Tag: statistics

Discov Nano. 2026 Jul 17;21(1):348. doi: 10.1186/s11671-026-04808-y.

ABSTRACT

Nanobiomaterials have emerged as critical platforms for modern therapeutics, offering targeted delivery, controlled release, and improved performance. Among these, polymeric PLGA nanoparticles (PLGA-NPs) are widely studied due to their tailorability, biocompatibility, biodegradability, and regulatory acceptance. However, their clinical translation depends on robust manufacturing approaches that support scalability, reproducibility, and continuous manufacturing. Conventional methods, such as high-shear homogenization, suffer from limitations, including high energy input, process sensitivity, and contamination risk. This study presents a comprehensive experimental and statistical approach to systematically compare three PLGA-NPs preparation methods: high-shear homogenization (HSH), dual centrifugation (DC), and high-pressure homogenization (HPH). A full factorial Design of Experiments (DoE) combined with Response Surface Methodology (RSM) evaluated the effects of formulation and process parameters, including PVA and PLGA concentrations, homogenization speed, bead diameter, and pressure on Critical Quality Attributes (CQAs; particle size, polydispersity index, and zeta potential). HSH produced uniform nanoparticles with narrow size distribution but was highly process-sensitive. DC showed more variability in results, while HPH achieved consistent results. PVA concentration was the dominant factor across all methods. In conclusion, DC and HPH emerged as viable candidates for scalable nanoparticles manufacturing.

PMID:42463954 | DOI:10.1186/s11671-026-04808-y

Behav Res Methods. 2026 Jul 16;58(8):240. doi: 10.3758/s13428-026-03112-y.

ABSTRACT

Experience sampling via mobile devices enables unprecedented insights into daily life. However, individual studies often cannot answer research questions conclusively, and open data are scattered across repositories in different formats. This impedes research into robustness, generalizability, and heterogeneity. We address this issue by introducing openESM, an open-source database of openly available experience sampling datasets in a harmonized format. The growing database currently comprises 60 datasets with more than 16,000 participants and more than 740,000 observations. Metadata can be searched via our website ( openesmdata.org ) to select and download datasets via packages in R and Python. We demonstrate the potential of openESM through an analysis of within-person correlations of positive and negative affect in 39 datasets, providing evidence for a large negative momentary correlation ( $–0.49$ , 95% CI: [ $–0.54$ , $–0.42$ ]). We end by discussing the design principles that will allow openESM to become a continuously evolving community resource for cumulative experience sampling research.

PMID:42463898 | DOI:10.3758/s13428-026-03112-y

Commun Med (Lond). 2026 Jul 16. doi: 10.1038/s43856-026-01664-w. Online ahead of print.

ABSTRACT

BACKGROUND: Endophthalmitis is a blinding complication following any invasive ocular procedure, and historical treatment guidelines do exist but only for cataract surgery cases. To the best of our knowledge, no randomised controlled trial evidence exists to answer the question of early vitrectomy surgery for the treatment of endophthalmitis following any eye surgery.

METHODS: We conducted a multicentre, national prospective randomized controlled clinical (RCT) trial aimed to assess the feasibility of randomizing patients to an early vitrectomy (Arm-A) intervention within 48-96 hours compared to current standard patient care of repeated, immediate intravitreal antibiotic injection (Arm-B) and delayed vitrectomy. There was no blinding or masking conducted in the trial. The key inclusion criteria were: over 18 years of age; confirmed diagnosis of POE at any time-point following an ocular surgery, procedure, or injection; symptomatic visual loss attributable to POE; best corrected visual acuity (VA) worse than 35 ETDRS letters, including counting fingers, hand motions and perception of light vision. The key exclusion criteria were: known adverse reaction to intravitreal antibiotics (amikacin/vancomyin/cephalosporins); optic atrophy in study eye; corneal oedema or haze that would prevent visualisation of fundus to perform vitrectomy surgery. The primary outcome measure was, the feasibility and acceptability of carrying out a RCT of early surgical treatment compared to standard treatment for POE.

CLINICALTRIALS: gov NCT04522661 (13/08/2020).

RESULTS: Here we show that the study is feasible and meets the primary endpoint whereby 63 participants are randomized at 79% recruitment rate. Median change in VA (IQR) as per-protocol from baseline-to-week 24 was 40 (28-70) letters in Arm-A (n = 24) versus 13 (0-66) letters in Arm-B (n = 25); corresponding to a between-group difference of 24 letters, adjusted for baseline, in favour of early vitrectomy (p = 0.139). Higher rate of non-serious adverse events observed in Arm-B (68%) compared to Arm-A (47%), with higher incidence of retinal detachment 8 cases (24%) in Arm-B versus 2 cases in Arm-A (6.7%).

CONCLUSIONS: The EVIAN trial meets the primary endpoint demonstrating feasibility in conducting a trial to randomize the target population at multiple eye centres. Although not statistically significant, the effect on VA change indicates a potential meaningful benefit of vitrectomy compared to standard of care treatment, which can now be tested in a definitive phase 3 clinical trial.

PMID:42463897 | DOI:10.1038/s43856-026-01664-w

Commun Med (Lond). 2026 Jul 16;6(1):397. doi: 10.1038/s43856-025-01272-0.

ABSTRACT

BACKGROUND: Data science methods can provide novel and pragmatic approaches for preventing and controlling non-communicable diseases (NCDs) in Africa. This study highlights current efforts, opportunities, and challenges in leveraging data science methods to accelerate and advance the prevention and control of NCDs in Africa.

METHODS: We undertake a systematic review and gap analysis, as registered in PROSPERO (CRD42023406237).

RESULTS: Our findings suggest several data science methods have been used in research across the four leading NCDs in Africa. However, limited information exists on their application to improve disease surveillance, risk factor identification and characterization, prevention, treatment, drug discovery and rehabilitation. Machine learning outperforms traditional statistical methods in improving risk stratification in most studies (80.8%) designed for the prevention and control of NCDs. Notwithstanding, most (76.0%) data science techniques for NCDs prevention and control remain in the exploratory research phase, with limited clinical or public health application and minimal impact on the African population. There are critical gaps along the continuum of data generation, data quality, method development, and validation, which may be attributed to inadequate funding, capacity development, policy shortcomings, and infrastructure deficits. Considerable gaps exist in intra-African collaboration, data sharing, and replication, which hinder the cross-cultural replication and applicability of data science methods for NCDs prevention and control in Africa.

CONCLUSIONS: Multi-sectoral interventions that promote interdisciplinary capacity building, investment, and knowledge linkages, taking into account indigenous epistemologies, are needed to harness the enormous potential of data science to accelerate the prevention and control of NCDs in Africa.

PMID:42463895 | DOI:10.1038/s43856-025-01272-0

Sci Rep. 2026 Jul 16. doi: 10.1038/s41598-026-61836-5. Online ahead of print.

ABSTRACT

Cytokines play crucial roles in regulating immune cell interactions, and in influencing innate and adaptive immune responses. People living with HIV (PLWH) on antiretroviral therapy (ART) show reduced inflammation and immune activation but with partial immune recovery. Interactions between HIV and human coronaviruses (hCoVs), with respect to immune modulation and ART impact on immune recovery, are not well understood. In this case-control cross-sectional study, we investigated cytokine profiles among three groups: PLWH co-infected with hCoVs (HIV+/hCoVs+), HIV mono-infected individuals (HIV+/hCoVs-), and HIV-negative without hCoVs control group (HIV-/hCoVs). A total of 300 PLWH were screened for hCoVs in three hospitals by subjecting their nasopharyngeal and oropharyngeal swabs to RNA extraction and PCR. Sixty-seven (67) PLWH with hCoVs were age- and sex-matched with HIV mono-infected and HIV negative control groups, and plasma samples were collected to assess cytokine levels using a Luminex multiplex bead-based immunoassay. Lower cytokine levels were observed among the HIV co-infected and mono-infected groups compared to HIV-negative control group. Granzyme B, TNF-α, IL-17 A, IL-3, IL-15 and VEGF were significantly reduced in the HIV co-infected group. Participants who had been on ART for less than a year had higher TNF-α levels than those who had been on ART for more than 5 years. The study demonstrates that HIV co-infection with hCoVs is associated with significantly reduced levels of key cytokines, which may be due to immune dysregulation and/or exhaustion associated with chronic HIV infections. The cytokine phenotype may be mitigated with long-term ART, which reduces inflammation and promote immunological recovery.

PMID:42463885 | DOI:10.1038/s41598-026-61836-5

Br Dent J. 2026 Jul 16. doi: 10.1038/s41415-026-9809-1. Online ahead of print.

ABSTRACT

Aims To investigate how UK dental professionals use social media for professional learning, to identify associated learning needs, and to examine the opportunities and challenges this presents for continuing professional development (CPD).Methods A cross-sectional, mixed-methods online survey gathered 381 responses from UK-registered dentists and dental care professionals (DCPs). Quantitative data on demographics and platform use were analysed using descriptive statistics, chi-square tests, and multiple logistic regression. Qualitative free-text responses were analysed using reflexive thematic analysis.Results A total of 381 participants responded (294 DCPs, 77%; 87 dentists, 23%). Facebook, WhatsApp, and LinkedIn were the dominant platforms. A 37-percentage-point digital confidence gap existed between professionals under 30 (85% confident) and those over 60 (48%; χ²(3) = 28.45, p <0.001), with a 3.5:1 consumption-to-creation ratio indicating predominantly passive engagement. While 84% considered sources reliable, only 78% recognised the need for cross-checking. Three qualitative themes emerged: professional identity validation and learning recognition; community support and accessible learning; and reflective practice enhancement and critical awareness.Conclusions Social media constitutes a substantive informal learning ecosystem within UK dental professional practice, operating alongside the General Dental Council’s formal CPD framework but largely outside its recognition and quality assurance processes, while equity implications of the digital divide remain unmitigated. Successful integration of informal and formal learning pathways requires coordinated action from regulators, educational institutions, and professional associations to ensure all practitioners, regardless of age or digital confidence, engage with these networks safely, critically, and effectively.

PMID:42463878 | DOI:10.1038/s41415-026-9809-1

Sci Rep. 2026 Jul 16. doi: 10.1038/s41598-026-59344-7. Online ahead of print.

ABSTRACT

Software Defined Networking (SDN) provides programmability and centralized control, but at the same time, increases the attack surface and prevents classical Intrusion Detection Systems (IDSs) from dealing with new attack vectors. To solve these challenges, we propose NeuroTwin QIDS, a novel quantum-enabled neuro-IDS for SDN. It uses a novel Neuro-Symbolic Feature Pruning (NSFP) approach involving Graph Attention Networks (GAT) and policy-aware symbolic pruning to guarantee the statistical relevancy and defensibility of features used to represent anomalies. Statistical features representing anomalies are mapped to Quantum Reservoir (QRE) space in order to enrich representation for better temporal classification. Classification itself is implemented in two steps: firstly, the Quantum Reservoir-Transformer Hybrid (QRT-Net) performs online real-time binary anomaly detection; secondly, the Capsule Network-BiLSTM (Cap-BiLSTM) classifies anomalies based on their behavior. After that, neuro-symbolic fusion is performed to validate predictions made by the neural network against SDN policies, and a digital twin model is synchronized for simulation of protective actions to be taken before applying the self-healing mechanism for network protection. The experiments were carried out with CSE-CIC-IDS2018 and InSDN datasets to evaluate the end-to-end performance of NeuroTwin QIDS. NeuroTwin QIDS provided outstanding detection results, surpassing state-of-the-art IDS systems. On the CSE-CIC-IDS2018 dataset, it showed 99.12% accuracy, 98.95% precision, 98.87% recall rate, and a 98.91% F1-score. Similarly, on InSDN dataset, the performance of the proposed method was 98.67% accuracy, 98.42% precision, 98.15% recall, and a 98.28% F1-score.

PMID:42463875 | DOI:10.1038/s41598-026-59344-7

Sci Rep. 2026 Jul 16. doi: 10.1038/s41598-026-60291-6. Online ahead of print.

ABSTRACT

Bakery workers are frequently exposed to flour dust and fine particulate, which can contribute to respiratory symptoms and impaired lung function. In Abidjan, the growth of the bakery sector is increasingly exposing workers to high concentrations of fine particulate. This study aimed to assess respiratory symptoms, impaired lung function and associated occupational factors among bakery workers in Abidjan, Côte d’Ivoire. An analytical and descriptive cross-sectional study was conducted in 40 bakeries within the Autonomous District of Abidjan between February 2019 and January 2020. Data were collected using standardized questionnaires, spirometry tests, and air quality measurements by zone (Production Zone (ZP) and Sales Zone (ZV)).The data were analyzed using Stata version 15.1. Bivariate and multivariate logistic regression analyses were carried out to identify factors associated with impaired respiratory function and small airways syndrome (SAS). Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated, and statistical significance was set at p < 0.05. A total of 599 employees were included in the study, comprising bakers/pastry chefs (59.7%), sales clerks/cashiers (23.5%), cleaning staff (6.3%), and administrative personnel (10.2%). The mean age was 31 years, with a male-to-female ratio of 2.2, and the majority (88.8%) had less than five years of work experience. Bakers/pastry chefs and sales clerks spent more than 20 hours per day continuously at the workplace. The most common respiratory symptoms were nasal congestion (68.1%), runny nose (46.3%) and sneezing (41.4%). Some workers had impaired FEV1 values (20.9%) and abnormal FEV1/FVC ratios (17.5%). PM2.5 concentrations reached 320 µg/m³ in production areas and 290 µg/m³ in sales areas, representing a 21.3-fold and 19.3-fold increase, respectively, over the WHO guideline value. Respiratory symptoms and impaired lung function were significant (adjusted OR = 3.25; 95% CI: 2.05-5.16; p < 0.001) among workers in production areas. The prevalence of small airway syndrome was low (7.35%). Dry cleaning of floors [aOR = 6.3 (1.06-17.29)] and workbench cleaning [aOR = 4.70 (1.11-10.80)] were significant risk factors, whilst the use of kneading machines fitted with airtight lids was protective [aOR = 0.18 (0.04-0.72)]. Bakery workers in Abidjan experience substantial respiratory symptoms and lung function impairment associated with high occupational exposure to flour dust and PM₂.₅. Preventive occupational measures including improved ventilation, wet-cleaning procedures, respiratory protection, and dust-control systems are urgently needed. Small airways syndrome was identified in a smaller proportion of workers and may represent an early marker of occupational respiratory damage.

PMID:42463864 | DOI:10.1038/s41598-026-60291-6

Sci Rep. 2026 Jul 16. doi: 10.1038/s41598-026-62631-y. Online ahead of print.

ABSTRACT

This paper addresses the poor stability of near-ground flexible capture nets under uncertainty in the ambient wind. The capture net considered is a near-ground system for intercepting small low-altitude targets such as small UAVs or individuals; given its small scale (a 3.2 m net) and short deployment time (about 2 s), the wind can be treated as a quasi-steady flow during a single deployment, and the relevant uncertainty is characterized through the variability of the near-ground ambient mean wind speed. Focusing on the factors influencing the flight attitude of capture nets, a performance evaluation index model for flexible capture nets is established, enabling quantitative assessment of net performance, and a near-ground flexible capture net dynamics model is constructed. The Morris-Sobol method is employed to perform global sensitivity analysis on the factors affecting the effective range of flexible capture nets, revealing that environmental wind speed, ballistic mass, launch angle, and cord diameter are the primary factors influencing capture net performance. The Pareto-optimal non-dominated solution set is obtained using a Gaussian Process Regression (GPR) surrogate model solved via the Non-dominated Sorting Genetic Algorithm II (NSGA-II), followed by objective decision-making based on the Utopia point method. The robust design optimum is determined as m_b = 22.34 g, d = 0.370 mm, and theta = 28.9 deg. Finally, high-fidelity numerical simulations are conducted for verification. Compared with the empirical design parameters, the mean effective range increases by 9.02% (statistically significant), and the standard deviation of the deterministic design is 45.71% higher than that of the robust design.

PMID:42463848 | DOI:10.1038/s41598-026-62631-y

Sci Rep. 2026 Jul 16. doi: 10.1038/s41598-026-62649-2. Online ahead of print.

ABSTRACT

Isthmin-1, a recently identified adipokine implicated in endothelial dysfunction and inflammation, may play a role in acute coronary syndromes. However, its clinical relevance in ST-segment elevation myocardial infarction (STEMI) remains unclear. This study aimed to investigate serum Isthmin-1 levels in patients presenting with STEMI and to evaluate their association with short-term clinical outcomes. In this single-center prospective study, 123 patients with STEMI and 89 healthy controls were enrolled between December 2023 and May 2024. Serum Isthmin-1 levels were measured using ELISA at admission. Clinical characteristics and 24-hour mortality and 28-day major adverse cardiac events (MACE) were recorded. Prognostic performance for predicting 28-day MACE was assessed using ROC curve analysis. The mean age was 58.1 ± 12.0 years in the STEMI group and 51.6 ± 16.5 years in the control group. Median serum Isthmin-1 levels were significantly higher in patients with STEMI compared with controls (406.98 ng/mL [IQR: 360.63-549.53] vs. 371.16 ng/mL [IQR: 245.18-487.31]; p < 0.001). No statistically significant association was observed between Isthmin-1 levels and STEMI subtype, 24-hour mortality, or 28-day MACE. ROC analysis demonstrated no discriminatory ability of baseline serum Isthmin-1 levels for predicting 28-day MACE (AUC: 0.453; 95% CI: 0.323-0.582; p = 0.479), indicating that Isthmin-1 did not provide clinically useful short-term prognostic discrimination in this cohort. Although serum Isthmin-1 levels were elevated in patients with STEMI, baseline concentrations were not associated with short-term mortality or 28-day MACE and demonstrated no discriminatory ability for predicting short-term adverse outcomes. These findings suggest that Isthmin-1 may reflect acute ischemic and inflammatory responses rather than serving as a clinically useful short-term prognostic biomarker.

PMID:42463837 | DOI:10.1038/s41598-026-62649-2