Tag: pubmed

Int J Epidemiol. 2026 Jun 24;55(4):dyag109. doi: 10.1093/ije/dyag109.

ABSTRACT

BACKGROUND: Colorectal cancer (CRC) screening programmes often use the faecal immunochemical test (FIT) to identify individuals for follow-up colonoscopy but evidence on its impact on CRC incidence remains limited. Using a regression discontinuity design (RDD), we investigated whether CRC screening affects CRC incidence among adults aged 71-75 years with FIT values close to the threshold-an age group not consistently included in screening programmes.

METHODS: Using registry data from 2014 to 2024, we compared CRC incidence among screening participants aged 71-75 years with FIT values just above versus just below the 100-ng/ml referral threshold, where only those above were offered colonoscopy. We included 2773 individuals with borderline FIT values (80-120 ng/ml). An RDD was used to estimate the effect of colonoscopy referral based on FIT on CRC incidence at values close to the threshold while mitigating healthy-user bias.

RESULTS: Over a median 8.4-year follow-up, 165 CRC cases were observed. As expected from the lead time, early incidence was higher in FIT-positive individuals offered colonoscopy but cumulative incidence later plateaued in this group while it continued to rise in FIT-negative individuals. After 10 years of follow-up, a reduction was seen between the groups from 12.1 to 6.6 cases per 1000 person-years, equivalent to 5.5 fewer cases (95% confidence interval: 1.44-9.56) per 1000 person-years, corresponding to a 45.5% reduction.

CONCLUSION: CRC screening reduces CRC incidence among adults aged 71-75 years with FIT values close to the FIT threshold. This could guide cancer screening policies for an age group that is only eligible for screening in some countries.

PMID:42470136 | DOI:10.1093/ije/dyag109

Int J Epidemiol. 2026 Jun 24;55(4):dyag114. doi: 10.1093/ije/dyag114.

ABSTRACT

BACKGROUND: It has been hypothesized that the incidence of cryptorchidism may have increased in Japan following the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident in March 2011; however, empirical evidence remains limited. This study aimed to assess the possible impact of the accident on cryptorchidism incidence over an extended period of time before and after the accident.

METHODS: Detailed information on all patients who underwent orchiopexy between April 2008 and March 2021 was obtained from the medical records of 86 hospitals in Fukushima Prefecture. Interrupted time series analyses were performed to evaluate the immediate post- versus pre-accident level change and the monthly post- versus pre-accident slope change in orchiopexy surgery rates and birth rates with cryptorchidism.

RESULTS: In total, 622 orchiopexy surgeries performed in Fukushima Prefecture during the study period were included. No significant increase was observed in the monthly orchiopexy surgery rate per 100 000 population in Fukushima Prefecture after the accident, in terms of either the immediate level change (incidence rate ratio [IRR], 1.21; 95% CI, 0.86-1.70) or the monthly slope change (IRR per month, 1.01; 95% CI, 0.99-1.04). The estimated monthly birth rate with cryptorchidism per 1000 live births in Fukushima Prefecture also showed no significant increase in either the immediate level change (IRR, 0.87; 95% CI, 0.52-1.44) or the monthly slope change (IRR per month, 1.01; 95% CI, 0.99-1.04).

CONCLUSIONS: Our study provided no evidence that the FDNPP accident increased the orchiopexy surgery rates or birth rates with cryptorchidism in Fukushima Prefecture.

PMID:42470134 | DOI:10.1093/ije/dyag114

Biostatistics. 2026 Jan 20;27(1):kxag021. doi: 10.1093/biostatistics/kxag021.

ABSTRACT

The three dimensional (3D) spatial organization of the genome is closely linked to biological functions and can be captured by Hi-C assays through interrogating genome-wide chromatin interactions. Methodologies for inferring 3D structures from Hi-C data summarized as a two-dimensional (2D) contact matrix can be broadly placed within the paradigms of optimization-based and sampling-based. Many optimization-based methods are capable of constructing whole genome 3D structures but do not account for spatial dependency in the 2D data matrix nor cell heterogeneity in bulk Hi-C data, which provide an average over millions of cells. Sampling-based methods, on the other hand, are probabilistic model-based and can account for not only dependency, heterogeneity, but also other features inherent in Hi-C data, such as over-dispersion and sparsity. However, whole-genome 3D structure recapitulation is too computationally expensive for sampling-based methods, while chromosome-by-chromosome strategies for sampling-based methods ignore important information on inter-chromosomal contacts. To address these issues, we propose the truncated Random effect EXpression-cut and paste (tREX-cap) method, which applies the tREX model within a divide and conquer strategy. The resulting method inherits the good data-feature-cognizant properties of tREX and, in the meantime, can efficiently infer the whole genome 3D structure. We demonstrate the performance of tREX-cap through an extensive simulation study and analyses of a Hi-C lymphoblastoid dataset and a Hi-C IMR90 dataset.

PMID:42470130 | DOI:10.1093/biostatistics/kxag021

Biostatistics. 2026 Jan 20;27(1):kxag015. doi: 10.1093/biostatistics/kxag015.

ABSTRACT

Serum prostate-specific antigen (PSA) is widely used for prostate cancer screening. While the genetics of PSA levels have been studied to enhance screening accuracy, the genetic basis of PSA velocity, the rate of PSA change over time, remains unclear. The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, a large, randomized study with longitudinal PSA data (15,260 cancer-free males, averaging 5.34 samples per subject) and genome-wide genotype data, provides a unique opportunity to estimate PSA velocity heritability. We developed a mixed model to jointly estimate the heritability of PSA levels at age 54 and PSA velocity. To accommodate the large dataset, we implemented 2 efficient computational approaches: a partitioning and meta-analysis strategy using average information restricted maximum likelihood (AI-REML) and a fast restricted Haseman-Elston (REHE) regression method. Simulations showed that both methods yield unbiased estimates of both heritability metrics, with AI-REML providing smaller variability in the estimation of velocity heritability than REHE. Applying AI-REML to PLCO data, we estimated heritability at 0.32 (s.e. = 0.07) for baseline PSA and 0.45 (s.e. = 0.18) for PSA velocity. These findings reveal a substantial genetic contribution to PSA velocity, supporting future genome-wide studies to identify variants affecting PSA dynamics and improve PSA-based screening.

PMID:42470129 | DOI:10.1093/biostatistics/kxag015

Biostatistics. 2026 Jan 20;27(1):kxag024. doi: 10.1093/biostatistics/kxag024.

ABSTRACT

Understanding the pathways through which diet affects human metabolism is a central task in nutritional epidemiology. This article proposes novel methodology to identify food items associated with blood metabolites in 2 cohorts of healthcare professionals. We analyze 244 metabolites characterized by statistical complexities that include skewness, left-censoring, and structural missingness. Though existing methods can address such factors in low-dimensional settings, they cannot exploit the nutritional or statistical relationships among the 30 considered food intake variables, and they are unsuitable for performing high-dimensional inference. To address these challenges, we develop a novel Bayesian variable selection framework for metabolite response variables based on a skew-normal censored mixture model, while exploiting substantive information on the considered food items via a Markov random field prior. Applying this methodology to the cohort data identifies multiple metabolite-diet associations that are consistent with previous research as well as several potentially novel associations that were not detected using standard methods. The proposed approach is implemented in the R package multimetab, facilitating its use in high-dimensional metabolomic analyses.

PMID:42470128 | DOI:10.1093/biostatistics/kxag024

Prep Biochem Biotechnol. 2026 Jul 17:1-16. doi: 10.1080/10826068.2026.2703129. Online ahead of print.

ABSTRACT

Lactococcus lactis SH6 was engineered for heterologous heparosan production, and its growth medium was optimized using a combination of experimental design and machine learning (ML). One-factor-at-a-time shake flask experiments revealed glucose (10 g/L) and yeast extract (17.5 g/L) as the best substrates, producing 50 mg/L heparosan. Plackett-Burman analysis and steepest ascent optimization revealed significant factors, and a central composite design (CCD) optimized nutrient concentrations, predicting 85 mg/L heparosan (validated at 81 mg/L). ML-Gaussian process regression was applied after CCD optimization to fine-tune and cross-check the optimal medium (glucose 8.94 g/L, yeast extract 22.89 g/L, ascorbate 0.38 g/L, β-glycerophosphate 28.2 g/L), producing 85.28 mg/L heparosan (predicted 88.8 mg/L) at the flask scale. Earlier nisin induction (2 h) at the bioreactor scale increased heparosan titers to 119.7 mg/L, and linear glucose feeding (1.5 g/L.h) extended the production phase to 133 mg/L. Medium optimization resulted in nearly doubling heparosan yield compared to the unoptimized medium, setting a new standard for L. lactis. This work offers a design-of-experiments-ML solution as a viable approach to designing high-yielding, animal-product-free heparosan production methods in a Generally Regarded as Safe (GRAS) microbe.

PMID:42470116 | DOI:10.1080/10826068.2026.2703129

Brain. 2026 Jul 18:awag246. doi: 10.1093/brain/awag246. Online ahead of print.

ABSTRACT

Strong evidence supports the role of low-grade systemic inflammation in neurodegeneration, including cognitive decline. Given the literature documenting chronic persistent inflammation in older Black adults, we investigated the association between circulating inflammatory proteins and cognitive decline in this high-risk population. We used data (n = 642) from the Minority Aging Research Study (MARS) and the Rush Clinical Core, including plasma samples to assess circulating inflammatory proteins (Olink® Target-96 Inflammation) and cognition (global cognition and five cognitive domains) assessed annually following proteomics measurement using previously stored blood samples. Linear mixed-effect and latent class mixed models (age at blood draw for proteomics measurement, sex, and education-adjusted), and elastic-net regression were used. Statistical significance was determined using an FDR threshold of 10%. Participants (62.3 to 99.4 years) were mostly women (80.68%) with 15.1 years of education. In multivariable linear mixed-effect models, we found that higher levels of osteoprotegerin (OPG) and chemokine (C-C motif) ligand 23 (CCL23) were cross-sectionally associated with poorer global cognition (beta=-0.205 and beta=-0.148), and higher CCL23 was associated with poorer semantic memory (beta=-0.206). Furthermore, protein × time interaction analyses indicated that higher OPG, Stem cell factor (SCF), and chemokine (C-X-C motif) ligand 9 (CXCL9) levels were associated with faster decline in global cognition (OPG × time term: beta=-0.042), semantic memory (SCF × time term: beta=-0.059, OPG × time term: beta=-0.043), episodic memory (SCF × time term: beta=-0.064; OPG × time term: beta=-0.044), and visuospatial ability (CXCL9×time term: beta=-0.012). In latent class mixed models, several significant protein × time interactions were observed for episodic memory in the subgroup with initial below-average performance and gradual decline. Using elastic net regression, we identified signatures of global cognitive level (26 proteins), but the prediction of cognitive decline was poor. In older Black adults, circulating inflammatory proteins were linked to cognition, reinforcing the role of systemic inflammation as a potential driver of neurodegeneration in this population.

PMID:42470112 | DOI:10.1093/brain/awag246

Gut Microbes. 2026 Dec 31;18(1):2691347. doi: 10.1080/19490976.2026.2691347. Epub 2026 Jul 17.

ABSTRACT

Although opioids are effective analgesics, they can lead to problematic drug use behaviors that underlie opioid use disorder (OUD). Opioids also cause gut microbiota dysbiosis, which is linked to altered opioid responses. We used a longitudinal paradigm of voluntary oral morphine self-administration to capture multiple facets of drug seeking and preserve both individual behavioral responses and individual gut microbiota variation to investigate the role of the gut microbiota in a mouse model of OUD. Although all the mice consumed morphine, only a subset of the mice that transitioned to a state we defined statistically as compulsive. In compulsive mice, morphine constricted natural variability and fragmented the microbiota community networks, which convergently reorganized to form robust novel connections post-morphine. In contrast, the more variable communities of non-compulsive mice were highly interconnected during morphine disturbance and displayed more continuity post-morphine, suggesting greater flexibility and adaptability. Compulsive mice displayed a greater loss of functional diversity and a shift in favor of potential pathobionts, whereas non-compulsive mice better preserved genera associated with gut health and broader functional diversity. These findings highlight the potential role of persistent and stable opioid-induced microbiota dysbiosis in long-term behavioral changes underlying OUD and contributing to vulnerability to relapse.

PMID:42470107 | DOI:10.1080/19490976.2026.2691347

BMC Psychol. 2026 Jul 17. doi: 10.1186/s40359-026-05195-w. Online ahead of print.

ABSTRACT

Physical activity (PA) in children is affected by physical and psychological factors. Exploring its characteristics and determinants is critical to promoting children’s PA participation. Existing empirical evidence is largely drawn from Western cultural contexts, and cultural divergences create uncertainty regarding whether these established associations generalize to Chinese children. Therefore, this study aimed to investigate the relationships motor skill competence (MSC), motivation, and PA among Chinese children. Participants were 177 fourth to six-grade students (76 boys vs. 101 girls; mean age = 10.94 years old; SD = 0.79) at two elementary school students from the province of Hunan in China. The students’ MSC, motivation and PA were measured using the Test of Gross Motor Development-Third Edition (TGMD-3), the Perceived Locus of Causality scale, and the PA Questionnaire for Older Children respectively. Data were analyzed with descriptive statistics, independent sample t-tests, Pearson’s correlation and linear regression models. Boys scored significantly higher than girls on ball skills and PA. Pearson’s correlation revealed that children’s autonomous motivation and controlled motivation were positively related to PA (r = 0.313, ρ < 0.01; r = 0.259, ρ < 0.05). Children’s MSC were not associated with motivation (ρ > 0.05). The result of linear regression models showed that MSC, autonomous motivation and controlled motivation were significantly associated with PA (F (3, 171) = 10.565, ρ < 0.01). Chinese children’s MSC was not associated with motivaiton. Physical education teachers should target the enhancement of both MSC and motivation as it is an effective strategy for promoting higher levels of PA among children.

PMID:42469925 | DOI:10.1186/s40359-026-05195-w

Trials. 2026 Jul 17. doi: 10.1186/s13063-026-09900-3. Online ahead of print.

ABSTRACT

BACKGROUND: Effective prediction and monitoring of recruitment in randomised controlled trials (RCTs) is critical to ensuring the target sample size is met, with 37% of trials failing to do so. This research aimed to identify various statistical methods for predicting recruitment during the design stage of an RCT and implement them using case-study trials, with a view to determining which method is more appropriate.

METHODS: Various deterministic, Poisson and Bayesian methods were identified and applied to data from six previously conducted RCTs, with varying numbers of participants recruited, sites opened, durations and recruitment outcomes.

RESULTS: Poisson methods were found to be more appropriate for obtaining predictions at the design stage of a trial. They produced confidence intervals to model uncertainty, unlike deterministic methods, and exhibited narrower intervals than Bayesian methods using informative priors. For single-centre trials, a homogeneous Poisson process was recommended, whilst a Non-homogeneous Poisson Process could be more suitable for multicentre trials. However, the non-homogeneous approach yielded more conservative estimates and required site-specific start dates, which may be less readily available at the design stage. Limitations included a lack of usable software for method implementation, difficulties with parameter elicitation, and a lack of additional data required to implement more complex methods, all of which may hinder the application of statistical methods for predicting recruitment which occurs in only 10% of RCTs.

CONCLUSIONS: To enhance transparency and reproducibility, it is recommended that RCTs publish the methods and parameters used in recruitment predictions. This may improve their accuracy, thereby reducing the cost and minimising the research waste associated with insufficient recruitment. Further research across a wider range of trials and methods may also be required due to the complexity of factors which influence recruitment and the variability in the accuracy of statistical methods across trials.

PMID:42469922 | DOI:10.1186/s13063-026-09900-3