internal standards. It is challenging to evaluate the data for lipids without specific labeled internal standards, especially when dozens to hundreds of lipids are measured simultaneously. Thus, evaluation of the performance of these platforms at the individual lipid level in interlaboratory studies is generally not feasible in a time-effective manner. Herein, using a focused subset of sphingolipids, we present an in-house validation methodology for individual lipid reliability assessment, tailored to the statistical analysis to be applied. Moreover, this approach enables the evaluation of various methodological aspects, including discerning coelutions sharing identical selected reaction monitoring transitions, pinpointing optimal labeled internal standards and their concentrations, and evaluating different extraction techniques. While the full validation according to analytical guidelines for all lipids included in a lipidomics method is currently not possible, this process shows areas to focus on for subsequent method development iterations as well as the robustness of data generated across diverse methodologies.Graphical abstract

Comparison of Analytical Method validation guidelines used for release, stability in Biosimilar Manufacturing process

Comparison of Analytical Method validation guidelines used for release, stability in Biosimilar Manufacturing process

Increased regional body fat is associated with depressive symptoms: a cross-sectional analysis of NHANES data obtained during 2011–2018

AimsThe findings from previous epidemiological studies of the association between regional body fat and depressive symptoms have been unclear. We aimed to determine the association between the body fat in different regions and depressive symptoms based on data from the National Health and Nutrition Examination Survey (NHANES).MethodsThis study included 3393 participants aged ≥ 20 years from the NHANES performed during 2011–2018. Depressive symptoms were assessed using the Patient Health Questionnaire-9. The fat mass (FM) was measured in different regions using dual-energy X-ray absorptiometry to determine the total FM, trunk FM, arm FM, and leg FM. The FM index (FMI) was obtained by dividing the FM in kilograms by the square of the body height in meters. Weighted data were calculated in accordance with analytical guidelines. Linear logistic regression models were used to quantify the association between regional FMI and depressive symptoms. Univariate and stratified analyses were also performed.ResultsThe participants in this study comprised 2066 males and 1327 females. There were 404 (11.91%) participants with depressive symptoms, who were aged 40.89 ± 11.74 years and had a body mass index of 30.07 ± 7.82 kg/m². A significant association was found between total FMI and depressive symptoms. In the fully adjusted multivariate regression model, a higher total FMI (odds ratio = 2.18, 95% confidence interval [CI] = 1.08–4.39) was related to a higher risk of depressive symptoms, while increased total FMI (β = 1.55, 95% CI = 0.65–2.44, p = 0.001), trunk FMI (β = 0.57, 95% CI = 0.04–1.10, p = 0.036), and arm FMI (β = 0.96, 95% CI = 0.33–1.59, p = 0.004) were significantly associated with PHQ-9 (Patient Health Questionnaire-9) scores, whereas the leg FMI was not (p = 0.102). The weighted association between total FMI and depressive symptoms did not differ significantly between most of the subpopulations (all p values for interaction > 0.05). The risk of having depression was higher in individuals who were non-Hispanic Whites, smokers, drinkers, obese, and had diabetes and thyroid problems (p < 0.05).ConclusionThese findings suggest that the population with a higher regional FMI is more likely to have depressive symptoms, especially in those who also have an increased total FMI. The association is more pronounced in individuals who are smokers, drinkers, obese, and have diabetes and thyroid problems.

RP-HPLC Estimation of Clobetasol Propionate and Salicylic Acid using Quality by Design Approach

ABSTRACT: The RP-HPLC method for CLOP and SA estimation from bulk and pharmaceutical dosage from has been developed and validated. For analytical methods to be robust, current ICH guidelines, Q8 to Q11 were suggested use of analytical quality by design (AQbD) includes adoption of current systematic approaches. The proposed method was optimized and developed using Taguchi orthogonal design. The RP-HPLC method parameters were optimized by box- Behnken design. The stationary phase used C18 Princeton column (150mm × 4.6mm × 5µm) with acetonitrile: 0.05M phosphate buffer (pH 2.5, adjustment with by ortho - phosphoric acid) as mobile phase at ratio of 60:40v/v, 1.0 ml/min of flow rate along with UV-Visible wavelength of detection 240 nm. The linearity over concentration 5-15 µg/ml for CLOP and 600-1500 µg/ml for SA (r2 =0.9969 for CLOP and 0.9943 for SA) was found. The retention time for SA was 2.2 min. and CLOP 7.0 minute. The % recovery was found to be 98.0.3 SA and 97.84 or CLOP. As per ICH analytical method validation guidelines [Q2 (R1)], the RP-HPLC method was validated.

Detection of Anatoxins in Human Urine by Liquid Chromatography Triple Quadrupole Mass Spectrometry and ELISA.

Harmful cyanobacterial blooms are becoming more common and persistent around the world. When in bloom, various cyanobacterial strains can produce anatoxins in high concentrations, which, unlike other cyanobacterial toxins, may be present in clear water. Potential human and animal exposures to anatoxins occur mainly through unintentional ingestion of contaminated algal mats and water. To address this public health threat, we developed and validated an LC-MS/MS method to detect anatoxins in human urine to confirm exposures. Pooled urine was fortified with anatoxin-a and dihydroanatoxin at concentrations from 10.0 to 500 ng/mL to create calibrators and quality control samples. Samples were diluted with isotopically labeled anatoxin and solvent prior to LC-MS/MS analysis. This method can accurately quantitate anatoxin-a with inter- and intraday accuracies ranging from 98.5 to 103% and relative standard deviations < 15%, which is within analytical guidelines for mass spectrometry methods. Additionally, this method qualitatively detects a common degradation product of anatoxin, dihydroanatoxin, above 10 ng/mL. We also evaluated a commercial anatoxin-a ELISA kit for potential diagnostic use; however, numerous false positives were detected from unexposed individual human urine samples. In conclusion, we have developed a method to detect anatoxins precisely and accurately in urine samples, addressing a public health area of concern, which can be applied to future exposure events.

Framework for in vivo T cell screens.

In vivo T cell screens are a powerful tool for elucidating complex mechanisms of immunity, yet there is a lack of consensus on the screen design parameters required for robust in vivo screens: gene library size, cell transfer quantity, and number of mice. Here, we describe the Framework for In vivo T cell Screens (FITS) to provide experimental and analytical guidelines to determine optimal parameters for diverse in vivo contexts. As a proof-of-concept, we used FITS to optimize the parameters for a CD8+ T cell screen in the B16-OVA tumor model. We also included unique molecular identifiers (UMIs) in our screens to (1) improve statistical power and (2) track T cell clonal dynamics for distinct gene knockouts (KOs) across multiple tissues. These findings provide an experimental and analytical framework for performing in vivo screens in immune cells and illustrate a case study for in vivo T cell screens with UMIs.

Healthy eating index-2015 and its association with the prevalence of stroke among US adults

This study aims to investigate the relationship between the healthy eating index (HEI) and the prevalence of stroke within a diverse United States population. Employing a cross-sectional design, we utilized data sourced from the National Health and Nutrition Examination Survey (NHANES). Dietary information was collected from participants and HEI scores were computed. NHANES employed stratified multistage probability sampling, with subsequent weighted analysis following NHANES analytical guidelines. Thorough comparisons were made regarding the baseline characteristics of individuals with and without stroke. Weighted multivariable logistic regression analysis and restricted cubic spline (RCS) methods were employed to ascertain the association between stroke risk and HEI, with LASSO regression utilized to identify dietary factors most closely linked to stroke risk. Additionally, we constructed a nomogram model incorporating key dietary factors and assessed its discriminatory capability using the receiver operating characteristic (ROC) curve. Our study encompassed 43,978 participants, representing an estimated 201 million U.S. residents. Participants with a history of stroke exhibited lower HEI scores than their non-stroke counterparts. Logistic regression analysis demonstrated a robust association between lower HEI scores and stroke, even after adjusting for confounding variables. RCS analysis indicated a nonlinear negative correlation between HEI and stroke risk. Furthermore, detailed subgroup analysis revealed a significant gender-based disparity in the impact of dietary quality on stroke risk, with females potentially benefiting more from dietary quality improvements. Sensitivity analysis using unweighted logistic regression yielded results consistent with our primary analysis. The nomogram model, based on key dietary factors identified through LASSO regression, demonstrated favorable discriminatory power, with an area under the curve (AUC) of 79.3% (95% CI 78.4–81.2%). Our findings suggest that higher HEI scores are inversely related to the risk of stroke, with potential greater benefits for women through dietary quality enhancement. These results underscore the importance of improving dietary quality for enhanced stroke prevention and treatment.

Plant extract mediated synthesis of ZnO and CeO2 nanoparticles for spectrofluorometric assay of omeprazole and domperidone in pharmaceuticals

The current research proposed a highly sensitive and selective spectrofluorometric approach for the assay of gastrointestinal medications omeprazole (OMZ) and domperidone (DOM). Green synthesis of metal oxide nanoparticles such as zinc oxide (ZnONPs) and cerium oxide (CeO2NPs) using Pimpinella anisum and Syzygium aromaticum extract was used as fluorescence emission catalysts for the determination of OMZ and DOM. Due to their unique optical properties, nanoparticles (NPs) form the basis for spectrofluorimetric quantification of the selected drugs. The detection studies were performed under λex/λem 350/450 nm and 284/392 nm for OMZ and DOM in the presence of ZnONPs and CeO2NPs, respectively. Under ideal conditions, fluorescence intensities (FI) were linearly with correlation coefficient (r = 0.999) over concentration ranges of 0.1–100 and 0.01–200 μg mL−1 for OMZ, 0.01–100 and 0.01–300 n g mL−1 for DOM in the presence of ZnONPs and CeO2NPs, respectively. Method validation was carried out to guarantee the accuracy, suitability, and precision of the proposed fluorescence (FL) systems for the determination of OMZ and DOM. Analytical method guidelines and requirements were followed. The designed procedure was used effectively to identify the determined drugs in both their pure and commercial versions.

Supporting Older Adults' Social Inclusion and Well‐Being in Neighbourhoods: The Social Hub Model

In recent years, many Finnish cities and municipalities have aspired to develop services that support older adults’ well‐being and social inclusion. This study focuses on the Social Hub model, a local social innovation developed in the city of Tampere. Social hubs operate on a neighbourhood level, providing free‐of‐charge service coordination and counselling, group activities, and meeting places for social gatherings. This study aims to look at whether this kind of local innovation can support older adults’ well‐being and social inclusion. The sociomaterial perspective and multidimensional model of well‐being (the having–doing–loving–being approach) provided theoretical and analytical guidelines to examine older adults’ experiences and perceptions of social hubs. The qualitative interview data was collected among people living in service housing, senior housing, or ordinary housing in the proximity of the social hubs studied. Face‐to‐face and “go‐along” interviews with 19 older adults aged between 57 and 96 were analysed with theory‐driven content analysis. The results showed that the hubs are a valuable local resource for older adults, providing free services, accessible and appealing shared spaces, and activities that promote social well‐being, physical activity, creativity, and autonomy. The hubs serve as important gathering points for older adults in the neighbourhood, fostering community‐building among citizens residing in different types of housing. The results highlight the importance of acknowledging well‐being as a multidimensional phenomenon. The Social Hub model provides one practical tool to support older adults’ well‐being and social inclusion by offering various kinds of resources and social and cultural activities.

Direct synthesis method of wideband tunable filtering phase shifter based on complex matched transversal multiple resonances

In this article, a wideband filtering phase shifter (FPS) based on transversal multiple resonances is proposed. By utilizing transversal resonances with complex impedance, a wide operation band is achieved with compact circuit size. By doubly loading the tunable external coupling networks (ECNs) with complex impedance, the FPS obtains continuous phase tuning with stable filtering performance. In addition to the structural construction, a set of analytical formulas and guidelines for the direct synthesis of the FPS are provided, rather than tedious optimization. Finally, an FPS using transversal three resonances with complex impedance is designed, fabricated, and measured to validate the concept. The example showcases a wide 10-dB RL bandwidth of 32.5% with high selectivity, a compact size of 0.068 λg2, a phase shift range (PSR) of 105°, and a low phase error of ±5.4∘.

Eco‐friendly synchronous fluorescence spectrofluorimetric method for simultaneous determination of montelukast sodium and fexofenadine hydrochloride in their antiallergic rhinitis fixed‐dose combination tablets

AbstractAn innovative, simple, accurate, sensitive, and eco‐friendly synchronous fluorescence spectrofluorimetric method has been developed for the simultaneous analysis of montelukast sodium (MON) and fexofenadine hydrochloride (FEX). The method relies on measuring the relative synchronous fluorescence intensity of both drugs using Δλ of 60 nm in methanol at 405 nm for MON and 288 nm for FEX. The experimental parameters influencing the developed method were investigated and optimized. The method was linear over the ranges 0.1–2.0 and 2.0–20.0 μg/ml for MON and FEX, respectively. The limits of detection were 0.018 and 0.441 μg/ml, and the limits of quantitation were 0.055 and 1.336 μg/ml for MON and FEX, respectively. The developed method was applied successfully for the determination of the two drugs in their newly released fixed‐dose combination prescribed for the treatment of allergic rhinitis. The mean per cent recoveries were found to be 100.680 ± 0.890 and 100.110 ± 0.940 for MON and FEX, respectively. Furthermore, the method was found to be eco‐friendly green as was evaluated according to the Green Analytical Procedure Index tool guidelines and analytical eco‐scale.

A Sequential Feature-Based Rate of Penetration Representation Prediction Method by Attention Long Short-Term Memory Network

Summary In the petroleum and gas industry, optimizing cost-effectiveness remains a paramount objective. One of the key challenges is enhancing predictive models for the rate of penetration (ROP), which are intricately tied to the delicate interplay between significant parameters and drilling efficiency. Recent research has hinted at the potential of temporal and sequential elements in drilling, but a detailed exploration and understanding of these dynamics remain underdeveloped. Addressing this research gap, our primary innovation is not just the introduction of a model but rather the employment of the attention-based long short-term memory (LSTM) network as a tool to deeply analyze the role of sequential features in ROP prediction. Beyond merely applying the model, we furnish a robust foundation for sequential analysis, detailing data processing methods and laying out comprehensive data analytics guidelines for such temporal assessments. The utilization of the LSTM network, in this context, ensures meticulous capture of real-time drilling data nuances, providing insights that are both profound and actionable. Through empirical evaluations with real-world data sets, we accentuate the vital importance of time-sequential dynamics in refining ROP predictions. Our methodological approach, tailored for the oilfield domain, is both rigorous and illuminating, achieving an R2 score of 0.95 and maintaining a relative error under 10%. This effort goes beyond simply proposing a new predictive mechanism. It establishes the centrality of sequential analysis in the drilling process, charting a course for future research and operational optimization in the petroleum and gas sector. We not only offer enhanced modeling strategies but also pioneer insights that can shape the next frontier of industry advancements.

Simultaneous Detection and Quantification of Aflatoxin M1, Eight Microcystin Congeners and Nodularin in Dairy Milk by LC-MS/MS

Dairy milk holds a prominent position as a widely consumed food, particularly among infants and children. However, it is crucial to address the presence of multiple natural toxic compounds that may co-occur in dairy milk to ensure its safety prior to consumption. Aflatoxin M1 (AFM1), an emerging mycotoxin of interest, is a potential contaminant in the milk of animals who ingest aflatoxin B1 (AFB1). The toxin is regulated in the European Union under Commission Regulation No 1881/2006. Unfortunately, there is a notable lack of data concerning the transfer of various emerging microbial contaminants into dairy milk and, therefore, their natural occurrences. In this study, a simple and sensitive LC-MS/MS method was developed and validated for the quantification of multiple cyanotoxins (microcystin congeners and nodularin) and AFM1 by the main analytical guidelines. Toxins are extracted with methanol 80%, followed by an SPE clean-up step before LC-MS/MS analysis. The LOQ was fixed at 1 µg/L for the nine cyanotoxins and 0.05 µg/L for AFM1. Recoveries were measured between 82.67% and 102%. To the best of our knowledge, there are no other LC-MS/MS methods available for the simultaneous quantification of cyanotoxins and mycotoxins in milk.

Fast and robust DC link voltage control of single-phase grid-connected converters supporting 50 Hz and 60 Hz mains with universal magnitudes range

It is well-known that dynamics of single-phase grid-connected power converters employing PI or type-II DC link voltage controllers is limited by the maximum tolerable value of utility-side current total harmonic distortion (THD). Moreover, universal DC link voltage controller must be capable of supporting both 50 Hz and 60 Hz utilities and universal range of magnitudes (85Vrms–265Vrms). As a result, DC link crossover frequency value (and hence corresponding settling time) may vary significantly in case grid voltage magnitude variations are not compensated in the controller. In order to cope with the above-mentioned deficiencies, the paper suggests a design methodology for a novel dual-frequency-tuned utility magnitude insensitive plug-in disturbance observer (DOB), supporting universal utility frequencies and magnitudes so that the transient response of a grid-connected converter is improved without altering the existing PI or type-II DC link voltage controller coefficients. These characteristics are attained by robust modification of DC link voltage loop plant to possess notch-like properties around two frequencies of interest and treating the grid voltage magnitude value as non-measurable uncertainty translated into input disturbance and subsequently cancelled. Analytical design guidelines for obtaining PI + DOB controller coefficients are provided for desired values of utility-side current THD and DC link voltage loop phase margin (PM). Simulations and experimental results are provided to validate the feasibility of proposed design methodology.

The association between serum albumin and depressive symptoms: a cross-sectional study of NHANES data during 2005–2018

AimsThe association between serum albumin and depressive symptoms has been unclear in previous epidemiological studies. We explored whether serum albumin is associated with depressive symptoms based on the National Health and Nutrition Examination Survey (NHANES) data.MethodsThis cross-sectional study included 13,681 participants aged ≥ 20 years from the NHANES performed during 2005–2018, which produced nationally representative database. Depressive symptoms were assessed using the Patient Health Questionnaire-9. Serum albumin concentration was measured using the bromocresol purple dye method, and participants were divided into quartiles of serum albumin concentrations. Weighted data were calculated according to analytical guidelines. Logistics regression and linear regression models were used to assess and quantify the association between serum albumin and depressive symptoms. Univariate and stratified analyses were also performed.ResultsThere were 1551 (10.23%) adults (aged ≥ 20 years) with depressive symptoms among the 13,681. A negative association was found between serum albumin concentration and depressive symptoms. Compared with the lowest albumin quartile, the multivariate-adjusted effect size (95% confidence interval) for depressive symptoms of the fully adjusted model in the highest albumin quartile was 0.77 (0.60 to 0.99) and − 0.38 (− 0.66 to − 0.09) using logistics regression and linear regression models respectively. Current smoking status modified the association between serum albumin concentration and PHQ-9 scores (p for interaction = 0.033).ConclusionThis cross-sectional study revealed that albumin concentration is significantly more likely to be a protective factor for depressive symptoms, with the association being more pronounced in non-smokers.