Category: Statistics

Skelet Muscle. 2025 Jan 13;15(1):2. doi: 10.1186/s13395-024-00371-1.

ABSTRACT

BACKGROUND: Duchenne muscular dystrophy (DMD) is a prevalent, fatal degenerative muscle disease with no effective treatments. Mdx mouse model of DMD exhibits impaired muscle performance, oxidative stress, and dysfunctional autophagy. Although antioxidant treatments may improve the mdx phenotype, the precise molecular mechanisms remain unclear. This study investigates the effects of aminoguanidine hemisulfate (AGH), an inhibitor of reactive oxygen species (ROS), on mitochondrial autophagy, oxidative stress, and muscle force in mdx mice.

METHODS: Male wild-type (WT) and mdx mice were divided into three groups: WT, mdx, and AGH-treated mdx mice (40 mg/kg intraperitoneally for two weeks) at 6 weeks of age. Gene expression, western blotting, H&E staining, immunofluorescence, ROS assays, TUNEL apoptosis, glutathione activity, and muscle force measurements were performed. Statistical comparisons used one-way ANOVA.

RESULTS: AGH treatment significantly reduced the protein levels of LC3, and p62 in mdx mice, indicating improved autophagy activity and the ability to clear damaged mitochondria. AGH restored the expression of mitophagy-related genes Pink1 and Parkin and increased Mfn1, rebalancing mitochondrial dynamics. It also increased Pgc1α and mtTFA levels, promoting mitochondrial biogenesis. ROS levels were reduced, with higher Prdx3 and MnSOD expression, improving mitochondrial antioxidant defenses. AGH normalized the GSSG/GSH ratio and decreased glutathione reductase and peroxidase activities, further improving redox homeostasis. Additionally, AGH reduced apoptosis, shown by fewer TUNEL-positive cells and lower caspase-3 expression. Histological analysis revealed decreased muscle damage and fewer embryonic and neonatal myosin-expressing fibers. AGH altered fiber composition, decreasing MyH7 while increasing MyH4 and MyH2. Muscle force improved significantly, with greater twitch and tetanic forces. Mechanistically, AGH modulated the AKT/FOXO1 pathway, decreasing myogenin and Foxo1 while increasing MyoD.

CONCLUSIONS: AGH treatment restored mitochondrial autophagy, reduced oxidative stress, apoptosis, and altered muscle fiber composition via the AKT/FOXO1 pathway, collectively improving muscle force in mdx mice. We propose AGH as a potential therapeutic strategy for DMD and related muscle disorders.

PMID:39806512 | DOI:10.1186/s13395-024-00371-1

Virol J. 2025 Jan 13;22(1):10. doi: 10.1186/s12985-025-02626-9.

ABSTRACT

BACKGROUND: Mycoplasma pneumoniae (MP) is a common pathogen for respiratory infections in children. Previous studies have reported respiratory tract microbial disturbances associated with MP infection (MPI); however, since the COVID-19 pandemic, respiratory virome data in school-aged children with MPI remains insufficient. This study aims to explore the changes in the respiratory virome caused by MPI after the COVID-19 pandemic to enrich local epidemiological data.

METHODS: Clinical samples from 70 children with MPI (70 throat swab samples and 70 bronchoalveolar lavage fluid (BALF) samples) and 78 healthy controls (78 throat swab samples) were analyzed using viral metagenomics. Virus reads were calculated and normalized using MEGAN.6, followed by statistical analysis.

RESULTS: Principal Coordinate Analysis (PCoA) showed that viral community diversity is a significant difference between disease cohorts and healthy controls. After MPI, the number of virus species in the upper respiratory tract (URT) increased obviously, and the abundance of families Poxviridae, Retroviridae, and Iridoviridae, which infect vertebrates, rose evidently, particularly the species BeAn 58,085 virus (BAV). Meanwhile, phage alterations in the disease cohorts were predominantly characterized by increased Myoviridae and Ackermannviridae families and decreased Siphoviridae and Salasmaviridae families (p < 0.01). In addition, some new viruses, such as rhinovirus, respirovirus, dependoparvovirus, and a novel gemykibvirus, were also detected in the BALF of the disease cohort.

CONCLUSIONS: This cross-sectional research highlighted the respiratory virome characteristics of school-aged children with MPI after the COVID-19 outbreak and provided important epidemiological information. Further investigation into the impact of various microorganisms on diseases will aid in developing clinical treatment strategies.

PMID:39806507 | DOI:10.1186/s12985-025-02626-9

J Cardiovasc Imaging. 2025 Jan 13;33(1):1. doi: 10.1186/s44348-024-00043-0.

ABSTRACT

BACKGROUND: There are insufficient studies to determine whether sodium-glucose cotransporter type 2 inhibitors (SGLT2i) will help reduce early diabetic cardiomyopathy, especially in patients without documented cardiovascular disease.

METHODS: We performed a single center, prospective observation study. A total of 90 patients with type 2 diabetes patients without established heart failure or atherosclerotic cardiovascular disease were enrolled. Echocardiography, cardiac enzyme, and glucose-control data were examined before and 3 months after the administration of SGLT2i (dapagliflozin 10 mg per day). Cardiovascular risk factors included hypertension, smoking, obesity, dyslipidemia, and old age. The primary end point was the change of E/e’ before and after administration of SGLT2i.

RESULTS: Most patients (86.7%) had three or more cardiovascular risk factors, and about 32% had all five risk factors. Although the decrease in E/e’ after the administration of SGLT2i was observed in 20% of enrolled patients, there was no significant difference in average E/e’ value or left atrial volume index before and after the SGLT2i medication. Even in patients with all known risk factors including old age, E/e’ value did not decrease after adding SGLT2i (8.9 ± 2.4 vs. 8.7 ± 3.2). There was a statistically significant difference in E/e’ change after the SGLT2i administration between patients younger than 60 years and those older than 60 years (-0.7 ± 2.2 vs. 1.1 ± 2.8, P = 0.002).

CONCLUSIONS: In type 2 diabetes patients without documented cardiovascular disease including heart failure, administration of SGLT2i showed no improvement in diastolic function profile. Further large-scale randomized studies are needed to determine who will benefit from potential cardiovascular events with early addition of SGLT2i.

PMID:39806504 | DOI:10.1186/s44348-024-00043-0

Int J Retina Vitreous. 2025 Jan 13;11(1):6. doi: 10.1186/s40942-025-00628-x.

ABSTRACT

BACKGROUND: Management of Diabetic Macular edema (DME) requires repeated injections. Therefore newer Anti-VEGFs like Brolucizumab with longer durability have been introduced. We compared two different dosages of Brolucizumab, 6.0 mg and 3.6 mg, for their safety & efficacy in treatment of DME, in treatment naïve patients over 52 weeks.

METHOD: A prospective, pilot randomised controlled, single centre, double blinded, two arm comparative study was conducted between Dec 2022 to Apr 2024. The study recruited 82 patients of DME who were randomised into two groups of 41 patients each, one group to be treated with Brolucizumab 6.0 mg in 50 μL and the other to receive 3.6 mg in 30 μL. All patients received the first dose of Brolucizumab at 0 week and were then followed up at every 4 weeks for detailed ophthalmic and OCT macula examination. Those who met the pre-defined re-treatment criteria were re-injected with Brolucizumab, the dose being fixed for each group throughout the study. All patient receiving an injection were further followed up on Day 1, Day 7 and Day 28 to look for any adverse reactions. The efficacy parameters included change in best corrected visusal acuity (BCVA), contrast and central macular thickness (CMT) on Optical Coherence Tomography. The average number of injections recd in each group were also calculated.

RESULTS: The change in BCVA from baseline in 6.0 mg group was 0.54 LogMAR units and 3.6 mg group was 0.59 LogMAR units, which was not statistically significant. The reduction in CMT from baseline in 6.0 mg group was 133.2 µm (μ) and 3.6 mg group was 110.6 μ, which was not statistically significant. The improvement in contrast from baseline in 6.0 mg group was 0.74 and 3.6 mg group was 0.95, with p value of 0.0002. The re-injection interval was 14.21 weeks in 6.0 mg group and 15.56 weeks for 3.6 mg subgroup. The total number of adverse events in both groups were similar at 70 in 6.0 mg group and 47 in 3.6 mg group with only one grade 4 adverse event occurring in each group.

CONCLUSION: The results of present study show that the safety and efficacy of both doses of Brolucizumab, i.e. 6.0 mg and 3.6 mg, for treating diabetic macular edema is similar. Trial registration Study was registered with Clinical trials registry of India (CTRI ref no. CTRI/2023/06/054105), registered on 14 Nov 2022.

PMID:39806501 | DOI:10.1186/s40942-025-00628-x

Int J Retina Vitreous. 2025 Jan 13;11(1):5. doi: 10.1186/s40942-025-00630-3.

ABSTRACT

PURPOSE: To evaluate the predictive accuracy of various machine learning (ML) statistical models in forecasting postoperative visual acuity (VA) outcomes following macular hole (MH) surgery using preoperative optical coherence tomography (OCT) parameters.

METHODS: This retrospective study included 158 eyes (151 patients) with full-thickness MHs treated between 2017 and 2023 by the same surgeon and using the same intraoperative surgical technique. Data from electronic medical records and OCT scans were extracted, with OCT-derived qualitative and quantitative MH characteristics recorded. Six supervised ML models-ANCOVA, Random Forest (RF) regression, K-Nearest Neighbor, Support Vector Machine, Extreme Gradient Boosting, and Lasso regression-were trained using an 80:20 training-to-testing split. Model performance was evaluated on an independent testing dataset using the XLSTAT software. In total, the ML statistical models were trained and tested on 14,652 OCT data points from 1332 OCT images.

RESULTS: Overall, 91% achieved MH closure post-surgery, with a median VA gain of -0.3 logMAR units. The RF regression model outperformed other ML models, achieving the lowest mean square error (MSE = 0.038) on internal validation. The most significant predictors of VA were postoperative MH closure status (variable importance = 43.078) and MH area index (21.328). The model accurately predicted the post-operative VA within 0.1, 0.2 and 0.3 logMAR units in 61%, 78%, and 87% of OCT images, respectively.

CONCLUSION: The RF regression model demonstrated superior predictive accuracy for forecasting postoperative VA, suggesting ML-driven approaches may improve surgical planning and patient counselling by providing reliable insights into expected visual outcomes based on pre-operative OCT features.

CLINICAL TRIAL REGISTRATION NUMBER: Not applicable.

PMID:39806497 | DOI:10.1186/s40942-025-00630-3

Environ Microbiome. 2025 Jan 13;20(1):5. doi: 10.1186/s40793-024-00659-1.

ABSTRACT

BACKGROUND: Viruses that infect prokaryotes (phages) constitute the most abundant group of biological agents, playing pivotal roles in microbial systems. They are known to impact microbial community dynamics, microbial ecology, and evolution. Efforts to document the diversity, host range, infection dynamics, and effects of bacteriophage infection on host cell metabolism are extremely underexplored. Phages are classified as virulent or temperate based on their life cycles. Temperate phages adopt the lysogenic mode of infection, where the genome integrates into the host cell genome forming a prophage. Prophages enable viral genome replication without host cell lysis, and often contribute novel and beneficial traits to the host genome. Current phage research predominantly focuses on lytic phages, leaving a significant gap in knowledge regarding prophages, including their biology, diversity, and ecological roles.

RESULTS: Here we develop and describe Prophage-DB, a database of prophages, their proteins, and associated metadata that will serve as a resource for viral genomics and microbial ecology. To create the database, we identified and characterized prophages from genomes in three of the largest publicly available databases. We applied several state-of-the-art tools in our pipeline to annotate these viruses, cluster them, taxonomically classify them, and detect their respective auxiliary metabolic genes. In total, we identify and characterize over 350,000 prophages and 35,000 auxiliary metabolic genes. Our prophage database is highly representative based on statistical results and contains prophages from a diverse set of archaeal and bacterial hosts which show a wide environmental distribution.

CONCLUSION: Given that prophages are particularly overlooked and merit increased attention due to their vital implications for microbiomes and their hosts, we created Prophage-DB to advance our understanding of prophages in microbiomes through a comprehensive characterization of prophages in publicly available genomes. We propose that Prophage-DB will serve as a valuable resource for advancing phage research, offering insights into viral taxonomy, host relationships, auxiliary metabolic genes, and environmental distribution.

PMID:39806487 | DOI:10.1186/s40793-024-00659-1

BMC Res Notes. 2025 Jan 13;18(1):11. doi: 10.1186/s13104-024-07064-4.

ABSTRACT

BACKGROUND: Postharvest lemons are affected by several fungal infections, and as alternatives to chemical fungicides for combating these infections, different microbial biocontrol agents have been studied, with the Clavispora lusitaniae 146 strain standing out. Although strain 146 has proven to be an effective agent, the influence of a microbial biological control agent on the postharvest lemon microbiome has not been studied until now. Thus, this study aimed to evaluate how the epiphytic microbiome of postharvest lemons is affected by the application of the biocontrol yeast C. lusitaniae 146.

RESULTS: In terms of bacterial composition, the most abundant genera were Sphingomonas, Pelomonas, and Bacillus and no significant differences in the composition were detected between the treated and control samples. Among fungi, Clavispora was predominant not only in the treated samples but also in the control, and statistics indicated differences, suggesting its significant role in modulating the epiphytic community composition of lemon. Understanding fruit microbiomes is vital for effective disease control, and this study provides insights into the microbial composition of the surface of lemon and the role of C. lusitaniae 146.

PMID:39806479 | DOI:10.1186/s13104-024-07064-4

Lipids Health Dis. 2025 Jan 13;24(1):12. doi: 10.1186/s12944-024-02426-0.

ABSTRACT

Lipid metabolism in cancer is characterized by dysregulated lipid regulation and utilization, critical for promoting tumor growth, survival, and resistance to therapy. Pancreatic cancer (PC) is a highly aggressive malignancy of the gastrointestinal tract that has a dismal 5-year survival rate of less than 10%. Given the essential function of the pancreas in digestion, cancer progression severely disrupts its function. Standard treatments for PC such as surgical resection, chemotherapy, and radiotherapy. However, these therapies often face significant challenges, including biochemical recurrence and drug resistance.Given these limitations, new therapeutic approaches are being developed to target tumor metabolism. Dysregulation of cholesterol biosynthesis and alterations in fatty acids (FAs), such as palmitate, stearate, omega-3, and omega-6, have been observed in pancreatic cancer. These lipids serve as energy sources, signaling molecules, and essential components of cell membranes. Their accumulation fosters an immunosuppressive tumor microenvironment that supports cancer cell proliferation and metastasis.Moreover, lipid metabolism dysregulation within immune cells, particularly T cells, impairs immune surveillance and weakens the body’s defenses against cancer. Abnormal lipid metabolism also contributes to drug resistance in PC. Despite these challenges, targeting lipid metabolism may offer a promising therapeutic strategy. By enhancing lipid peroxidation, the induction of ferroptosis-a form of regulated cell death-could impair the survival of PC cells and hinder disease progression.

PMID:39806478 | DOI:10.1186/s12944-024-02426-0

J Health Popul Nutr. 2025 Jan 13;44(1):8. doi: 10.1186/s41043-025-00739-z.

ABSTRACT

BACKGROUND: Socioeconomic inequality in nutritional status as one of the main social determinants of health can lead to inequality in health outcomes. In the present study, the socioeconomic inequality in the burden of nutritional deficiencies among the countries of the world using Global Burden of Disease (GBD) data was investigated.

METHODS: Burden data of nutritional deficiencies and its subsets including protein-energy malnutrition, iodine deficiency, vitamin A deficiency, and dietary iron deficiency form GBD study and Human Development Index (HDI), a proxy for the socio-economic status of countries, from united nations database were collected. After descriptive statistics, the concentration index (CI) curve was used to measure socioeconomic inequality. CI for nutritional deficiencies was estimated based on Disability Adjusted Life Years (DALY), Years Lived with Disability (YLD), Years of Life Lost (YLL), prevalence, incidence and death indices. Moreover, CI of DALY and prevalence was estimated and reported for four nutritional deficiencies subgroups.

RESULTS: CIs for DALY, YLD, YLL, prevalence, incidence and death rate show negative values and their, which indicates the concentration of nutritional deficiencies burden among lower HDI countries. The highest value of CI (lowest inequality) for DALY was related to iodine deficiency (-0.3401) and the lowest (highest inequality) was related to vitamin A deficiency (-0.5884). Also, the highest value of CI for prevalence was related to protein-energy malnutrition (-0.1403) and the lowest was related to vitamin A deficiency (-0.4308). Results also show the inequality in DALY was greater than the disparity in prevalence for all subgroups of nutritional deficiencies.

CONCLUSIONS: Inequality in burden of nutritional deficiencies and protein-energy malnutrition, iodine deficiency, vitamin A deficiency and dietary iron deficiency are concentrated in countries with low HDI, so there is pro- poor inequality. Findings indicate that although malnutrition occurs more in low-income countries, due to the weakness of health care systems in these countries, the inequality in the final consequences of malnutrition such as DALY becomes much deeper. More attention should be paid to the development of prevention and primary treatment measures in low HDI countries, such as improving nutrition-related health education, nutritional support and early aggressive treatment, and also eliminating hunger.

PMID:39806471 | DOI:10.1186/s41043-025-00739-z

BMC Med Inform Decis Mak. 2025 Jan 13;25(1):18. doi: 10.1186/s12911-024-02848-x.

ABSTRACT

BACKGROUND: This systematic review aims to explore the early predictive value of machine learning (ML) models for the progression of gestational diabetes mellitus (GDM) to type 2 diabetes mellitus (T2DM).

METHODS: A comprehensive and systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science up to July 02, 2024. The quality of the studies included was assessed. The risk of bias was assessed through the prediction model risk of bias assessment tool and a graph was drawn accordingly. The meta-analysis was performed using Stata15.0.

RESULTS: A total of 13 studies were included in the present review, involving 11,320 GDM patients and 22 ML models. The meta-analysis for ML models showed a pooled C-statistic of 0.82 (95% CI: 0.79 ~ 0.86), a pooled sensitivity of 0.76 (0.72 ~ 0.80), and a pooled specificity of 0.57 (0.50 ~ 0.65).

CONCLUSION: ML has favorable diagnostic accuracy for the progression of GDM to T2DM. This provides evidence for the development of predictive tools with broader applicability.

PMID:39806461 | DOI:10.1186/s12911-024-02848-x