Tag: pubmed

Environ Monit Assess. 2025 Jun 14;197(7):751. doi: 10.1007/s10661-025-14205-0.

ABSTRACT

This study investigates the ecological dynamics of Qiaoying Reservoir, a medium-sized multi-purpose water body in Zhejiang Province, China, through seasonal (spring and autumn 2022) analyses of aquatic communities, water quality, and Ecopath modeling. Fish community structure showed seasonal shifts, with Cypriniformes dominating (68.75% in spring, 88.89% in autumn), while zooplankton composition transitioned from Cladocera-dominated (38.46%) to Copepoda-dominated (35.71%) between seasons. Phytoplankton biomass and density exhibited consistent spatial patterns (higher in southeastern zones). Water quality met Class I standards, with stable physicochemical parameters. Ecopath modeling revealed simplified trophic interactions (Connectance Index, 0.333; Omnivory Index, 0.136), with 76% of energy flow concentrated at trophic level I (primary producers). The low inter-trophic transfer efficiency (total 2.25%) highlighted imbalances, notably insufficient grazer pressure on phytoplankton. Recommendations include diversifying fish stocking (Hypophthalmichthys nobilis, Cyprinus carpio, Hypophthalmichthys molitrix, Carassius auratus, and Megalobrama terminalis) to enhance trophic regulation, adjusting harvest strategies. This integrated approach supports sustainable fisheries management by aligning ecological capacity with socioeconomic needs, emphasizing the role of filter-feeding species in maintaining water quality and ecosystem stability.

PMID:40515961 | DOI:10.1007/s10661-025-14205-0

Mol Biol Rep. 2025 Jun 14;52(1):593. doi: 10.1007/s11033-025-10646-5.

ABSTRACT

OBJECTIVE: To evaluate the prevalence and clinical significance of autoantibodies to mitochondrial sulphite oxidase (SUOX) and glycogen phosphorylase (PYGL) in Chinese PBC patients.

METHODS: Enzyme-linked immunosorbent assays (ELISA) were developed with purified SUOX and PYGL proteins. Serum samples from 780 PBC patients and 352 healthy controls were used for antibody detection. Statistical analysis was performed with antibody results and biochemical data from PBC patients.

RESULTS: Antibodies to SUOX and PYGL were found in 14.23% and 22.94% of PBC patients, but also in 6.53% and 9.37% of healthy controls. There is a significant positive correlation between anti-SUOX and -PYGL with anti-M2, -sp100 and -gp210. Anti-SUOX and -PYGL positivity does not correlate with ursodeoxycholic acid (UDCA) response. Time course analysis found no specific change of anti-SUOX or -PYGL antibody titers in positive patients before and after UDCA treatment.

CONCLUSIONS: The data concluded that anti-SUOX and -PYGL autoantibodies are not serological markers in PBC diagnosis due to a lack of sensitivity and specificity. With the existence of PBC specific autoantibodies in PBC diagnosis and treatment, anti-SUOX and -PYGL status in PBC patients have no significant value.

PMID:40515960 | DOI:10.1007/s11033-025-10646-5

Clin Exp Med. 2025 Jun 14;25(1):204. doi: 10.1007/s10238-025-01753-5.

ABSTRACT

The SARS-CoV-2 RNA virus, with its rapid spread and frequent genetic changes, has posed unparalleled obstacles for public health and treatment efforts. Early diagnosis of the disease and the development of effective treatment strategies are the main pillars of epidemic control. In this regard, machine learning (ML) methods, an advanced subset of artificial intelligence (AI), can play an effective role in improving the accuracy of diagnosis and the effectiveness of treatments related to SARS-CoV-2. However, the implementation of ML in clinical settings faces issues such as data heterogeneity, lack of training data, model interpretability challenges, patient privacy protection, and implementation limitations. This article provides a systematic review of the applications of federated learning (FL), deep learning (DL), reinforcement learning (RL), and hybrid approaches in the field of SARS-CoV-2 diagnosis and treatment. Based on the analysis of the results, the main focus of the research was on increasing privacy and security (P&S) with a share of 26%, improving detection accuracy and robustness (DAR) with 24%, and improving computational and communication efficiency (CCE) with 20%. These statistics indicate the importance of prioritizing patient information confidentiality and improving systems’ accuracy and stability against data variability. In conclusion, the findings of this review can pave the way for the practical application of ML technologies in clinical decision-making and improving the quality of healthcare services related to SARS-CoV-2.

PMID:40515956 | DOI:10.1007/s10238-025-01753-5

Support Care Cancer. 2025 Jun 14;33(7):582. doi: 10.1007/s00520-025-09627-y.

ABSTRACT

PURPOSE: The purpose of this study was to compare the utilization of complementary, alternative, and integrative medicine (CAIM) therapies between US adults with and without cancer.

METHODS: This investigation is based on publicly available data from the 2022 National Health Information Survey (NHIS). Descriptive statistics are presented for demographic characteristics, physical and mental health factors, and CAIM practices stratified by cancer status. Differences between groups were assessed using chi-squared tests, with significance defined by p < 0.05.

RESULTS: The study included 24,184 individuals without cancer and 3430 individuals with a self-reported history of any cancer type. The majority of participants were of non-Hispanic White racial-ethnic background, 54% were female, and those with cancer were found to be significantly older than those without. Approximately 18% of adults reported meditating during the past 12 months, and 15% practiced yoga; however, individuals with a history of cancer were significantly less likely to practice yoga than non-cases (p < 0.001). While cancer cases sought out practices for pain relief more frequently than non-cases, the utilization of these activities was < 5%.

CONCLUSIONS: Notably, fewer than 20% of US adults who completed the NHIS 2022 survey, regardless of cancer status, reported participating in CAIM practices within the prior year. While some may not find CAIM therapies beneficial or of interest, providing education to this population has the potential to better aid with symptom management. Future research should explore influencing factors for the adoption of these practices to quantify the impact of these modalities and uncover the potential epigenetic changes and biological mechanisms responsible for their effects, particularly among those diagnosed with cancer.

PMID:40515954 | DOI:10.1007/s00520-025-09627-y

Support Care Cancer. 2025 Jun 14;33(7):581. doi: 10.1007/s00520-025-09633-0.

ABSTRACT

PURPOSE: The Clinical Oncology Society of Australia (COSA) position statement on exercise in cancer care encourages all healthcare professionals to discuss, recommend, and refer people with cancer to exercise; however, use of these recommendations in practice is unknown.

METHODS: Oncology healthcare professionals working in Australia were invited to complete a cross-sectional online survey that assessed contextual factors that influence implementation of COSA exercise guidance in cancer care, based on the Consolidated Framework for Implementation Research.

RESULTS: We received 133 survey responses. Most were women (74%), nurses (35%), or oncologists (26%), involved in cancer care for > 10 years (63%), and in a public hospital setting (69%). Most participants agreed that exercise is beneficial (94%) and the COSA recommendations would positively influence patients’ exercise behaviours (94%). However, only 35% routinely apply COSA recommendations in practice, and only 35% believe they are the best person to provide exercise support. Patient-level barriers included needing additional support to access exercise (92%), most commonly financial (74%). Organisational-level barriers included a lack of dedicated resources to support delivering exercise guidance (69%), and not believing providing exercise guidance is an important part of their role (51%). Only 24% agreed their organisation revised practice based on the COSA recommendations.

CONCLUSION: Despite most oncology healthcare professionals agreeing that exercise is beneficial, and that the COSA recommendations are important for patients, only a minority actually apply the recommendations in their practice. Targeted implementation efforts are needed to facilitate use of COSA exercise guidance in clinical practice.

PMID:40515951 | DOI:10.1007/s00520-025-09633-0

J Community Health. 2025 Jun 14. doi: 10.1007/s10900-025-01489-z. Online ahead of print.

ABSTRACT

The purpose of this study was to measure the HPV vaccine behaviors and intentions of college-aged men. 493 participants, who identified as “male” or “trans man”, from a large university in the Mid-Atlantic were included in this study. An online survey measured several independent variables as well as variables related to HPV and HPV vaccine knowledge, perceptions, and behaviors. Descriptive statistics were used to evaluate each variable after filtering the participants by vaccination status. A binomial logistic regression was used to analyze and predict the effect of each variable on college men’s vaccination status. The academic year in which participants completed the survey, home location, and HPV knowledge were significant predictors of HPV vaccination status. Lack of inclusion of males during conversations about the HPV vaccine could be the source of the differences between male and female HPV vaccination behavior and intention.

PMID:40515894 | DOI:10.1007/s10900-025-01489-z

Metabolomics. 2025 Jun 14;21(4):78. doi: 10.1007/s11306-025-02265-9.

ABSTRACT

INTRODUCTION: Breast cancer is the most common cancer among women, with its burden increasing over the past decades. Early diagnosis significantly improves survival rates and reduces lethality. Innovative technologies are being developed for early detection, making accurate tumor identification crucial.

OBJECTIVES: The research aims to identify significant metabolomics biomarkers that can help in detecting tumor progression, which could contribute to early breast cancer diagnosis.

METHODS: A dataset of 228 metabolites from breast cancer patients and healthy individuals was curated from the Metabolomics Workbench Database. Statistical tests and Machine Learning (ML) algorithms were applied for feature selection, assessing normality, variance homogeneity, and significance Recursive Feature Elimination (RFE) with a Random Forest (RF) classifier was used to identify a minimal set of six significant metabolites with strong predictive potential. A Ridge Classifier was employed for classification, achieving an 83% accuracy in distinguishing between cancerous and healthy individuals.

RESULTS: A minimal set of six significant metabolites was identified in plasma samples. The developed model showed an 83% accuracy in classifying cancerous vs. healthy individuals using the Ridge Classifier.

CONCLUSION: The study provides valuable insights into metabolomic changes associated with breast cancer, identifying potential biomarkers that could enhance early detection and diagnosis.

PMID:40515893 | DOI:10.1007/s11306-025-02265-9

Lifetime Data Anal. 2025 Jun 14. doi: 10.1007/s10985-025-09658-x. Online ahead of print.

ABSTRACT

We study shape-constrained nonparametric estimation of the underlying survival function in a cross-sectional study without follow-up. Assuming the rate of initiation event is stationary over time, the observed current duration becomes a length-biased and multiplicatively censored counterpart of the underlying failure time of interest. We focus on two shape constraints for the underlying survival function, namely, log-concavity and convexity. The log-concavity constraint is versatile as it allows for log-concave densities, bi-log-concave distributions, increasing densities, and multi-modal densities. We establish the consistency and pointwise asymptotic distribution of the shape-constrained estimators. Specifically, the proposed estimator under log-concavity is consistent and tuning-parameter-free, thus circumventing the well-known inconsistency issue of the Grenander estimator at 0, where correction methods typically involve tuning parameters.

PMID:40515884 | DOI:10.1007/s10985-025-09658-x

Support Care Cancer. 2025 Jun 14;33(7):579. doi: 10.1007/s00520-025-09575-7.

ABSTRACT

PURPOSE: Lesbian, Gay, Bisexual, Transgender, Queer, Plus (LGBTQ+) cancer survivors are at risk of financial hardship due to multilevel factors amplified by anti-LGBTQ+ stigma. Transgender and gender diverse (TGD) cancer survivors may experience greater financial hardship than cisgender lesbian, gay, and bisexual (LGB) individuals, but data on LGBTQ+ individuals is often reported in aggregate. We describe differences in crowdfunding experiences between TGD and LGB cancer crowdfunding campaigns to address this gap in TGD cancer-related financial hardship literature.

METHODS: We used a mixed methods approach to evaluate LGBTQ+ cancer crowdfunding campaigns from GoFundMe’s website, coded as TGD or LGB. Campaign data (amount raised, funding goal, etc.) were compared using summary statistics and independent t-tests. Qualitative content analysis described campaign text. Quantitative and qualitative findings were integrated by theme.

RESULTS: A total of N = 470 LGBTQ+ cancer campaigns were included for this analysis, of which 175 (32.5%) were TGD campaigns and 295 (54.8%) were LGB. TGD campaigns raised 39% less than LGB campaigns ($7782 [$5842-$9723] vs. $12,724 [$10,525-$14,924], p < 0.0001). TGD campaigns had more mentions of perceived stigma in healthcare spaces and fewer mentions of caregiver support.

CONCLUSIONS: TGD cancer campaigns earned significantly less money than LGB campaigns, suggesting that TGD cancer survivors may face more challenges in using community-based financial support mechanisms to mitigate financial hardship. Structural stigma and transphobia may be impacting the amount of funds raised by TGD cancer survivors through crowdfunding.

PMID:40515868 | DOI:10.1007/s00520-025-09575-7

Environ Monit Assess. 2025 Jun 14;197(7):752. doi: 10.1007/s10661-025-14246-5.

ABSTRACT

This study examines the spatial and temporal characteristics of heatwaves (HWs) in Türkiye, a region predominantly characterized by an arid-semiarid macro-Mediterranean climate, which is susceptible to frequent droughts. Using daily maximum temperature data from 277 meteorological stations across Türkiye (1970-2022), the research analyzes HW frequency, duration, and intensity, adopting a definition aligned with the World Meteorological Organization (WMO). Temporal trends were assessed using statistical trend analysis, while spatial patterns were evaluated through spatial autocorrelation methods. The findings indicate a statistically significant increase in the frequency of heatwaves over time, with the annual average number of events rising from approximately 5 in the 1970s to over 10 since the 2000s. This trend is particularly evident in the Marmara, Aegean, and Black Sea regions. Trend analysis results reveal that heatwave duration has exhibited a statistically significant increase throughout the study period in 96.4% of the analyzed stations. The most pronounced increases have been observed in the Marmara, Black Sea, and Eastern Mediterranean regions. These results underscore the growing impact of climate change on Türkiye and highlight the need for targeted adaptation and mitigation strategies. Insights from this study can inform the development of early warning systems, resource allocation, and public health preparedness, ultimately enhancing community and ecosystem resilience to climate-related challenges.

PMID:40515861 | DOI:10.1007/s10661-025-14246-5