Cannabis use among adolescents is an increasing public health concern, particularly in the context of the digital era, where social and behavioral influences are rapidly evolving. However, the mechanisms linking social media exposure to cannabis use remain unclear. This study investigates the association between social media use and cannabis use in late adolescence, examining the mediating roles of behavioral problems using an instrumental variable (IV) approach to address endogeneity. We analyzed data from 1766 participants in the Longitudinal Study of Australian Children (aged 18-19years at Wave 8) using a control-function approach, with mobile phone ownership with home internet access as instrumental variables for social media use. We evaluated adolescent cannabis use using self-reported lifetime cannabis use from longitudinal surveys of children aged 18-19years at Wave 8. Generalized structural equation modeling (GSEM) was applied in the second stage to estimate IV-based direct, indirect, and total effects through behavioral problems, with bias-corrected bootstrapped confidence intervals. By late adolescence, 34.6% reported cannabis use. Instrumental mediation analysis showed instrument-induced frequent social media use was associated with nearly threefold higher odds of cannabis use (OR=2.85; 95% CI: 1.99-4.10). Externalizing behaviors significantly mediated this IV-based relationship, accounting for a 22% increase in cannabis use odds via this pathway (OR=1.22; 95% CI: 1.10-1.37). Internalizing behaviors did not mediate the association. The total IV based indirect effect through behavioral problems was significant (OR=1.20; 95% CI: 1.07-1.36), confirming behavioral problems as key mechanisms linking social media use and cannabis use. IV-based frequent social media use is robustly associated with increased cannabis use in adolescents, primarily through elevated externalizing behaviors. These findings highlighted the need for integrated digital and behavioral interventions targeting externalizing symptoms to mitigate substance use risk in the digital era. Enhanced parental engagement and digital literacy may further buffer against adverse outcomes associated with social media exposure.

This paper concerns a particular property of the basic instrumental variable (IV) estimator that is useful for multiple-input multiple-output (MIMO) modeling problems where it is not obvious how to partition the available signals between the sets of inputs and outputs. In general, a repartitioning of the input and output signals will result in a different model compared to the original input–output choice. It is important to distinguish cases where a repartitioning results in an algebraically equivalent model and cases where the resulting model transformation is more complex and depends also on particular system and signal properties. The latter situation typically occurs when models are estimated from data. We here show that the basic IV estimator is an exception since it provides algebraically equivalent estimates regardless of true system structure, noise properties, or amount of data. This equivalence result is illustrated in two simulation examples.

From siblings to skills: How does sibling structure shape children's academic achievement and non-cognitive development in rural Northwest China?

Government ownership and stock price crash risk in banks: International evidence

Osteoprotegerin is associated with reduced risk of abdominal aortic aneurysm and the role of vascular calcification: insights from Mendelian randomization approach.

Highly emitting red-CDs for extreme acidic pH monitoring, and multi-mode ratiometric detection of Ag.

The causal relationship between sarcopenia traits and abdominal hernia: A bidirectional Mendelian randomization study.

A growing body of evidence links microRNAs (miRNAs) to major depressive disorder (MDD). However, the causal nature of these associations remains unclear. This study aimed to investigate the potential causal association between miRNAs and MDD by combining Mendelian Randomization (MR) analyses and experimental validation. Single-nucleotide polymorphisms (SNPs) significantly associated with the expression levels of miRNAs identified in the Framingham Heart Study (FHS) were used as instrumental variables serving as a proxy for miRNA exposure. The outcome was derived from the genome-wide association study (GWAS) of MDD (cases=170,756, controls=329,443). Two-sample MR was conducted to assess the association of miRNAs with MDD. The miRNAs identified from MR analyses were further validated in blood samples from individuals in the Women's Health in Lund Area (WHILA) cohort using qPCR. MR analysis identified six miRNAs significantly associated with MDD risk, including miR-133a-3p [Odds Ratio (OR)=1.03, 95% Confidence interval (CI):1.00-1.05], miR-130a-3p (OR=1.06, 95% CI:1.03-1.09), miR-138-5p (OR=1.06, 95% CI:1.01-1.11), miR-629-5p (OR=0.96, 95% CI:0.93-0.99), miR-132-3p (OR=0.97, 95% CI:0.94-1.00) and miR-635-3p (OR=0.97, 95% CI:0.95-0.99). Among them, miR-130a-3p (OR=2.06, 95% CI:1.08-4.28, P=0.04) and miR-132-3p (OR=0.51, 95% CI:0.29-0.88, P=0.02) were further confirmed to be associated with MDD by experimental validation. Combining genetic and experimental approaches, this study provides evidence supporting a potential causal role for specific circulating miRNAs in MDD. While the MR findings were limited by single-SNP instruments, precluding formal pleiotropy assessment, the experimental validation of miR-130a-3p and miR-132-3p strengthens the evidence. Further research with multi-SNP instruments and larger cohorts are needed to confirm causality and explore clinical relevance.

The impact of artificial intelligence and group effects on supply chain resilience in enterprises

Tissue-specific gene expression is critical in complex disease etiology, but traditional transcriptome-wide Mendelian Randomization (TWMR) often overlooks tissue heterogeneity and is constrained by limited valid instrumental variables (IVs) per tissue. We propose Multi-Tissue TWMR (MT-TWMR), which selects cis-eQTLs with consistent effects across tissues as IVs and estimates tissue-specific causal effects via a penalized regression model combining L1 regularization for sparsity with a weighted tissue-difference penalty based on tissue similarity to enable cross-tissue information sharing. Simulations under varying IV numbers, pleiotropy levels, and tissue counts showed MT-TWMR consistently achieved higher power, lower root mean square error, and better type I error control than existing univariate and multivariable MR methods, particularly when IVs were scarce. Applied to major depressive disorder and primary hypertension, MT-TWMR identified 28 and 57 causal genes respectively, with enriched signals in biologically relevant tissues and strong colocalization and pathway evidence. MT-TWMR offers an effective and interpretable framework for integrating multi-tissue eQTL data to construct tissue-specific disease gene maps.

Patient selection remains a major challenge in evaluating hospital performance. We exploit the quasi-random assignment of patients to hospitals, based on a rotation schedule between hospitals in the Upper Austrian capital of Linz. In an instrumental variable (IV) framework, we use high-quality administrative data and estimate hospital performance with respect to in-hospital mortality, 30-day mortality, and 30-day readmission. We contrast these results with those of traditional risk adjustment models based on patient observables. We find that the assessment of hospital performance is sensitive to the inclusion of patient observables and that increasing the number of socio-economic covariates to better control for patient risk profiles does not always help bring risk-adjusted estimates closer to IV estimates. The divergence between methods is most pronounced for readmissions, where risk-adjustment models imply large and statistically significant differences between hospitals, whereas IV estimates are substantially smaller and not statistically significant. Our results suggest that common risk adjustment does not adequately control for patient differences between hospitals and that hospital quality indicators based on common administrative data should be interpreted with caution. The trend toward personalized medicine may support the process of collecting more clinical information at the individual level, thus allowing for better quality comparisons between hospitals.

The rapid expansion of healthcare infrastructure may exert increasing pressure on the sustainability of social health insurance. China's concurrent pursuit of universal coverage, coupled with extensive hospital construction, offers a valuable context for examining whether the patterns observed in China align with Roemer's Law (1961), which is often summarized as 'a hospital bed built is a bed filled' within an insured population. This study investigates the relationship between hospital bed density and insurance expenditure to deepen our understanding of the factors associated with the growth of healthcare costs. We compiled a panel dataset encompassing 31 Chinese provinces covering the period from 2011 to 2024. To strengthen identification and address potential endogeneity concerns, we employed two-way fixed effects models alongside instrumental variable (IV-2SLS) estimation. Mediation analysis was employed to investigate potential pathways, while panel threshold regression was utilized to examine nonlinear patterns in the relationship between supply and expenditure. The baseline estimates indicated a positive association, suggesting that higher provincial bed density correlates with increased province-level insurance spending. Mediation analysis revealed that the Average Length of Stay may serve as a potential aggregate pathway, accounting for 17.8% of the estimated relationship. Furthermore, threshold regression analysis indicated a possible nonlinear pattern, with an estimated threshold of 7.271 beds per 1,000 population. Below this threshold, hospital bed density is positively related to insurance spending (β = 0.217); however, above this threshold, the association loses statistical significance. Regional analysis demonstrated that the positive association was most pronounced in the western region, while no statistically significant association was observed in the northeastern region. Our findings support a conditional, province-level interpretation of Roemer's Law within the Chinese context, indicating that the association between bed density and insurance expenditure varies across institutional and capacity settings. Specifically, higher provincial bed density is more strongly associated with a longer average length of stay at the provincial level than with increased admission volumes. Beyond the exploratory threshold estimate, the marginal association between additional bed supply and insurance expenditure appears to weaken. These results suggest that payment reform, length-of-stay management, and regulatory oversight should be prioritized alongside careful capacity planning.

Studies have shown that an increase in the abundance of triglycerides (TG), oleic acid, and stearic acid can exacerbate the symptoms of psoriasis. Based on this, the present study aimed to employ Mendelian randomization (MR) methods to investigate the causal relationship between fatty acid (FA) and TG levels and the risk of psoriasis. A 2-sample MR analysis was performed using summary statistics from the genome-wide association studies of FA, TG, and psoriasis of European ancestry. Single nucleotide polymorphisms were used as instrumental variables in MR analysis. Inverse variance weighted was used as a primary method to study the causal relationship of FA on psoriasis. Similarly, inverse variance weighted was used to test for the causal effect of TG on psoriasis as well as the causal effect of FA on TG. Finally, sensitivity analysis was used to test the reliability of the MR analysis results. In this study, no significant association was observed between FA and psoriasis, indicating that FA was not a causal factor for psoriasis. TG had a causal relationship with psoriasis, and it was a risk factor for psoriasis. In MR analysis, it was demonstrated that FA did not directly exacerbate psoriasis; TG was a risk factor for psoriasis exacerbation. Our study elucidates the relationship between TG and FAs in psoriasis pathogenesis, thereby refining the understanding of its underlying mechanisms and offering novel theoretical and therapeutic avenues for diagnosis and treatment .

The causal relationship between instant coffee consumption and carpal tunnel syndrome (CTS) remains unclear. This study aimed to investigate the potential causal association between instant coffee consumption and CTS using data from large-scale genome-wide association studies, thereby providing genetic epidemiological evidence on this association. This study selected single nucleotide polymorphisms strongly associated with instant coffee consumption as instrumental variables. A 2-sample Mendelian randomization (MR) design was used. Three MR analysis methods were used: inverse variance weighted, MR-Egger regression, and weighted median to assess potential causal relationships. Cochran’s Q test was used to evaluate heterogeneity in the data. Summary statistics were derived from 1,80,764 individuals for instant coffee consumption and 4,80,201 individuals for CTS, all of European ancestry, to minimize bias from population stratification. Sensitivity analyses were performed using the leave-one-out method to validate the robustness of the results. The inverse variance weighted results showed that the odds ratio of CTS with respect to instant coffee consumption was 3.41 (95% confidence interval: 1.65–7.04, P = .0009), suggesting a significant positive causal relationship between instant coffee consumption and CTS. Sensitivity analyses did not reveal significant heterogeneity and horizontal pleiotropy (P > .05). This study suggested a potential positive causal association between instant coffee consumption and CTS using the 2-sample MR approach, although the findings should be considered preliminary and hypothesis-generating.

The association between apolipoprotein and chronic obstructive pulmonary disease (COPD) has been reported in observational studies. However, the causality of apolipoprotein on COPD remains unknown. A 2-sample Mendelian randomization (MR) analysis was performed to investigate the causal association of apolipoprotein with COPD using summary-level data. Genome-wide association studies of two apolipoproteins, apolipoprotein A-1 (ApoA-I) and apolipoprotein B, were selected as instrumental variables. COPD was included as the outcome. A significant association between ApoA-I and COPD risk was found using the inverse-variance weighted (IVW) method (odds ratio [OR]: 0.993, 95% confidence interval [CI]: 0.990–0.997, P = .0003). However, contrasting results were observed using the weighted median (OR: 0.995, 95% CI: 0.989–1.001, P = .119) and MR-Egger (OR: 0.992, 95% CI: 0.986–0.998, P = .015) methods. Since both pleiotropy and heterogeneity tests were negative (intercept = 6.032e-06, P = .948; Q = 98.996, Q-value = 0.696), and after MR-PRESSO correction, the IVW estimates can be considered acceptable. After adjusting for confounding factors, the genetic predisposition to higher levels of ApoA-I (OR = 0.993, 95% CI: 0.990–0.997, IVW P value = 0.0003) is causally associated with a reduced risk of COPD. No causal effect was found between apolipoprotein B and COPD.

Herpes zoster (HZ) and postherpetic neuralgia (PHN) are more common in immunocompromised individuals. This study aimed to explore potential associations between chronic diseases and HZ and PHN using a 2-sample Mendelian randomization (MR) approach. Genome-wide significant (P < 5 × 10-8) and independent (r2 <0.001) single-nucleotide polymorphisms (SNPs) from published genome-wide association studies consortia were selected as instrumental variables. Exposure SNPs were obtained from MRC-IEU and FinnGen databases, including obesity (N = 13,848), type 2 diabetes (N = 298,957), and ischemic stroke (N = 484,121). Outcome data for HZ (2080 cases/213,936 controls) and PHN (144 cases/195,191 controls) were obtained from FinnGen. SNPs were assessed for strength, horizontal pleiotropy, and heterogeneity. MR results were primarily based on inverse-variance weighted (IVW) analysis and expressed as odds ratios (ORs) with 95% confidence intervals. Genetically predicted ischemic stroke (IVW: OR = 1.420 [95% CI: 1.044–1.933], P = .0256, false discovery rate (FDR)-corrected P = .0312) increased the risk of HZ. Similarly, obesity (IVW: OR = 1.851 [95% CI: 1.058–3.239], P = .0311, FDR-corrected P = .0375) and type 2 diabetes (IVW: OR = 1.685 [95% CI: 1.023–2.775], P = .0404, FDR-corrected P = .0493) were associated with an increased risk of PHN. No significant associations were observed for other chronic diseases, such as hypertension with HZ (OR = 0.82, 95% CI: 0.47–1.44) and rheumatoid arthritis with PHN (OR = 0.87, 95% CI: 0.71–1.08). This study suggests potential associations between ischemic stroke and HZ, as well as obesity/type 2 diabetes and PHN. However, these findings should be interpreted with caution, given the limited statistical power, potential outcome misclassification, and small sample size for PHN analysis.

Purpose To evaluate the per-protocol effect of early mobilization on in-hospital adverse events among patients with acute stroke who had premorbid disability, using a target trial emulation framework. Methods This retrospective observational study conducted at a single center in Japan included patients with acute stroke, all of whom had a premorbid disability. Early mobilization was defined as mobilization within 2 days of hospital admission. The primary outcome was the occurrence of any adverse event―such as death or neurological or non-neurological adverse events—between day 4 and day 30 following admission. Sunday to Thursday admission was used as an instrumental variable (IV) to estimate the causal effect of early mobilization, based on reduced rehabilitation staffing on weekends. A two-stage least squares regression model was applied, adjusting for relevant clinical covariates. Results Among 165 patients, 58% received early mobilization. Admission from Sunday to Thursday increased the probability of early mobilization by a mean of 0.53 points (F-statistic = 44.79). IV analysis indicated that early mobilization reduced the probability of adverse events by 28 percentage points (absolute risk difference) [95% confidence interval: −55 to −2 percentage points]. Conclusion Early mobilization appeared to reduce adverse events in patients with acute stroke and premorbid disability.

Osteoporosis is a systemic skeletal disease characterized by decreased bone mass and microstructural destruction of bone tissue, leading to fragile bones and susceptibility to fractures, significantly affecting the quality of life of patients and increasing the socioeconomic burden. The aim of this study was to investigate the independence of quantitative ultrasound (QUS) of the heel bone in the prediction of osteoporosis and associated fractures, especially its relationship with bone mineral density (BMD). We used Mendelian randomization to analyze the causal relationship between QUS and BMD, osteoporosis and fracture risk by using genetic variants as instrumental variables. The results showed a significant correlation (P < .01) between heel QUS metrics and BMD, suggesting that QUS is not independent of BMD in assessing osteoporosis risk. Therefore, the value of QUS needs to be used in conjunction with BMD results in fracture risk assessment. The use of a Mendelian randomization design enhances the inference of causality and avoids bias in traditional observational studies. Therefore, this study employs bibliometric methodology to further supplement existing research on the relationship between QUS measurements of the calcaneus and BMD. In summary, this study emphasizes the importance of integrating BMD in clinical applications and calls for replication of the study in larger samples to further explore the relationship between QUS and BMD in order to improve screening and management strategies for osteoporosis.

Immune-related inflammation is linked to preeclampsia (PE), but immune cell–PE associations remain inconsistent. This study used two-sample Mendelian randomization (MR) to explore causal links between immune cell profiles and PE, informing clinical research and interventions. Genome-wide association study data included 731 immune cell phenotypes (3757 Europeans) and PE (2355 cases/264,887 controls, European descent). Single nucleotide polymorphisms were selected as instrumental variables (IVs) after quality control. Multiple MR methods (inverse variance weighted, weighted median estimator, weighted mode, and MR-Egger) and sensitivity analyses (heterogeneity, leave-one-out, and pleiotropy) were applied; false discovery rate (FDR) correction adjusted for multiple comparisons. Bidirectional MR explored reverse causality. After FDR correction (P_FDR < 0.20), 6 immunophenotypes showed significant causal associations with PE: 3 protective (CD62L−CD86+ myeloid dendritic cell [DC], CD62L− myeloid DC, granulocyte SSC-A levels) and 3 risk-increasing (CD16 on CD14+CD16+ monocytes, human leukocyte antigens DR+ natural killer cells, programmed death-ligand 1 on CD14−CD16+ monocytes). No horizontal pleiotropy was detected, and results were robust. Reverse MR identified 18 suggestive immunophenotypes (P < 5 × 10−6) potentially affected by PE (predominantly B cells) but no reverse causality for the 6 key phenotypes. Six immune cell phenotypes have causal links to PE, highlighting monocytes, myeloid DCs, natural killer cells, and granulocytes in PE pathogenesis. These findings offer potential immune biomarkers and therapeutic targets, emphasizing the need for translational research to validate clinical utility.

The aim of this study was to use Mendelian randomization (MR) method to deeply explore the possible causal association between depression and rotator cuff injury. Using pooled data from genome-wide association studies covering large-scale populations, independent genetic loci associated with depression and rotator cuff injuries and showing significant genetic associations in populations of European ancestry were carefully selected as study instrumental variables. The potential causal effect of depression on rotator cuff injury was systematically assessed by implementing 3 MR analysis strategies: MR-Egger regression, weighted median, and inverse variance weighting. Heterogeneity and multiplicity tests were further incorporated into the study, supplemented by a “leave-one-out” sensitivity analysis to ensure the reliability and robustness of the results. The combined results of this inverse variance weighting analysis (OR 0.72, 95% confidence interval = 0.41 to 1.27, P-value = .259) indicated that there was no significant causal association between depression and rotator cuff injury. In addition, no significant heterogeneity or pleiotropy was detected by a comprehensive test, and further sensitivity analyses confirmed the stability of the findings. Using 2-sample MR analysis, the present study provided an in-depth analysis of the genetic data, revealing a lack of clear causal evidence between depression and rotator cuff injury. Given the limitations of the current data, future studies should consider the inclusion of larger samples with the aim of exploring potential causal links with greater precision.