Tag: pubmed

Integr Psychol Behav Sci. 2025 Dec 1;59(4):89. doi: 10.1007/s12124-025-09944-1.

ABSTRACT

In this chapter, I draw inspiration from American psychologist Jim Lamiell to explore the original meanings of the terms “idiographic” and “nomothetic” as conceptualized by Wilhelm Windelband in 1894. Windelband critiqued the traditional division between natural and human sciences, proposing instead a new classification system that distinguishes scientific inquiries into idiographic and nomothetic fields. According to Windelband, scientific endeavors should be categorized based on the researcher’s goals: if the aim is to discover general, invariant laws governing physical and mental phenomena, the approach is nomothetic. In contrast, if the goal is to understand the uniqueness and depth of individual experiences, literature, or national moods-among other psychophysically neutral phenomena-the research is idiographic. This chapter demonstrates that historically, idiographic and nomothetic research were intended to complement and enrich each other. In the latter part of the paper, I contrast Windelband’s historical interpretation with modern views that often equate quantitative, statistical research (generalizations from samples to populations) with nomothetic research and single-case qualitative research with idiographic. I argue that this modern interpretation diverges from Windelband’s original concepts and suggest, in line with Lamiell, that population generalization may be more sensitive to cultural and historical contexts, thus aligning more closely with idiographic research than commonly assumed. Building on this analysis, I introduce the concept of synthography as a novel methodological framework aimed at integrating nomothetic and idiographic perspectives into a more comprehensive and culturally grounded approach to psychological inquiry.

PMID:41324849 | DOI:10.1007/s12124-025-09944-1

Mol Neurobiol. 2025 Dec 1;63(1):230. doi: 10.1007/s12035-025-05469-1.

ABSTRACT

Schizophrenia (SCZ) is a complex polygenic disorder influenced by genetic, epigenetic, and environmental factors. While numerous risk loci disease-associated methylation variants have been identified, their functional impact and contribution to disease risk remain largely unclear. This study addresses a fundamental yet underexplored question: how do non-coding allele-specific methylation (ASM) sites influence disease risk via gene regulation? We employed the Mendelian randomization (MR) method to integrate ASM data from monozygotic twins discordant for psychiatric disorders with brain eQTL and GWAS summary statistics to identify potential risk genes. The regulatory of the rs2280906 locus was investigated using dual-luciferase reporter assays, gene expression quantification, gene editing, methylation editing, and electrophoretic mobility shift assays. We used MR to prioritize these ASM locus associated with schizophrenia risk and demonstrated that the affected genes are enriched in energy metabolism pathways-suggesting that targeting energy dysregulation may represent a promising therapeutic avenue. We further elucidated the allele-specific, methylation-dependent mechanism by which ASM site rs2280906 regulates risk gene MYOM2. In healthy individuals, hypomethylation of the reference C allele permits MYOM2 expression. In contrast, affected individuals exhibit hypermethylation of this allele, leading to biallelic methylation, increased recruitment of repressive transcription factors, and MYOM2 downregulation. Our study uncovers new risk genes regulated by ASM and provide mechanistic insight into the rs2280906-MYOM2 axis in schizophrenia. Our work advances understanding of how epigenetic regulation contributes to disease susceptibility and inter-individual variability, and offers new avenues for the identification of causal variants and therapeutic targets.

PMID:41324836 | DOI:10.1007/s12035-025-05469-1

Prev Sci. 2025 Dec 1. doi: 10.1007/s11121-025-01860-5. Online ahead of print.

ABSTRACT

The COVID-19 pandemic had disparate impacts on Black and Hispanic Americans, as observed in mortality and infection rates. The mental health impact of the pandemic is less clear, with little research exploring mental health disparities and differences by state and region. Using the Behavioral Risk Factor Surveillance System (BRFSS), state-level differences in unhealthy mental health days were examined between 2019 and 2021 for White, Black, and Hispanic respondents. Nonparametric tests assessed group differences in unhealthy mental health days, while state-level within- and between-group difference scores highlighted areas with the greatest disparities. Both White and Black respondents experienced significantly more unhealthy mental health days in 2021 than in 2019; though Hispanic respondents reported more unhealthy days in 2021 than in 2019, this finding was not statistically significant. Black respondents, but not Hispanic, reported significantly more unhealthy mental health days than White respondents in 2021. Missouri had the worst outcomes for Black respondents, with the greatest increase in unhealthy mental health days between 2019 and 2021 and the greatest difference between White and Black groups in 2021. Regionally, the Northeast had the best outcomes for Black respondents and the Midwest had the worst. These findings can help identify population groups and geographic areas most in need of disaster-preparedness efforts and policy interventions for future public health emergencies. Practitioners and state health officials can use these findings to identify potentially impactful community interventions, or to develop infrastructure for addressing community mental health.

PMID:41324832 | DOI:10.1007/s11121-025-01860-5

Metabolomics. 2025 Dec 1;22(1):5. doi: 10.1007/s11306-025-02381-6.

ABSTRACT

OBJECTIVE: Radicular cyst (RC), the most prevalent odontogenic cyst in the jaw, remains poorly characterized regarding its systemic metabolic profile. This study aims to elucidate metabolic disturbance patterns in RC patients through serum metabolomics and identify potential biomarkers for constructing a diagnostic model.

METHODS: Serum samples from 30 RC patients and 20 healthy controls (HCs) were analyzed using gas chromatography-mass spectrometry (GC-MS)-based untargeted metabolomics. Multivariate statistical analyses (PCA, OPLS-DA) were employed to identify differential metabolites. A diagnostic model was subsequently developed through LASSO regression with ROC curve validation.

RESULTS: Seventy-three serum metabolites were identified, with 31 exhibiting significant dysregulation in RC patients (8 upregulated, 23 downregulated). LASSO regression selected seven metabolites (threonine, homoserine, dAMP, biotin, ADP, dGDP, deoxyuridine) to construct a diagnostic model demonstrating perfect discrimination between RC and HCs (sensitivity: 1.00, specificity: 1.00, AUC: 1.00).

CONCLUSION: This study provides the first report of systemic metabolic characteristics in RC patients and establishes a high-precision diagnostic model based on seven metabolites. These findings offer novel insights into RC pathogenesis and facilitate the development of non-invasive diagnostic approaches.

PMID:41324827 | DOI:10.1007/s11306-025-02381-6

Clin Exp Nephrol. 2025 Dec 1. doi: 10.1007/s10157-025-02798-2. Online ahead of print.

ABSTRACT

BACKGROUND: Cognitive impairment is a prevalent comorbidity in patients with chronic kidney disease (CKD). While hemodialysis (HD) and peritoneal dialysis (PD) are established renal replacement therapies, their relative effects on cognitive outcomes remain unclear. This meta-analysis compared cognitive outcomes between HD and PD in CKD patients.

METHODS: The protocol was prospectively registered on PROSPERO (CRD42024602533). PubMed, CENTRAL, Embase, Medline, Web of Science, PsychInfo, and CINAHL were searched from January 2000 to January 2025. Eligible studies included cohort studies of adult patients undergoing HD versus PD. Primary outcomes were cognitive function and dementia incidence. A random-effects meta-analysis model was used. Risk of bias was assessed using ROBINS-I, and evidence quality was evaluated using GRADE. Methodological rigor was benchmarked against previous reviews using AMSTAR 2.0.

RESULTS: The search identified 1489 studies, of which 26, involving 326,216 patients, were included. There was a statistically significant difference in overall cognitive function between HD and PD (SMD: -0.46; 95% CI: -0.62 to -0.29; p < 0.00001; I² = 49%), and dementia incidence (OR: 1.68; 95% CI: 1.25 to 2.25; p = 0.0006; I² = 94%). Subgroup and qualitative analyses suggested PD offers advantages in executive function, verbal memory, and cognitive stability.

CONCLUSIONS: Quantitative analyses revealed significant evidence, and qualitative trends suggest PD may be associated with better cognitive outcomes in select domains. These findings underscore the need to individualize dialysis modality decisions based on cognitive risk profiles and conduct further standardized research.

PMID:41324826 | DOI:10.1007/s10157-025-02798-2

Curr Environ Health Rep. 2025 Dec 1;12(1):50. doi: 10.1007/s40572-025-00517-3.

ABSTRACT

PURPOSE OF REVIEW: Interrupted time series (ITS) designs are increasingly used in environmental health to evaluate impacts of extreme weather events or policies. This paper aims to introduce traditional and contemporary ITS approaches, including machine learning algorithms and Bayesian frameworks, which enhance flexibility in modeling complex temporal patterns (e.g., seasonality and nonlinear trends) and spatially heterogeneous treatment effects. We present a comparative analysis of methods such as ARIMA, machine learning models, and Bayesian ITS, using a real-world case study: estimating excess respiratory hospitalizations during the 2018 wildfire smoke event in San Francisco.

RECENT FINDINGS: Our study demonstrates the practical application of these methods and provides a guide for selecting and implementing ITS designs in environmental epidemiology. To ensure reproducibility, we share annotated datasets and R scripts, allowing researchers to replicate analyses and adapt workflows. While focused on environmental applications, particularly acute exposures like wildfire smoke, the framework is broadly applicable to public health interventions. This work advances ITS methodology by integrating contemporary statistical innovations and emphasizing actionable guidance for causal inference in complex, real-world settings.

PMID:41324811 | DOI:10.1007/s40572-025-00517-3

Environ Monit Assess. 2025 Dec 1;197(12):1389. doi: 10.1007/s10661-025-14828-3.

ABSTRACT

Coastal wetlands, unique ecosystems situated at the interface of land and coastal waters, are the principal retention pools for environmental microplastics, which can be degraded at higher rates by their anomalous hydrological characteristics. The Ashtamudi coastal wetland, a Ramsar wetland, is increasingly affected by anthropogenic and natural microplastic pollution and nutrient enrichment. To evaluate the present status and spatial heterogeneity in this ecosystem, water quality and microplastic distribution were studied at seven sites. Extensive physicochemical analysis was carried out with key physicochemical parameters such as BOD, potassium, nitrogen, phosphorus, TDS, turbidity, and chloride, and microplastic characterization using FTIR spectroscopy, zeta potential, and UV-visible analysis. Statistical analysis showed significant spatial heterogeneity in water quality and microplastic characteristics. CPCB limit exceedance was found at all the sites for BOD, chloride, and water quality index (WQI), suggesting extreme organic pollution, salinity stress, and overall water quality impairment. High levels of nitrogen (~ 5.5 mg/L) and phosphorus (~ 1.2 mg/L) at all the sites, particularly at Thekkumbhagam, suggest advanced eutrophication, leading to algal blooms, oxygen depletion, and aquatic ecosystem disturbance. Mukkadu and Ashtamudi presented relatively lower values, but all the sites exceeded wetland nutrient thresholds. FTIR detected microplastic polymers like polypropylene (PP), polyethene (PE), polyvinyl chloride (PVC), and polyethene terephthalate (PET), with differences in particle size and distribution. Besides identification, microplastics are carriers of toxic pollutants, alter aquatic food chains, and produce ingestion-related health risks to organisms. The current study points out the interlinked consequences of nutrient enrichment, salinity, ecological concerns and microplastic dispersal, suggesting the ecological vulnerability of the Ashtamudi wetland. The study outlines the future scope and possible solutions for the mitigation of microplastic pollution in wetlands. These implications need immediate pollution control and conservation measures to ensure the long-term environmental sustainability of this critical wetland ecosystem.

PMID:41324810 | DOI:10.1007/s10661-025-14828-3

J Gastrointest Cancer. 2025 Dec 1;56(1):232. doi: 10.1007/s12029-025-01312-x.

ABSTRACT

BACKGROUND: Routine endoscopic re-evaluation of gastric ulcers (GUs) is widely recommended to exclude malignancy. However, in modern practice, particularly in low-to-intermediate gastric cancer prevalence settings, the diagnostic yield, cost-effectiveness, and necessity of universal surveillance are increasingly debated.

OBJECTIVE: To evaluate compliance with British and Irish guidelines recommending repeat gastroscopy for GUs, identify predictors of malignancy, and assess the diagnostic yield and healthcare cost of ulcer re-evaluation in a large tertiary centre.

METHODS: We retrospectively analysed 2132 index GUs from 56,874 gastroscopies performed between May 2006 and August 2024. Demographic, endoscopic, and histological data were collected. Malignancy outcomes were determined by cross-referencing with histology databases. Binary logistic regression identified predictors of malignancy. Surveillance rates, ulcer healing, and inflation-adjusted costs were assessed.

RESULTS: Eighty-six ulcers (4%) were diagnosed as gastric malignancies. Of these, 96% were identified at index histology; three were diagnosed at short-interval re-evaluation following inadequate or false-negative biopsies. No malignancies were detected during routine surveillance of benign-appearing ulcers with adequate histology. Macroscopic concern was the strongest predictor of malignancy (odds ratio 66.9, p < 0.01), alongside older age, male sex, and non-antral ulcer location. Surveillance was performed in 59% of benign ulcers at a mean interval of 12.5 weeks. None of the 837 patients with benign ulcers who did not undergo re-evaluation developed gastric cancer during 19 years of follow-up. Re-evaluation procedures represented 2.5% of total endoscopy workload, at a cumulative cost of €1,028,016.

CONCLUSION: Routine re-evaluation of GUs that appear benign and have adequate negative histology provided minimal diagnostic benefit while generating significant healthcare costs. A selective approach, focusing on ulcers with suspicious endoscopic features, inadequate biopsies, or unresolved symptoms, would better allocate resources and avoid unnecessary procedures.

PMID:41324807 | DOI:10.1007/s12029-025-01312-x

Support Care Cancer. 2025 Dec 1;33(12):1154. doi: 10.1007/s00520-025-10210-8.

ABSTRACT

BACKGROUND: Pressure injuries are a significant concern in oncologic surgical patients due to factors such as hypoproteinemia and complex surgeries. These injuries impact the quality of care and patient safety. Despite the importance of prevention, nurses often rely on empirical methods, leading to procedural errors. Checklist management, a structured approach to quality control, has shown promise in improving outcomes in various medical contexts. This study aims to explore the clinical application and effectiveness of checklist management in preventing pressure injuries among oncologic surgical patients.

OBJECTIVE: To investigate the impact of implementing checklist management on the execution of pressure injury prevention programs among operating room nurses, aiming to establish a standardized operational procedure through the use of a task checklist.

METHODS: A convenience sampling method was used to select patients undergoing elective surgery under general anesthesia at a tertiary-level cancer hospital in Tianjin between August and December 2022. Patients from August to September 2022 (4658 cases) were assigned to the control group, which implemented conventional pressure injury prevention management. Patients from November to December 2022 (4508 cases) were assigned to the observation group, which implemented checklist-based pressure injury prevention management. Compare the compliance rate of nursing staff in risk assessment, the pass rate of patient positioning, the proper use rate of pressure-relieving dressings, comprehensive knowledge of prevention management, the incidence of pressure injuries, and feedback on the implementation of the Evidence-Based Nursing Practice Plan for Pressure Injury Prevention in Surgical Patients between the two groups.

RESULTS: After implementing checklist-based management, compared to the control group, the observation group showed significant improvements: risk assessment compliance rate increased from 83.02% to 95.23%;Patient positioning pass rate increased from 81.25% to 95.25%; proper use rate of pressure-relieving dressings increased from 72.75% to 96.50%; average score for comprehensive knowledge of prevention management increased from 77.69 ± 4.67 to 92.89 ± 1.54; incidence of pressure injuries decreased from 0.322% to 0.067%, with the incidence of Stage 2 or higher pressure injuries decreasing from 0.086% to 0.000%. Additionally, the observation group scored significantly higher than the control group in terms of implementation convenience, operational proficiency, and team collaboration efficiency, and it had a long-term positive impact. All indicators showed statistical significance (P < 0.05).

CONCLUSION: Checklist management facilitates the routine implementation of pressure injury prevention management programs for oncologic surgical patients, effectively enhances nurses’ preventive practice abilities, thereby reducing the incidence of pressure injuries. It promotes refined and homogeneous development in operating room nursing quality control.

PMID:41324795 | DOI:10.1007/s00520-025-10210-8

J Robot Surg. 2025 Dec 1;20(1):50. doi: 10.1007/s11701-025-03002-z.

ABSTRACT

Console time is one of the automated performance metrics (APM) recorded by the robot software during robotic cardiac surgery. Little is known about what this APM predicts in cardiac surgery. This study aimed to evaluate factors associated with console time during robotically assisted mitral valve repair (raMVR). A total of 150 patients underwent raMVR from 7/2021 to 12/2024. Console time and related APMs were extracted from robotic system logs. Correlation analysis, multivariable linear regression, and multivariate analysis of variance (MANOVA) were used to assess associations between console time and pre-, intra-, and post-operative outcomes. Mean console time was 123.2 ± 47.0 min. Console time correlated with body mass index (r = 0.22, p = 0.01), cardiopulmonary bypass (CPB) time (r = 0.50, p < 0.001), aortic cross-clamp (ACC) time (r = 0.60, p < 0.001), and hospital stay (r = 0.24, p = 0.003). Console time was longer with bileaflet prolapse (p = 0.003), annular calcification (p = 0.01), leaflet calcification (p = 0.04), complex repair (p < 0.001), transfusion (p = 0.01) and reoperation for bleeding (p = 0.005). Multivariable regression identified decalcification (B = + 78.6 min, p < 0.001), ACC time (p < 0.001), CPB time (p = 0.02), leaflet resection combined with neochords (p = 0.01), and annular calcification (p = 0.03) as independent predictors. MANOVA showed console time tertiles were significantly associated with postoperative outcomes (Wilks’ lambda = 0.86, p = 0.02). Patients in the lowest and middle tertile were more likely to be extubated in the operating room (p < 0.001). Console time reflects procedural complexity and operative intensity in raMVR. As an automated, objective metric, it may serve as a valuable tool for intra-operative assessment, surgical planning, and early outcome prediction in robotic cardiac programs.

PMID:41324791 | DOI:10.1007/s11701-025-03002-z