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Nevin Manimala Statistics

Efficacy & safety of brolucizumab 6.0 mg versus 3.6 mg in diabetic macular edema

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

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Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study

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

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Prophage-DB: a comprehensive database to explore diversity, distribution, and ecology of prophages

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

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Insights into the lemon (Citrus limon) epiphytic microbiome: impact of the biocontrol yeast Clavispora lusitaniae 146

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

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Targeting lipid metabolism: novel insights and therapeutic advances in pancreatic cancer treatment

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

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Socio-economic inequality in the nutritional deficiencies among the world countries: evidence from global burden of disease study 2019

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

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Predictive value of machine learning for the progression of gestational diabetes mellitus to type 2 diabetes: a systematic review and meta-analysis

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

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Boswellic acid synergizes with low-dose ionizing radiation to mitigate thioacetamide-induced hepatic encephalopathy in rats

BMC Pharmacol Toxicol. 2025 Jan 13;26(1):6. doi: 10.1186/s40360-024-00831-w.

ABSTRACT

Hepatic encephalopathy (HE) is a syndrome that arises from acute or chronic liver failure. This study was devised to assess the impact of a combination of boswellic acid (BA) and low doses of gamma radiation (LDR) on thioacetamide (TAA)-induced HE in an animal model. The effect of daily BA treatment (175 mg/kg body weight, for four weeks) and/or fractionated low-dose γ-radiation (LDR; 0.25 Gy, twice the total dose of 0.5 Gy) was evaluated against TAA (200 mg/kg, intraperitoneal) twice-weekly for four weeks to induce liver damage and HE in rats. TAA-exposed rats exhibited a significant elevation in serum activities of liver enzymes (GGT, ALP) and plasma ammonia levels at P < 0.05 (Duncan’s test) compared to the control group. Moreover, there was an increase in the levels of proinflammatory cytokines (IL6, IL12, IL18) in the TAA-exposed animals accompanied by a depletion in the activities of paraoxonase-1 and neurotransmitter contents compared with normal control rats (P < 0.05). However, the administration of BA alone or in combination with LDR led to improvements in liver and brain parameter indices. Furthermore, the histopathological assessments of liver and brain tissues supported the findings of the biochemical investigations. From the statistical analysis, it can be concluded that the combined administration of BA and exposure to LDR may possess potential hepatoprotective effects against hepatic encephalopathy-associated hyperammonemia and the consequent damage to the liver and brain. This study proposes that a combination of therapeutic approaches, LDR and BA could be a new therapeutic candidate for the management of hepatic encephalopathy.

PMID:39806460 | DOI:10.1186/s40360-024-00831-w

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Strengthening research preparedness for crises: lessons from Norwegian government agencies in using randomized trials and quasi-experimental methods to evaluate public policy interventions

Health Res Policy Syst. 2025 Jan 13;23(1):8. doi: 10.1186/s12961-024-01271-y.

ABSTRACT

During public health crises such as pandemics, governments must rapidly adopt and implement wide-reaching policies and programs (“public policy interventions”). A key takeaway from the coronavirus disease 2019 (COVID-19) pandemic was that although numerous randomized controlled trials (RCTs) focussed on drugs and vaccines, few policy experiments were conducted to evaluate effects of public policy interventions across various sectors on viral transmission and other consequences. Moreover, many quasi-experimental studies were of spurious quality, thus proving unhelpful for informing public policy. The pandemic highlighted the need to continuously develop competence, capacity and a robust legal-ethical foundation for impact evaluations well before crises occur. It raised a crucial question: how can governments in non-crisis times develop capabilities to generate evidence on the effects of public policy interventions, thus enabling a rapid and effective research response during public health crises? We conducted a mapping to explore how government agencies in Norway use RCTs and quasi-experimental methods to strengthen the evidence base for public policy interventions and to identify barriers and facilitators to their use. Contributing to the study were 10 government agencies across sectors such as development assistance, education, health, social welfare, statistics and taxation. Many of these agencies have conducted or commissioned RCTs or quasi-experimental studies in the past 5 years, with evaluations ranging from 1 or 2 to more than 15 per agency. The measures evaluated included organizational, educational and financial interventions and interventions for oversight and sanctions. Some agencies have internal capabilities for designing and conducting evaluations, while others commissioned such studies to universities and other research institutions. Agencies reported examples where enhanced communication among implementers, researchers, ministries and political leaders facilitated impact evaluations, and these lessons offer opportunities for cross-sector knowledge-sharing to help strengthen rigorous evaluations of public policy interventions. Despite their potential, various government agencies report that randomized and quasi-experimental studies face legal, ethical, political and practical barriers that affect their use. For instance, the urgency of politicians to implement policies at scale has led to the discontinuation of trials and hindered learning from their effects. The surveyed agencies stressed the importance of legislation providing clear guidelines on when differential treatment can be justified and when informed consent requirements can be waived, as well as faster and clearer processes for managing privacy concerns related to data access. Crucially, greater political acceptance for systematically and gradually implementing reforms, including using randomization, could strengthen evidence-informed public policy, enhancing the scaling-up of effective interventions and deprioritizing ineffective ones.

PMID:39806454 | DOI:10.1186/s12961-024-01271-y

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Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding-based methodology

J Cheminform. 2025 Jan 13;17(1):4. doi: 10.1186/s13321-025-00946-0.

ABSTRACT

Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode. Fragmenstein either takes the atomic coordinates of ligands from a experimental fragment screen and combines the atoms together to produce a novel merged virtual compound, or uses them to predict the bound complex for a provided molecule. The molecule is then energy minimised under strong constraints to obtain a structurally plausible conformer. The code is available at https://github.com/oxpig/Fragmenstein .Scientific contributionThis work shows the importance of using the coordinates of known binders when predicting the conformation of derivative molecules through a retrospective analysis of the COVID Moonshot data. This method has had a prior real-world application in hit-to-lead screening, yielding a sub-micromolar merger from parent hits in a single round. It is therefore likely to further benefit future drug design campaigns and be integrated in future pipelines.

PMID:39806443 | DOI:10.1186/s13321-025-00946-0