Intersectional Analysis Research Articles

The transmission of social inequalities through economic difficulties and lifestyle factors on body mass index: An intersectional mediation analysis in the Swedish population

Body mass index (BMI) has increased in Sweden, disproportionally for socially disadvantaged groups, including women, low-educated, and immigrants, who may also face economic constraints, physical inactivity, and poor-quality diets. Intersectional public health research aims to unravel such complex social inequalities, but the intersectional transmission of inequalities to BMI remains unexplored. We aimed to examine intersectional inequalities in BMI mediated by economic strain and health-related lifestyle in the Swedish population. By using the Health on Equal Terms cross-sectional surveys in 2016, 2018, 2020, and 2021 (n = 44,177 inhabitants aged 25 and over), we performed an intersectional mediation analysis to analyze how inequalities across social intersectional strata (by gender, education, and migration status) may be transmitted through economic strain and unhealthy lifestyle (physical inactivity or inadequate fruit/vegetables consumption) to BMI. Our findings showed a sequential transmission that indicates the fact that socially disadvantaged strata (compared with high-educated native men) experienced more economic strain, which in turn led to poorer health-related lifestyles and ultimately to a higher BMI. We also found that certain intersectional strata, such as high-educated women, were more vulnerable to economic strain, despite having lower BMI than high-educated native men. Additionally, the highest BMI and unhealthy lifestyle risk was observed among low- and middle-educated men. In conclusion, not only inequalities in BMI, but also the economic and behavioral pathways underpinning the inequalities, act by intersectional patterns. Public health interventions should provide economic security, particularly for women and migrant population as well as promoting a healthy lifestyle in lower-educated strata, especially among men, to achieve healthy BMI levels.

Challenges in Agrobiodiversity Maintenance in Southwest Bangladesh: An Intersectional Analysis

Guided by the intersectional approach, the objective of the paper is to engage gender as an analytical variable across class and spatial inequalities to explore agrobiodiversity maintenance. The paper dwells on challenges faced, and factors influencing agrobiodiversity choices and its maintenance. Data was collected from a survey of 343 households, 14 focus group discussions conducted in seven villages, and in-depth interviews with 30 research participants in Southwest Bangladesh. The findings show that challenges in maintaining agrobiodiversity and its choices are gender, class, and spatially differentiated within the context of environmental change. The challenges faced by rural households in maintaining agrobiodiversity are not linear and straightforward and poor women are inclined to make choices to ensure food security and wellbeing of the family. Therefore, understanding how overlapping inequalities in rural farming areas experiencing environmental change is key to the design of agrobiodiversity-based solutions towards food security for the poor.

Identification of psoriasis-associated immune marker G3BP2 through single-cell RNA sequencing and meta analysis.

Psoriasis is a chronic skin disease with an increasing prevalence each year. However, the mechanisms underlying its onset and progression remain unclear, and effective therapeutic targets are lacking. Therefore, we employs an innovative approach by combining single-cell RNA sequencing (scRNA-seq) with meta-analysis. This not only elucidates the potential mechanisms of psoriasis at the cellular level but also identifies immunoregulatory marker genes that play a statistically significant role in driving psoriasis progression through comprehensive analysis of multiple datasets. Skin tissue samples from 12 psoriasis patients underwent scRNA-seq, followed by quality control, filtering, PCA dimensionality reduction, and tSNE clustering analysis to identify T cell subtypes and differentially expressed genes (DEGs) in psoriatic skin tissue. Next, three psoriasis datasets were standardised and merged to identify differentially expressed genes (DEGs). Subsequently, weighted gene co-expression network analysis (WGCNA) was applied for clustering analysis of gene co-expression network modules and to assess the correlation between these modules and DEGs. Least absolute shrinkage and selection operator (LASSO) regression and receiver operating characteristic (ROC) curve analyses were conducted to select disease-specific genes and evaluate their diagnostic value. Single-cell data revealed nine cell types in psoriatic skin tissue, with seven T cell subtypes identified. Intersection analysis identified ADAM8 and G3BP2 as key genes. Through the integration of scRNA-seq and Meta analysis, we identified the immunoregulatory marker gene G3BP2, which is associated with the onset and progression of psoriasis and holds clinical significance. G3BP2 is speculated to promote the development of psoriasis by increasing the proportion of CD8+ T cells.

Does 4IR and Covid 19 Effect The Quality of Work Life and Living Standard of Women Workers? Evidence from Selected RMG Firms in Bangladesh

Purposes The study's main objective is to find out the impact of the fourth industrial revolution and covid-19 on women workers of selected Ready-Made Garments (RMG) sector in Bangladesh. Methodology This study mainly followed a quantitative research approach with survey study. Total 18 garments (case) has been chosen randomly from DSE listed RMG firm based on access priority. Sample size for survey study has been determined by statistical method is 384. But this study consider total (15*27) = 405. Data have been collected from selected respondents (women workers) using structured questionnaire. Findings The study reveals that women workers in the RMG sector exhibit a remarkable lack of anxiety about their work-life quality, largely due to their experience and resilience in handling the challenges of their profession. It highlights the adaptability of these workers and underscores the importance of targeted support and interventions to promote sustainable livelihoods and better working conditions amid persistent challenges. Implications The study's findings can inform policymakers about the specific challenges faced by women workers in the RMG sector due to the convergence of 4IR and the COVID-19 pandemic. Originality/Value this study's originality and value lie in its intersectional analysis, empirical evidence, contextual specificity, practical implications, and contributions to knowledge, all of which enrich our understanding of the complex dynamics shaping the lives of women workers in Bangladesh's RMG sector amidst the challenges of 4IR and COVID-19. Limitations The study's findings may be limited by the scope of the selected RMG firms and the sample size of women workers included in the research. While efforts were made to ensure diversity within the sample, the findings may not be representative of all women workers in the RMG sector in Bangladesh, limiting the generalizability of the results.

The influence of modified Qing E Formula on the differential expression of serum exosomal miRNAs in postmenopausal osteoporosis patients.

Although guidelines support the efficacy of Modified Qing' E Formula (MQEF) in treating postmenopausal osteoporosis (PMOP), its underlying mechanisms remain incompletely understood. This retrospective investigation aims to elucidate MQEF's impact on serum exosomal miRNA expression in postmenopausal osteoporosis patients and to explore potential therapeutic mechanisms. Following ethical approval and registration, postmenopausal osteoporosis patients aged 50-85years, meeting the diagnostic criteria were randomly selected and received MQEF decoction supplementary therapy. Serum samples were collected pre- and post-treatment, followed by isolation and sequencing of exosomal miRNAs. Differential miRNAs in serum exosomes were identified, and bioinformatics analysis was conducted to discern the principal exosomal miRNAs involved in MQEF's effects on PMOP and the associated signaling pathways. Eighteen clinical blood samples were collected. A total of 282,185 target genes were detected across the three groups. 306 miRNAs exhibited altered expression in serum exosomes of PMOP patients, while MQEF intervention resulted in changes in 328 miRNAs. GO enrichment analysis revealed the immune and endocrine systems was pertained. KEGG enrichment analysis indicated associations between PMOP occurrence and MQEF treatment with cytokine interactions, oxidative phosphorylation, and the renin-angiotensin system. Intersectional analysis identified 17 miRNAs, including 2 consistent trends. miR-3188 as a potentially pivotal miRNA implicated in both PMOP occurrence and MQEF treatment. This study constitutes the first randomized, retrospective clinical exploration confirming that MQEF demonstrates regulatory influence over exosomal miRNA expression in PMOP patients' serum, its impact likely involves modulation of the immune and endocrine systems, as well as the renin-angiotensin system.

The cruel optimism of contact improvisation: Dancing between neoliberal subjectivation and practices of commoning

Within the social world of Contact Improvisation, the question of class relations remains conspicuous by its absence. Whilst ongoing debates in the global Contact Improvisation (CI) community and recent scholarship have foregrounded the problem of Whiteness, there have been few attempts to provide intersectional analyses of the racialised, classed subjectivation of contact dancers. To make such future enquiry possible, this paper dismantles originary CI myths about ‘natural’ movement, also attended to by Bojana Cvejić, and explores the question of social antagonism through analysing the dance form’s discursive norms and movement vocabulary. As this essay argues, the contact dancer occupies a paradoxical subject position: between a neoliberal embrace of risk-taking and precarity, and a cruelly optimistic prefiguration of the commons.

Peace and Human Rights in Sri Lanka: The Struggle for Marginalised Communities to Advocate for Justice

Peace and human rights serve as a check on the dominant or majoritarian culture. An absence of human rights is conducive to weak democratic forms, unequal social and political relations, marginalisation, oppression and, in some cases, criminalisation of communities. Such a scenario can be found in Sri Lanka. This paper expands upon a principal research project which found that the marginalisation of participants arose from aspects of their particular identities, including diverse sexualities and genders, races, ethnicities, religions and youth. The principal research was informed by intersectionality, social interactionism, interviews and interpretative phenomenological analysis. This paper was composed out of the research results and was further structured by literature review. People’s marginalisation, oppression and exclusion are related directly to the absence of peace and human rights manifested through injustices and structural barriers that frustrated social and political participation.

Life course financial mobility and later-life memory function and decline by gender, and race and ethnicity: an intersectional analysis of the US KHANDLE and STAR cohort studies

Intersectionality has rarely been considered in research studies of cognitive ageing. We investigated whether life-course financial mobility is differentially associated with later-life memory function and decline across intersectional identities defined by gender, and race and ethnicity. Data were from two harmonised multiethnic cohorts (the Kaiser Healthy Aging and Diverse Life Experiences cohort and the Study of Healthy Aging in African Americans cohort) in northern California, USA (n=2340). Life-course financial mobility, measured using a combination of self-reported financial capital measures in childhood (from birth to age 16years) and later adulthood (at the cohort baseline) was defined as consistently high, upwardly mobile, downwardly mobile, or consistently low. We clustered individuals into 32strata representing intersectional identities defined by life-course financial mobility combined with gender, and race and ethnicity. Verbal episodic memory was assessed using the Spanish and English Neuropsychological Assessment Scales over four waves from 2017to 2023. Adjusted mixed-effects linear regression models were estimated with and without fixed effects of gender, race and ethnicity, and financial mobility, to evaluate whether the random effects of the intersectional identity strata contributed variance to memory beyond individual fixed effects. Mean age was 73·6years (SD 8·1). Of 2340individuals, 1460 (62·4%) were women, 880 (37·6%) were men, 388 (16·6%) were Asian, 1136 (48·5%) were Black, 334 (14·3%) were Latinx, and 482 (20·6%) were White. Consistently low and downwardly mobile financial capital were strongly negatively associated with later-life memory at baseline (-0·162SD units [95% CI -0·273to -0·051] for consistently low and -0·171 [-0·250to -0·092] for downwardly mobile), but not rate of change over time. Intersectional identities contributed 0·2% of memory variance after accounting for the fixed effects of gender, race and ethnicity, and financial mobility. Consistently low and downward life-course financial mobility are associated with lower later-life memory function. Intersectional identities defined by financial mobility in addition to gender, and race and ethnicity, contribute negligible additional variance to later-life memory in this study setting. US National Institute on Aging, US National Institutes of Health.

Caribbean street vending experiences: Guyanese migrant women in Trinidad and Tobago

ABSTRACT This article offers a critical overview of how South-South migration operates in the Caribbean. It represents an intersectional feminist analysis of the experiences of Guyanese migrant women who work as street vendors in Trinidad and Tobago. Via the use of narrative inquiry, the study examines the daily challenges migrant women face as they interact with state officials, police officers, customers, and other vendors. We also provide a summary of the individual and collective tactics migrant women employ to navigate a context in which they are often stigmatised, marked as Other, and experience multiple barriers to be able to make a living. In doing so, the piece details how sexism, xenophobia and racism are mutually constituted and function in a Caribbean context, as well as how interlocking systems of oppression create barriers for migrant women to secure sustainable livelihood. We also illustrate the political agency of Guyanese migrant women by highlighting the ways they co-create safe spaces and build community despite obstacles. This article contributes to critical migration studies from the Global South/Majority World, fosters greater regional consciousness across the Caribbean, and underscores the importance of centring migrant women’s experiences in research and scholarship.

Navigating educational inequities in the USA: A statistical analysis of socio-economic and cultural barriers faced by young adults in formal education

Young adults in the USA face a multitude of challenges, particularly those from multi-disadvantaged backgrounds. This paper examines the socio-economic and cultural barriers impacting the educational experiences of young adults aged 18–29 within formal education settings in the USA. Utilising theoretical frameworks of life course research, intersectionality, and spatial justice, this study aims to provide a comprehensive understanding of the multifaceted barriers that hinder educational attainment. Drawing on data collected from surveys, interviews, and secondary sources, we employ robust statistical techniques, including regression and factor analysis, to identify and analyse key socio-economic barriers such as income, employment status, and parental education. Additionally, we explore cultural barriers, including language proficiency, ethnicity, and cultural capital, and conduct an intersectional analysis to uncover the compounded effects of these factors. Our findings reveal significant disparities in educational outcomes linked to socio-economic and cultural factors, highlighting the pervasive nature of educational inequities in the USA. The analysis indicates that young adults from lower socio-economic backgrounds and minority cultural groups face substantial obstacles in accessing and succeeding in formal education. These barriers are exacerbated by institutional and structural factors, emphasising the need for targeted policies and practices to support vulnerable populations.

Deep-learning-based natural fracture identification method through seismic multi-attribute data: a case study from the Bozi-Dabei area of the Kuqa Basin, China

Fractures play a crucial role in tight sandstone gas reservoirs with low permeability and low effective porosity. If open, they not only significantly increase the permeability of the reservoir but also serve as channels connecting the storage space. Among numerous fracture identification methods, seismic data provide unique advantages for fracture identification owing to the provision of three-dimensional information between wells. How to accurately identify the development of fractures in geological bodies between wells using seismic data is a major challenge. In this study, a tight sandstone gas reservoir in the Kuqa Basin (China) was used as an example for identifying reservoir fractures using deep-learning-based method. First, a feasibility analysis is necessary. Intersection analysis between the fracture density and seismic attributes (the characteristics of frequency, amplitude, phase, and other aspects of seismic signals) indicates that there is a correlation between the two when the fracture density exceeds a certain degree. The development of fractures is closely related to the lithology and structure, indirectly affecting differences in seismic attributes. This indicates that the use of seismic attributes for fracture identification is feasible and reasonable. Subsequently, the effective fracture density data obtained from imaging logging were used as label data, and the optimized seismic attribute near the well data were used as feature data to construct a fracture identification sample dataset. Based on a feed-forward neural network algorithm combined with natural fracture density and effectiveness control factor constraints, a trained identification model was obtained. The identification model was applied to seismic multi-attribute data for the entire work area. Finally, the accuracy of the results from the training, testing, and validation datasets were used to determine the effectiveness of the method. The relationship between the fracture identification results and the location of the fractures in the target reservoir was used to determine the reasonableness of the results. The results indicate that there is a certain relationship between multiple seismic attributes and fracture development, which can be established using deep learning models. Furthermore, the deep-learning-based seismic data fracture identification method can effectively identify fractures in the three-dimensional space of reservoirs.

MiR-542-5p targets GREM1 to affect the progression of renal fibrosis.

Renal fibrosis (RF) is a typical pathological presentation of end-stage chronic kidney disease (CKD) and autosomal dominant polycystic kidney disease (ADPKD). However, the precise regulatory mechanisms governing this re-expression process remain unclear. Differentially expressed microRNAs (miRNAs) associated with RF were screened by microarray analysis using the Gene Expression Omnibus (GEO) database. The miRNAs upstream of the genes in question were predicted using the miRWalk database. The miRNAs involved in the two GEO data sets were intersected to identify key miRNAs; their regulatory pathways were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Subsequently, the effects and the underlying mechanisms of target miRNA on RF were examined in a unilateral ureteral obstruction (UUO)-induced mice renal fibrotic model and a transforming growth factor-β1 (TGF-β1)-induced tubular epithelium (HK-2) fibrotic cell model. In total, 109 and 32 differentially expressed miRNAs were identified in the GSE133530 and GSE80247 data sets, respectively. GREM1 was identified as a hub gene, where its 2196 upstream miRNAs were predicted; miR-574-5p was found to be downregulated and closely related to fibrosis after data set intersection and enrichment analyses, thus was selected for further investigation. A differential expression heatmap (GSE162794) showed that miR-542-5p was downregulated. The expression of GREM1 mRNA was upregulated, whereas that of miR-542-5p was downregulated in UUO mice and fibrotic HK-2 cells as compared with the relevant controls. The binding site of miR-542-5p was predicted at the 3'UTR region of GREM1 and was confirmed by subsequent dual luciferase reporter gene assay. Western blot analysis showed that Gremlin-1 and Fibronectin were significantly upregulated after induction of TGF-β1; when miR-542-5p was overexpressed or GREM1 mRNA was interfered, the upregulations of Gremlin-1 and Fibronectin were significantly reduced. Our research demonstrates that miR-542-5p plays a critical role in the progression of RF, and thus may be a promising therapeutic target for CKD and ADPKD.

A multidimensional gender analysis of health technology self-efficacy among people with Parkinson’s disease

BackgroundDigital health technologies (DHT) enable self-tracking of bio-behavioral states and pharmacotherapy outcomes in various diseases. However, the role of gender, encompassing social roles, expectations, and relations, is often overlooked in their adoption and use. This study addresses this issue for persons with Parkinson’s disease (PD), where DHT hold promise for remote evaluations.MethodsWe conducted a cross-sectional survey study in the Netherlands, assessing the impact of gender identity, roles, and relations on health technology self-efficacy (HTSE) and attitude (HTA). An intersectional gender analysis was applied to explore how gender intersects with education, employment, disease duration, and severity in influencing HTSE and HTA.ResultsAmong 313 participants (40% women), no significant correlation was found between gender identity or relations and HTSE or HTA. However, individuals with an androgynous (non-binary) gender role orientation demonstrated better HTSE and HTA. The exploratory intersectional analysis suggested that sociodemographic and clinical factors might affect the influence of gender role orientations on HTSE and HTA, indicating complex and nuanced interactions.ConclusionThis study highlights the importance of investigating gender as a multidimensional variable in PD research on health technology adoption and use. Considering gender as a behavioral construct, such as through gender roles and norms, shows more significant associations with HTSE and HTA, although effect sized were generally small. The impact of gender dimensions on these outcomes can be compounded by intersecting social and disease-specific factors. Future studies should consider multiple gender dimensions and intersecting factors to fully understand their combined effects on technology uptake and use among people with PD.

Can everyone get interesting jobs? Estimating interest fit across gender, ethnicity, and education

AbstractAlthough research and policy efforts have attempted to “even the hiring playing field” and progress equal opportunities, systemic employment patterns based on gender and ethnicity remain prevalent. An unexplored avenue of diversity, equity, and inclusion efforts is the degree to which all people can obtain jobs that fit their interests. The present study used a large, diverse sample of over 250,000 American employees to estimate the average vocational interest fit that people have with their jobs and differences in fit across race/ethnicity, gender, and education. Overall, employees showed moderate positive vocational interest fit with their jobs, with an average profile correlation of .20 between person and job interests. There were small gender differences in vocational interest fit favoring men, especially White and Hispanic men, with minimal differences across other race/ethnicity groups. However, the largest group differences emerged for education, as employees with higher educational attainment showed greater vocational interest fit, particularly among women. Further intersectional analyses added greater nuance to these results, including how various groups achieve vocational interest fit across different types of jobs. Altogether, this work provides important fit benchmark estimates for researchers, counselors, organizational placement, and theory refinement.

Investigating the Nonlinear Effect of Land Use and Built Environment on Public Transportation Choice Using a Machine Learning Approach

Understanding the relationship between the demand for public transportation and land use is critical to promoting public-transportation-oriented urban development. Taking Beijing as an example, we took the Public Transportation Index (PTI) during the working day’s early peak hours as the dependent variable. And 15 land use and built environment variables were selected as the independent variables according to the “7D” built environment dimensions. According to the Modifiable Areal Unit Problem (MAUP), the size and shape of the spatial units will affect the aggregation results of the dependent variable and the independent variables. To find the ideal spatial unit division method, we assess how well the nonlinear model fits several spatial units. Extreme Gradient Boosting (XGBoost) was utilized to investigate the nonlinear effects of the built environment on PTI and threshold effects based on the ideal spatial unit. The results show that (1) the best spatial unit division method is based on traffic analysis zones (TAZs); (2) the top four explanatory variables affecting PTI are, in order: mean travel distance, residential density, subway station density, and public services density; (3) there are nonlinear relationships and significant threshold effects between the land use variables and PTI. The priority regeneration TAZs were identified according to the intersection analysis of the low PTI TAZs set and the PTI-sensitive TAZs set based on different land use variables. Prioritized urban regeneration TAZs require targeted strategies, and the results of the study may provide a scientific basis for proposing strategies to renew land use to increase PTI.

Methylation-related differentially expressed genes as potential prognostic biomarkers for cervical cancer

AimTo discover novel methylation-related differentially expressed genes (MRDEGs) for cervical cancer, with a focus on their potential for early diagnosis and prognostic assessment. Materials & methodsWe integrated data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. TCGA-MRDEGs were identified by analyzing differentially methylated genes (DMGs) and their correlation with gene expression. We examined GEO datasets GSE39001, GSE9750, and GSE46306 for GEO-MRDEGs. Overlapping MRDEGs were subjected to overall survival (OS) analysis to identify prognostic markers. The expression and methylation levels of these genes were validated in a total of 30 tissue samples, comprising 20 from cervical cancer patients and 10 from normal cervical tissues, using qRT-PCR and MassARRAY EpiTYPER Assay. ResultsA total of 314 TCGA-MRDEGs and 40 GEO-MRDEGs were identified. Intersection analysis yielded 10 overlapping MRDEGs. Notably, NOVA1, GSTM5, TRHDE, and CXCL12 were found to have reduced expression and increased methylation in cervical cancer, which correlated with poor prognosis. The methylation status and expression levels of these genes were confirmed in tissue specimens. ConclusionWe identified four MRDEGs as potential prognostic biomarkers for cervical cancer. Their clinical utility is highlighted, but further validation in larger cohorts is required to establish their clinical significance.

Identification of crosstalk genes and immune characteristics between Alzheimer's disease and atherosclerosis.

Advancements in modern medicine have extended human lifespan, but they have also led to an increase in age-related diseases such as Alzheimer's disease (AD) and atherosclerosis (AS). Growing research evidence indicates a close connection between these two conditions. We downloaded four gene expression datasets related to AD and AS from the Gene Expression Omnibus (GEO) database (GSE33000, GSE100927, GSE44770, and GSE43292) and performed differential gene expression (DEGs) analysis using the R package "limma". Through Weighted gene correlation network analysis (WGCNA), we selected the gene modules most relevant to the diseases and intersected them with the DEGs to identify crosstalk genes (CGs) between AD and AS. Subsequently, we conducted functional enrichment analysis of the CGs using DAVID. To screen for potential diagnostic genes, we applied the least absolute shrinkage and selection operator (LASSO) regression and constructed a logistic regression model for disease prediction. We established a protein-protein interaction (PPI) network using STRING (https://cn.string-db.org/) and Cytoscape and analyzed immune cell infiltration using the CIBERSORT algorithm. Additionally, NetworkAnalyst (http://www.networkanalyst.ca) was utilized for gene regulation and interaction analysis, and consensus clustering was employed to determine disease subtypes. All statistical analyses and visualizations were performed using various R packages, with a significance level set at p<0.05. Through intersection analysis of disease-associated gene modules identified by DEGs and WGCNA, we identified a total of 31 CGs co-existing between AD and AS, with their biological functions primarily associated with immune pathways. LASSO analysis helped us identify three genes (C1QA, MT1M, and RAMP1) as optimal diagnostic CGs for AD and AS. Based on this, we constructed predictive models for both diseases, whose accuracy was validated by external databases. By establishing a PPI network and employing four topological algorithms, we identified four hub genes (C1QB, CSF1R, TYROBP, and FCER1G) within the CGs, closely related to immune cell infiltration. NetworkAnalyst further revealed the regulatory networks of these hub genes. Finally, defining C1 and C2 subtypes for AD and AS respectively based on the expression profiles of CGs, we found the C2 subtype exhibited immune overactivation. This study utilized gene expression matrices and various algorithms to explore the potential links between AD and AS. The identification of CGs revealed interactions between these two diseases, with immune and inflammatory imbalances playing crucial roles in their onset and progression. We hope these findings will provide valuable insights for future research on AD and AS.

Exploring genetic associations in systemic lupus erythematosus through Mendelian randomization: implications for novel biomarkers and therapeutic targets.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by a significant health burden. There is an essential need for novel biomarkers and therapeutic targets to improve diagnosis and management. Mendelian randomization (MR) was applied to explore causal links between SLE and various biomarkers like immune cells, metabolites, and inflammatory cytokines using multiple databases. Initially, biomarkers significantly associated with SLE were identified. Bidirectional MR helped clarify these relationships, and a two-step mediation MR examined their effects on SLE risk. Intersection analysis was used to identify biomarkers with consistent effects across datasets. Four biomarkers were identified as having significant associations with SLE risk: 1-palmitoyl-2-arachidonoyl-GPI levels [odds ratio (OR), 1.379; 95% confidence interval (CI), 1.180 to 1.613; FDR, 0.046], IL-17A levels (OR, 2.197; 95% CI, 1.412 to 3.418; FDR, 0.044), N-acetyl-aspartyl-glutamate (NAAG) levels (OR, 0.882; 95% CI, 0.831 to 0.936; FDR, 0.030), and ribitol levels (OR, 0.743; 95% CI, 0.644 to 0.857; FDR, 0.012). Bidirectional MR showed an inverse effect of NAAG on IL-17A levels (OR, 0.978; 95% CI, 0.962 to 0.994; p = 0.006). Mediation analysis indicated that NAAG influenced SLE risk both directly (beta = - 0.108) and indirectly through IL-17A (beta = - 0.018), highlighting the potential mediating role of IL-17A. After expanding the significance criteria to p < 0.05, intersection analysis across multiple datasets revealed 29 biomarkers with consistent beta directions, including 19 potential risk factors (beta > 0) and 10 protective factors (beta < 0) for SLE. This research has revealed significant genetic associations with SLE and demonstrated that IL-17A mediates the relationship between NAAG levels and SLE risk, highlighting potential new targets for personalized therapeutic interventions. Key Points • This study employs MR to identify significant genetic associations between various biomarkers and SLE, providing novel insights into potential biomarkers and therapeutic targets. • Four key biomarkers were identified as significantly associated with SLE risk: 1-palmitoyl-2-arachidonoyl-GPI, IL-17A, N-acetyl-aspartyl-glutamate (NAAG), and ribitol. • The findings suggest that NAAG levels have a protective effect against SLE, partly mediated through IL-17A, indicating a complex interplay between these biomarkers in the pathogenesis of SLE. • Intersectional analysis across multiple datasets revealed 29 biomarkers with consistent effects on SLE risk, highlighting new directions for future research and potential personalized therapeutic strategies.

The new pattern for dual NOTCH pathway involving nuclear transcription and mitochondrial regulation supports therapeutic mechanism of 4-butyl benzophenone derivatives against SIRS

The systemic inflammatory response syndrome (SIRS) represents a self-amplifying cascade of inflammatory reactions and pathophysiological states triggered by infectious or non-infectious factors. The identification of disease targets and differential proteins in the liver (the unique and important immune organ) of SIRS mice treated with the lead compound D1 was conducted using the Genecards database and proteomic analysis, respectively. Subsequently, NOTCH1 was identified as the potential hub target via an intersection analysis between the aforementioned differentially expressed proteins and disease targets. Based on our previous research on the structure-activity relationship, we designed and synthesized a series of SIRS-related derivatives, wherein butyl, halogen, and ester groups were incorporated into benzophenone, aiming at exploring the anti-inflammatory protective action from the perspective of macrophage polarization. Notably, these derivatives exhibited a direct binding capability to the O-glucosylation site (SER496) or its vicinities (such as SER492, VAL485) of NOTCH1 using docking, SPR, DARTS, and CETSA techniques. Mechanistically, derivative D6 exerted anti-inflammatory effects via the dual NOTCH pathway. Firstly, it could inhibit NOTCH1 nuclear transcriptional activity, attenuate the interaction between NICD and RBPJK, concurrently suppress NF-κB and NLRP3 inflammasome (NLRP3, ASC, and cleaved CASP1) activation, and promote NICD (NOTCH1 active fragments) ubiquitination metabolism (the nuclear transcriptional pathway). Secondly, it might possess the ability to increase PGC1α level, subsequently, enhance ATP and MMP levels, mitigate ROS production, increase mitochondrial numbers, and ameliorate mitochondrial inflammatory damage (the mitochondrial pathway). Importantly, the activator Jagged1 could effectively reverse the aforementioned effects, while the inhibitor DAPT exhibited a synergistic effect, suggesting that the nuclear transcriptional regulation and mitochondrial regulation were both in a NOTCH1-dependent manner. Subsequently, it effectively alleviated the inflammatory response and preserved organ function as evidenced by up-regulating M2-type macrophage-related anti-inflammatory cytokines (IL10, TGFβ, CD206, and ARG1) and down-regulating M1-type macrophage-related pro-inflammatory cytokines (NO, IL6, IL18, iNOS, TNFα, CD86, and IL1β). In a word, derivative D6 modulated macrophage polarization and effectively mitigated SIRS by targeting inhibition of the dual NOTCH pathway.

Logging Identification Methods for Oil-Bearing Formations in the Chang 6 Tight Sandstone Reservoir in the Qingcheng Area, Ordos Basin

The Chang 6 sandstone reservoir of the Upper Triassic Yanchang Formation in the Ordos Basin is one of the tight-oil-rich intervals in the basin. Owing to the strong heterogeneity and complex lithology of the Chang 6 reservoir, lithology and fluid identification have become more challenging, hindering exploration and development. This study focused on the Chang 6 member in the Qingcheng area of the Ordos Basin to systematically analyze the lithology, physical properties, and oil-bearing properties of the Chang 6 reservoir. We adopted the method of normalized superposition of neutron and acoustic time-difference curves, the method of induced conductivity–porosity–density intersection analysis, the method of superposition of difference curves (Δφ), and the induced conductivity curve. Our results indicated that the method of normalized superposition of neutron and acoustic wave time-difference curves could quickly and effectively identify the lithologies of tight fine sandstone, silty mudstone, mudstone, and carbonaceous mudstone. The induced conductivity–porosity–density cross-plot could be used to effectively identify oil and water layers, wherein the conductivity of tight oil layers ranged from 18 to 28.1 mS/m, the density ranged from 2.42 to 2.56 g/cm3, the porosity was more than 9.5%, and the oil saturation was more than 65%. Based on the identification of tight fine sandstone using the dual-curve normalized superposition method, the oil layer thickness within the tight fine sandstone could be effectively identified using the superposition of difference curves (Δφ) and induced conductivity curves. Verified by oil-bearing reservoir data from the field test, the overall recognition accuracy of the plots exceeded 90%, effectively enabling the identification of reservoir lithology and fluid types and the determination of the actual thickness of oil layers. Our results provide a reference for predicting favorable areas in the study area and other tight reservoirs.