Nevin Manimala

Sci Rep. 2025 Aug 23;15(1):31039. doi: 10.1038/s41598-025-15292-2.

ABSTRACT

The increasing reliance on Human-centric Internet of Things (H-IoT) systems in healthcare and smart environments has raised critical concerns regarding data integrity, real-time anomaly detection, and adaptive access control. Traditional security mechanisms lack dynamic adaptability to streaming multimodal physiological data, making them ineffective in safeguarding H-IoT devices against evolving threats and tampering. This paper proposes a novel trust-aware hybrid framework integrating Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) models, and Variational Autoencoders (VAE) to analyze spatial, temporal, and latent characteristics of physiological signals. A dynamic Trust-Aware Controller (TAC) is introduced to compute real-time trust scores using anomaly likelihood, context entropy, and historical behavior. Access decisions are enforced via threshold-based logic with a quarantine mechanism. The system is evaluated on benchmark datasets and proprietary H-IoT signals under diverse attack and noise scenarios. Experiments are conducted on edge devices including Raspberry Pi and Jetson Nano to assess scalability. The proposed framework achieved an average F1-score of 94.3% for anomaly detection and a 96.1% accuracy in access decision classification. Comparative results against rule-based and statistical baselines showed a 12-18% improvement in detection sensitivity. Real-time inference latency was maintained under 160 ms on edge hardware, validating feasibility for critical H-IoT deployments. Trust scores exhibited high stability under adversarial data fluctuations. This research delivers a scientifically grounded, practically scalable solution for adaptive security in H-IoT networks. Its novel fusion of deep learning and trust modeling enhances both responsiveness and resilience, paving the way for next-generation secure health and wearable ecosystems.

PMID:40849566 | DOI:10.1038/s41598-025-15292-2

Biol Trace Elem Res. 2025 Aug 23. doi: 10.1007/s12011-025-04795-8. Online ahead of print.

ABSTRACT

This study aimed to determine the levels of lead (Pb) and cadmium (Cd) in orange juice samples collected from various markets in Rabat (Morocco), using graphite furnace atomic absorption spectrometry (GF-AAS), and to evaluate the risk posed to consumer health. Pb was detected in 58% of samples, with concentrations ranging from 0.009 to 0.047 mg/kg and an average of 0.024 mg/kg. The incidence rates were 81.8% in pure juices, 70% in nectars, and 90% in juice concentrates. Five samples (16%) exceeded the maximum authorized limit for Pb (0.03 mg/kg) according to the standards of the European Commission, the Codex Alimentarius, and the Moroccan authorities. In the case of Cd, it was detected in 74.2% of samples, with levels ranging from 0.014 to 0.041 mg/kg (average: 0.025 mg/kg). Although no specific regulatory limit has been set for Cd in juices, the concentrations observed greatly exceeded the United States Environmental Protection Agency (US EPA) reference (0.005 mg/L) for drinking water. The non-carcinogenic risk assessment, based on hazard quotient (HQ) and hazard index (HI) values, revealed values of less than 1, indicating no significant long-term health risk. On the other hand, the carcinogenic risk (CR) and total carcinogenic risk (TCR) values for Cd exceeded the acceptable threshold of 1 × 10^-5 according to Health Canada recommendations, suggesting a potential cancer risk in the event of chronic exposure. Statistical analyses were performed using R software, including box and whisker plots to visualize the distribution and variability of heavy metals in orange juices. These results underscore the importance of ongoing monitoring and the establishment of suitable regulatory thresholds for trace elements in orange juice.

PMID:40849555 | DOI:10.1007/s12011-025-04795-8

Int J Obes (Lond). 2025 Aug 23. doi: 10.1038/s41366-025-01884-5. Online ahead of print.

ABSTRACT

BACKGROUND: Endothelial progenitor cells (EPCs) play an important role in angiogenic responses in multiple tissues and mediate a coordinate augmentation of the capillary network as adipose tissue (AT) expands in response to positive energy balance. However, the isolation and culture of EPCs from human AT has proven difficult so far. Here, we report the isolation and characterization of EPCs from human AT (AT-EPCs).

METHODS: Omental and subcutaneous AT specimens (approximately 1-2 g) were obtained during abdominal surgery. Following AT digestion with collagenase, both the filtered (SVF-I) and unfiltered (SVF-II) stromal vascular fractions (SVF) of AT were used. Expression of endothelial markers, such as CD31 and VE-Cadherin, was analyzed by using flow cytometry. Both SVF-I and SVF-II fractions were used for magnetic-based enrichment of endothelial cells using anti-human CD31 beads. Immunofluorescence staining, immunoblotting, and quantitative real-time PCR were performed to analyze expression of endothelial markers. Functional assays, including matrigel-based capillary-like tube formation assay and acetylated LDL uptake assays, were also performed.

RESULTS: CD31 and VE-Cadherin were more expressed in SVF-II than SVF-I. CD31+ cells from SVF-II exhibited an endothelial-like cobblestone morphology. The CD31+ fraction also expressed Von Willebrand Factor (vWF) and VE-Cadherin. High mRNA levels of E-selectin, e-NOS, VEGFR, and CD34 were found in CD31+ cells, and E-selectin and e-NOS proteins were readily detectable. In addition, CD31+ cells were able to form tubes and incorporate acetylated LDL in vitro.

CONCLUSIONS: Large amounts of AT-EPCs with distinct functional properties can be isolated from omental and subcutaneous adipose tissue.

PMID:40849547 | DOI:10.1038/s41366-025-01884-5

Sci Rep. 2025 Aug 23;15(1):31032. doi: 10.1038/s41598-025-15430-w.

ABSTRACT

Multiple Sclerosis (MS), an autoimmune disorder, is characterized by severe neuroinflammation, leading to demyelination and neuronal damage in the CNS, resulting in significant clinical impairment. MS progression involves complex pathological processes like immune cell invasion and cytokine-mediated recruitment to the CNS. Experimental autoimmune encephalomyelitis (EAE), widely used as a model for MS, despite its translational limitations, has been crucial for identifying effective treatments. Recent studies have shown that sodium channel (NaV) blockers and monoamine oxidase- (MAO) B inhibitors can alleviate symptoms of EAE and optic neuritis (ON), but their mode of action remains partially unclear. To evaluate the effects and understand the action mechanism of NaV blockers and MAO-B inhibitors (rasagiline, safinamide, flecainide and phenytoin) in neurological conditions, various techniques were used, including optical coherence tomography (OCT), optomotor response measurement (OMR), flow cytometry, histological evaluations, Evans blue assay, blood-brain barrier (BBB) permeability assay, western blot, proliferations assay, and gene expression analyses. The study found that the primary therapeutic effect comes from inhibiting the NaV 1.5 sodium channel, not MAO-B inhibition. Flecainide, a NaV 1.5 channel blocker, significantly reduced EAE disability scores, mitigated neurodegeneration, preserved visual function, and restricted immune cell migration into the CNS. Importantly, blocking the NaV 1.5 channel had an effect on the BBB, limiting lymphocyte entry into the CNS. This research highlights sodium channel blockers’ potential in treating EAE. The findings demonstrate induced neuroprotection and reduced disease progression, suggesting a novel therapeutic approach. Crucially, it reveals for the first time that NaV 1.5 channel blockade leads to neuroprotection primarily by affecting the BBB, a key factor in controlling immune cell migration, thus addressing a critical aspect of neuroinflammation.

PMID:40849530 | DOI:10.1038/s41598-025-15430-w

Radiol Med. 2025 Aug 23. doi: 10.1007/s11547-025-02062-3. Online ahead of print.

ABSTRACT

PURPOSE: This study sought to investigate the presence of residual myocardial hyperemia on the recovery phase in patients undergoing stress CMR.

MATERIAL AND METHODS: Fifty patients with clinical indication for stress CMR underwent quantitative perfusion imaging in resting conditions, after regadenoson-induced hyperemia (400 mcg, 5 mL), and 10 min after recovery with euphylline. Studies showing hypoperfusion due to ischemia and/or prior myocardial infarction were excluded. Global myocardial blood flow during rest (MBF_rest), stress (MBF_stress) and recovery (MBF_recovery) and MPR indices (MPR_stress/rest and MPR_{stress/recovery}) were calculated using automated pixel-wise quantitative myocardial perfusion mapping.

RESULTS: A total of 30 patients (22 males, mean age of 62.7 ± 1 years) were included in the analysis. Global MBF_rest and MBF_stress were 0.83 ± 0.2 mL/g/min and 2.1 ± 0.6 mL/g/min, respectively. After recovery with euphylline, myocardial perfusion did not return to the resting values (MBF_recovery of 0.92 ± 0.3 mL/g/min) and statistically differed from MBF_rest (p < 0.01), suggesting residual myocardial hyperemia. This resulted in an abnormally low MPR_{stress/recovery} (2.43 ± 0.7) with respect to MPR_stress/rest (2.56 ± 0.7) (p = 0.03). A linear mixed-effects model accounting for repeated measures revealed statistically significant group differences over time in global MBF (mean difference 0.1, 95% CI 0.02-0.17, p = 0.01) and global MPR (mean difference -0.13, 95% CI -0.25 to -0.02, p = 0.02).

CONCLUSION: Despite the use of euphylline to counteract the vasodilator effect, MBF does not completely revert to resting values and MBF_recovery cannot be used as a substitute for MBF_rest when regadenoson is used. Consequently, a rest/stress protocol is advised for quantitative CMR perfusion to obtain accurate MBF and MPR parameters.

PMID:40848227 | DOI:10.1007/s11547-025-02062-3

Int Ophthalmol. 2025 Aug 23;45(1):348. doi: 10.1007/s10792-025-03730-z.

ABSTRACT

PURPOSE: Glaucoma and cataract are the most frequent causes of blindness worldwide with very distinct etiology and pathogenesis. Sleep disturbances have been reported in both conditions with their etiology attributed not only to the particular underlying eye condition but to other comorbid conditions such as chronic diseases and old age. This study compares sleep quality in fifty primary open-angle glaucoma patients and fifty cataract patients of similar vision loss in order to determine the comparative impact of those eye disorders in sleep quality.

METHODS: The glaucoma patients group was comprised of 50 patients with bilateral primary open-angle glaucoma, of moderate stage (38 men and 12 women, mean age = 62.94 years, SD = 4.99 years). The cataract patient group was comprised of 50 gender-matched cataract patients with either cortical sclerotic or posterior sclerotic types of cataracts (mean age = 62.38 years, SD = 4.62 years). All cataract patients were receiving a pre-surgery evaluation at the time of the study and had cataract involvement of both eyes that necessitated cataract surgery. All patients were administered the Pittsburgh Sleep Quality Index (PSQI), a self-administered questionnaire designed to subjectively evaluate sleep quality over the preceding month, and their findings were statistically compared.

RESULTS: Both groups had overall poor sleep quality but the glaucoma patients had worse PSQI total scores (p = .042), higher sleep latency (p = .005) and sleep disturbance (p = .002).

CONCLUSION: Those findings suggest that among patients with comparable vision loss, glaucoma patients may be even more severely affected with disordered sleep than cataract patients. There is a need for the creation and testing of treatment modalities for chronodisruption in both patient groups.

PMID:40848200 | DOI:10.1007/s10792-025-03730-z

Carbon Balance Manag. 2025 Aug 23;20(1):34. doi: 10.1186/s13021-025-00313-4.

ABSTRACT

Agricultural greenhouse gas emissions on the planet threaten both food security and climate change. The United Nations is calling for food security and sustainable agriculture to end hunger by 2030. Sustainable Development Goal 2.4 addresses resilient agricultural practices to combat climate change and produce sustainable food. Resilient agricultural practices are only possible with agricultural technologies (AgriTech) that will create a digital transformation in agriculture. AgriTech can meet the increasing food demand by increasing production efficiency while increasing resource efficiency by combating problems such as climate change and water scarcity. The aim of this study is to examine the impacts of AgriTech usage on sustainable agriculture in Sub-Saharan African (SSA) countries. The analyses were conducted using panel data from 20 SSA countries between 2000 and 2022. In this study, MMQR (Method of Moments Quantile Regression) provided consistent results across quantiles in variable interactions, while GMM (Generalized Method of Moments) and KRLS (Kernel Regularized Least Squares Method) approaches were used to ensure consistency of results. The findings confirm that AgriTech (ATECH) and agricultural value added (AGRW) contribute significantly to sustainable agriculture in SSA countries. The coefficients of ATECH and AGRW variables are negative and statistically significant in all quantiles. This shows that when AgriTech use and agricultural value added increase in SSA, emissions from agriculture decrease and the environment improves. However, agricultural credits (ACRD) are insufficient to reduce agricultural emissions. Furthermore, agricultural workers (AEMP) and internet use (INT) help reduce agricultural emissions up to the 60th and 50th quantiles, while this effect disappears at higher quantile levels. These results emphasize the importance of integrating green procurement and green production technologies supported by green credits into agricultural production in order to achieve sustainable agricultural development goals in SSA. Policies that facilitate farmers’ access to agricultural green credits should be adopted in SSA societies. Infrastructure works that will increase farmers’ access to the internet should be increased. Awareness of agricultural workers on green production and sustainability should be provided to agricultural workers.Highlights. The results show that agricultural technologies, agricultural growth, agricultural labor, and internet use reduce agricultural emissions in SSAcountries, while credit use increases agricultural emissions. AgriTech use (ATECH) and agricultural value-added (AGRW) have statistically significant negative coefficients in all quantiles, indicating that increasing AgriTech and value-added reduce agricultural greenhouse gas emissions. The potential of AgriTech to reduce emissions is higher in low-emission quantiles (10-30%), while the effect is relatively weaker in high-emission quantiles. Agricultural credits (ACRD) only provide environmental improvements in the low-emission quantile (25%) and are insufficient to reduce emissions in high quantiles. Agricultural labor (AEMP) and internet use (INT) significantly reduced emissions at 10-50% quantiles, while this effect disappeared at higher quantiles. Farmers’ success in reducing emissions is directly dependent on their internet access. Panel instantaneous momentum quantile regression (MMQR) was preferred to capture heterogeneous interactions, and the robustness of the results was confirmed with the GMM and KRLS approaches.

PMID:40848194 | DOI:10.1186/s13021-025-00313-4

Mol Diagn Ther. 2025 Aug 23. doi: 10.1007/s40291-025-00805-6. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Colorectal cancer remains a major global health challenge, necessitating the development of accurate non-invasive diagnostic tools. Circulating and excretory microRNAs (miRNAs) are promising biomarkers owing to their stability and regulatory roles in tumorigenic pathways. While single miRNA assays often lack sufficient diagnostic accuracy, panels combining multiple miRNAs have shown enhanced performance. This systematic review and meta-analysis evaluated the diagnostic accuracy of multi-miRNA panels and explored their mechanistic relevance to colorectal cancer pathogenesis.

METHODS: A comprehensive search of PubMed, Embase, Web of Science, and Scopus was conducted through March 2025 following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The study protocol was registered with PROSPERO (CRD420251060655). Eligible studies assessed the diagnostic accuracy of multi-miRNA panels for colorectal cancer using extractable data on sensitivity, specificity, and area under the curve. Data were extracted independently by two reviewers. A bivariate random-effects model was used to calculate pooled diagnostic estimates. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool, and heterogeneity was evaluated using I² statistics. Subgroup analyses were conducted by sample type (e.g., plasma, serum, stool) and panel size. Target genes of recurrent miRNAs were mapped to canonical colorectal cancer-related pathways.

RESULTS: Twenty-nine studies comprising 5497 participants (3070 colorectal cancer cases and 2427 controls) and 35 multi-miRNA panels were included. Pooled sensitivity was 0.85 (95% confidence interval 0.80-0.88), specificity was 0.84 (95% confidence interval 0.80-0.88), and the area under the curve was 0.90, despite substantial heterogeneity (I² > 77%). Panels derived from plasma samples showed the highest balanced performance (sensitivity 0.88; specificity 0.87), while three-miRNA panels exhibited the best diagnostic trade-offs. Mechanistic analysis of 42 recurrent miRNAs revealed consistent involvement in key colorectal cancer pathways, including PI3K/AKT, Wnt/β-catenin, epithelial-mesenchymal transition, angiogenesis, and immune regulation.

CONCLUSIONS: Multi-miRNA panels derived from diverse biospecimen sources demonstrate high diagnostic accuracy for colorectal cancer and are mechanistically linked to fundamental oncogenic pathways. Future efforts should focus on panel standardization, biospecimen-specific validation, and integration into clinical workflows to advance precision oncology.

PMID:40848187 | DOI:10.1007/s40291-025-00805-6