Nevin Manimala

Commun Biol. 2025 Nov 27. doi: 10.1038/s42003-025-09234-x. Online ahead of print.

ABSTRACT

Membrane proteins are crucial in cellular processes like signal and energy transduction and are influenced by the properties of the surrounding lipid bilayer. Fatty acids, key components of phospholipids, adjust membrane properties in response to environmental changes; however, their direct effect on membrane protein activity is poorly understood. Cyclopropane fatty acids (CFAs) are produced by a cyclopropane fatty acid synthase (Cfa) by adding a methylene group to unsaturated fatty acids. CFAs are abundant in the membranes of Escherichia coli, particularly during the stationary phase or stress conditions, and are believed to contribute to modulating membrane rigidity and permeability, yet their functional role in membrane protein regulation remains unclear. Here, we examined the effect of CFAs on the activity of NhaA, a Na⁺/H⁺ antiporter in E. coli, using Δcfa mutants deficient in CFA synthesis. NhaA activity exhibits a strong negative correlation with the ratio of cyclopropane to saturated fatty acids. Molecular dynamics simulations showed that CFA reduces NhaA-phospholipid interactions, restricting the conformational change needed for activation. These results suggest that membrane protein activity can be regulated by fatty acid composition, with CFAs playing a significant role.

PMID:41310198 | DOI:10.1038/s42003-025-09234-x

Sci Rep. 2025 Nov 27. doi: 10.1038/s41598-025-29168-y. Online ahead of print.

ABSTRACT

Deoxyribonucleic acid cryptography is a biologically inspired approach characterized by low computational complexity. It employs biological principles to create cryptographically strong ciphers, making it particularly suitable for protecting sensitive data on resource-constraints devices. However, the existing literature lacks solutions for securing authentication mechanisms tailored for these resource-constrained devices. To bridge this gap, the current study proposes a novel authentication design rooted in deoxyribonucleic acid cryptography, namely omega deoxyribonucleic acid cryptography key-based authentication. The proposed omega deoxyribonucleic acid cryptography-based authentication method aligns with contemporary standards for cryptographic systems and delivers a security level quantified at 256 bits of complexity. To validate its resilience, one tests the collision resistance of the proposed authentication mechanism using the standard Dieharder statistical test suite, where the mechanism successfully passes the collision resistance test. Additionally, the proposed scheme is mathematically proven secure against existential forgery under a chosen message attack.

PMID:41310192 | DOI:10.1038/s41598-025-29168-y

Commun Med (Lond). 2025 Nov 27. doi: 10.1038/s43856-025-01264-0. Online ahead of print.

ABSTRACT

BACKGROUND: Renal cell carcinoma is one of the most common cancers of the urinary tract and is usually diagnosed by interpreting contrast-enhanced computed tomography scans. Rising demand for radiological services, combined with a shortage of radiologists, makes timely and accurate diagnosis increasingly challenging. Automated approaches may help radiologists improve efficiency and accuracy.

METHODS: We developed BMVision, a deep learning-based tool for detecting and characterizing kidney cancer. The tool integrates with a web-based viewer designed to provide an intuitive interface for radiologists. Its performance was evaluated in a two-stage retrospective reader study. Six radiologists independently reviewed 200 scans across both AI-assisted and unaided workflows, allowing comparison of diagnostic performance and workflow efficiency with and without support from the tool. Statistical analysis compared AI-aided and unaided workflows across predefined clinical criteria, including diagnostic sensitivity, lesion measurement, reporting efficiency, and inter-radiologist agreement, using non-parametric tests and bootstrapping.

RESULTS: Here we show that BMVision reduces radiologists’ reporting time by an average of 33%, up to 52%. The tool provides structured auto-generated reports, minimizing the need for manual dictation or typing. In addition, BMVision improves sensitivity for detecting benign renal lesions (from 79.9 to 86.3%) and leads to a significant increase in inter-radiologist agreement.

CONCLUSIONS: To the best of our knowledge, BMVision is the first clinically validated commercial artificial intelligence tool for kidney cancer detection and characterization. By improving diagnostic accuracy and reporting efficiency, it has the potential to enhance patient care and help radiologists meet the growing demand for high-quality cancer diagnostics.

PMID:41310187 | DOI:10.1038/s43856-025-01264-0

Ambio. 2025 Nov 27. doi: 10.1007/s13280-025-02278-7. Online ahead of print.

ABSTRACT

Community-based forest management (CBFM) is widely promoted as a strategy that links forest management with local livelihoods through participatory governance. This global review used novel systematic review methods to evaluate predictors of people’s participation in CBFM. Based on 66 cases from 47 studies across 18 countries, we identified 248 predictors that have been used to explain people’s participation in CBFM and categorized them into seven broad categories. While demographics, household size, and landholding size are the most frequently tested, factors such as off-farm household income, leadership style, and forest condition are less commonly tested yet more often statistically significantly related to participation in CBFM. The meta-regression revealed that the specific type of CBFM (the institutional model) moderates the effects of certain predictors. These results highlight the multifaceted and context-specific drivers of participation in CBFM, underscoring the need for both household- and community-level strategies to foster effective forest governance.

PMID:41310143 | DOI:10.1007/s13280-025-02278-7

Eur Radiol. 2025 Nov 28. doi: 10.1007/s00330-025-12186-9. Online ahead of print.

ABSTRACT

OBJECTIVES: Atherosclerotic carotid artery disease (CarAD) is a significant contributor to the global burden of cerebrovascular diseases. Several positron emission tomography computed tomography (PET/CT) radiotracers showed promising results in identifying and assessing vulnerable carotid atherosclerotic plaque. This review aims to assess the current evidence surrounding the use and potential of multiple PET radiotracers in identifying vulnerable carotid atherosclerotic plaque.

MATERIALS AND METHODS: A scoping review of the literature was conducted for original peer-reviewed articles of PET studies published between 2010 and 2024 that used ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG), ¹⁸F-sodium fluoride (¹⁸F-NaF), ¹⁸F-fluoromisonidazole (¹⁸F-FMISO), ⁶⁸Ga-DOTATATE, ⁶⁸Ga-Pentixafor, and ¹¹C-Acetate for the evaluation of vulnerable carotid atherosclerotic plaque. The Covidence platform facilitated the screening of articles and data extraction.

RESULTS: 37 studies matched the inclusion criteria. Seven (19%) included serial dual-tracer PET/CT with ¹⁸F-FDG/¹⁸F-NaF, ¹⁸F-FDG/¹⁸F-FMISO, ¹⁸F-FDG/⁶⁸Ga-DOTATATE, and ¹⁸F-FDG/⁶⁸Ga-Pentixafor. The remaining studies used PET/CT ¹⁸F-FDG (N = 26, 70%), ¹⁸F-NaF (N = 2, 5%), 11C-Acetate (N = 1, 3%) and ⁶⁸Ga-DOTATATE (N = 1, 3%). Substantial variation in PET/CT acquisition parameters such as uptake time (min) [¹⁸F-FDG: 50-180, ¹⁸F-NaF: 60-180, and ⁶⁸Ga-DOTATATE: 60-120], radiotracer dose (MBq) [¹⁸F-FDG: 185-555, ¹⁸F-NaF: 125-370] and analysis methods [target-to-background ratio and/or standardised uptake values] were observed with no clear consensus on what constitutes a standard approach for carotid plaque evaluation using PET/CT.

CONCLUSION: The use of multiple PET radiotracers may provide novel diagnostic insights into the diagnosis of CarAD and improve the identification of vulnerable carotid atherosclerotic plaque. However, protocol heterogeneity affects reproducibility, necessitating standardised imaging parameters and histological validation to enable future clinical use of PET for CarAD assessment.

KEY POINTS: Question Conventional atherosclerotic plaque assessments, focusing on vessel occlusion, lack predictive power for vulnerable carotid atherosclerotic plaque. Can multi-radiotracer PET/CT, targeting plaque metabolic processes, address this? Findings Multi-radiotracer PET/CT demonstrates promising potential in detecting vulnerable carotid atherosclerotic plaque, but variability in data acquisition and analysis methods persists. Clinical relevance This review shows that multi-radiotracer PET/CT may provide novel diagnostic insights for detecting vulnerable carotid atherosclerotic plaque, potentially enhancing risk assessment and identifying patients at higher risk of cerebrovascular events.

PMID:41310133 | DOI:10.1007/s00330-025-12186-9

Gait Posture. 2025 Nov 22;124:110062. doi: 10.1016/j.gaitpost.2025.110062. Online ahead of print.

ABSTRACT

INTRODUCTION: Knee osteoarthritis (KOA) can alter gait biomechanics and neuromuscular activity. Valgus brace (VB) treatment aims to reduce medial compartment loading. While the mechanical efficacy of VBs is well-documented, their effect on neuromuscular deviations in KOA patients remains unclear. This study assesses the potential of VB to modulate altered muscle synergy activation patterns in KOA patients.

METHODOLOGY: Forty participants (twenty KOA, twenty age-matched controls) performed five locomotion tasks: overground walking, ramp and stair ascent / descent. Trials with and without VB were conducted at baseline and after six weeks of regular brace use. Muscle synergies were calculated based on electromyographic data of eight lower limb muscles per side. Inverse dynamics were calculated using marker-based motion capture data. A statistical parametric mapping three-way ANOVA with the factors group affiliation, brace condition, and measurement time point was conducted for each task.

RESULTS: Four synergies were identified across groups, tasks, brace conditions, and time points. The KOA cohort exhibited increased knee flexor synergy activity during early- to mid-stance, increased sagittal trunk flexion, increased hip flexion angles and moments, and decreased knee flexion angles and moments. Brace condition and time point had no effect on synergy activity or sagittal joint moments.

DISCUSSION AND CONCLUSION: Persistently increased hip flexion moments in the KOA group, possibly caused by increased sagittal trunk flexion, appeared to drive elevated activity of the biarticular knee flexor synergy. Increased knee flexor synergy activity can result in elevated knee joint contact forces, potentially aggravating KOA progression. Rather than being caused solely by the need for local stability, increased knee flexor synergy activity may be driven by altered trunk dynamics, which remained unaffected throughout the brace intervention.

PMID:41308271 | DOI:10.1016/j.gaitpost.2025.110062

Physiotherapy. 2025 Sep 9;130:101841. doi: 10.1016/j.physio.2025.101841. Online ahead of print.

ABSTRACT

OBJECTIVES: Behaviour change interventions may support physical activity behaviour in people with chronic respiratory disease. The most effective interventions for long-term physical activity behaviour change in this cohort remains unclear. This aim of this study was to explore the use and perceptions of behaviour change interventions by both providers of physical activity programmes for people with chronic respiratory disease and by people living with chronic obstructive pulmonary disease (COPD) in The Republic of Ireland.

DESIGN: Two anonymous online and paper-copy cross-sectional surveys, piloted and mapped to the COM-B model of behaviour change, were distributed via social media and relevant gate-keepers (e.g Irish Society of Chartered Physiotherapists, COPD Support Ireland) between November 2023 and April 2024. Findings were summarised using descriptive statistics including frequencies, percentages, means and medians. Relationships between variables were investigated using Chi² (p = 0.05).

RESULTS: The response rate to the provider survey was 71% (107/150), and 112 participants responded to the COPD cohort survey. Providers perceived encouragement, pertaining to theoretical constructs such as self-confidence, optimism and reinforcement to be the most effective techniques influencing physical activity behaviour. People with COPD perceived social support, pertaining to theoretical constructs such as interpersonal skills and social identity, to be the most effective interventions influencing their physical activity behaviour. Motivation was frequently identified as a common COM-B component, suggesting important links to this mechanism of action in influencing behaviour.

CONCLUSIONS: Interventions with motivational components are perceived as effective influencers of physical activity behaviour by providers of physical activity programmes and by those living with chronic respiratory disease. CONTRIBUTION OF THE PAPER.

PMID:41308270 | DOI:10.1016/j.physio.2025.101841

Patient Educ Couns. 2025 Nov 23;143:109431. doi: 10.1016/j.pec.2025.109431. Online ahead of print.

ABSTRACT

PURPOSE: The growing prevalence of cancer and of the responsibilities of primary informal caregivers calls for exploring the burden of caregivers. Communication with providers has become a major responsibility of caregivers increasing their burden. Despite the harmful consequences of caregiver burden (CB), little is known regarding mitigators of CB. The perceived high quality of communication with providers may be a mitigator of CB which is yet to be tested. Therefore, this study tests the association of episodic listening behaviors of providers and CB among caregivers of cancer patients. We hypothesize that constructive listening behaviors of nurses will shape the extent of CB.

METHODS: In this cross-sectional study, hospitalized oncology patients gave their consent to approach their informal primary caregivers and requested their consent to participate by completing anonymous questionnaires. Study variables included the Zarit Burden Interview and the abbreviated Constructive and Destructive Listening questionnaires. Statistical analyses used Pearson correlations and multivariable linear regression.

RESULTS: The sample comprised 80 primary caregivers of cancer patients. 65 % were women, 65 % were religious, and the average age was 51 years. Mean CB was 27.21 (SD-16.39). CB was positively associated with destructive listening (r = 0.400, p = 0.000) and negatively associated with constructive listening (r = -0.223, p = 0.000). Multivariable linear regression identified destructive listening as a significant antecedent (β = 0.265; t = 2.007; p = 0.049), explaining 14.7 % of the variance in CB (R² = 0.0192; MS = 568.147; df = 6; F = 2.7; p = < 0.002).

CONCLUSIONS: Although episodic listening is a key component of nursing ethics and fundamental to relationships with patients, caregivers of cancer patients may be ignored. To reduce CB, nurses should eradicate destructive listening and promote constructive listening forging higher quality communication with patients. Insights may guide future research and paths to reduce CB.

PMID:41308256 | DOI:10.1016/j.pec.2025.109431

Biomed Phys Eng Express. 2025 Nov 27. doi: 10.1088/2057-1976/ae250e. Online ahead of print.

ABSTRACT

The study of inter-beat intervals (IBI) and systolic blood pressure (SBP) fluctuations is of public health importance. Here we obtain insights about their underlying dynamics by means of an innovative study of the distribution of their rank-ordered registers, provided by fits to the Discrete Generalized Beta Distribution (DGBD), for healthy subjects and patients with end-stage renal disease (ESRD), under an active standing maneuver. SBP and IBI non-invasive time series were recorded during supine position followed by active standing for nine ESRD patients and eighteen age-matched healthy subjects. Once the data were rank ordered, the three parameter DGBD function was fitted through the Levenberg-Marquardt non-linear algorithm. Taking into consideration the statistical interpretations of the parameters, the quantitative exploration of their dependence with regard to the cases examined and changes in body position provided new insights: i) Evidence for the presence of regulatory mechanisms that preserve the tail symmetry of the IBI distributions in healthy subjects, which are not evident in ESRD patients; ii) The identification of a more pronounced weight of low-magnitude fluctuations at active standing in the SBP time series, manifested as a broader statistical dispersion of blood pressure values; iii) A quantitative determination of a more undermined SBP regulation in ESRD. Overall, a better understanding of the statistical behavior of IBI and SBP time series is achieved by means of the DGBD function. Through the variation of its parameters, the DGBD approach has the potential to become a marker for assessing or even predicting the impairment of cardiovascular control mechanisms.&#xD.

PMID:41308208 | DOI:10.1088/2057-1976/ae250e

Biomed Phys Eng Express. 2025 Nov 27. doi: 10.1088/2057-1976/ae250f. Online ahead of print.

ABSTRACT

Photoplethysmography (PPG) is widely used in wearable health monitors for tracking fundamental physiological parameters (e.g., heart rate and blood oxygen saturation) and advancing applications requiring high-quality signals-such as blood pressure assessment and cardiac arrhythmia detection. However, motion artifacts and environmental noise significantly degrade the accuracy of PPG-derived physiological measurements, potentially causing false alarms or delayed diagnoses in longitudinal monitoring cohorts. While signal quality assessment (SQA) provides an effective solution, existing methods show insufficient robustness in ambulatory scenarios. This study concentrates on PPG signal quality detection and proposes a robust SQA algorithm for wearable devices under unrestricted daily activities. PPG and acceleration signals were acquired from 54 participants using a self-made physiological monitoring headband during daily activities, segmented into 35712 non-overlapping 5-second epochs. Each epoch was annotated with: (1) PPG signal quality levels (good: 10817; moderate: 14788; poor: 10107), and (2) activity states classified as stationary, light, moderate, or vigorous-intensity. The dataset was stratified into training (80%) and testing (20%) subsets to maintain proportional representation. Fourteen discriminative features were extracted from four domains: morphological characteristics, time-frequency distributions, physiological parameter estimation accuracy, and statistical properties of signal dynamics. Four machine learning algorithms were employed to train models for SQA. The random forest (95.6%) achieved the highest accuracy on the test set, but no significant differences (p=0.471) compared to support vector machine (95.4%), naive Bayes (94.1%), and BP neural network (95.1%). Additionally, the classification accuracy showed no statistically significant variations (p=0.648) across light (95.3%), moderate (97.6%), and vigorous activity (100%) when compared to sedentary (95.8%). All features exhibited significant differences (p<0.05) across high/moderate/poor quality segments in all pairwise comparisons.The results indicate that the proposed feature set achieves robust SQA, maintaining consistently high classification accuracy across all activity intensities. This performance stability enables real-time implementation in wearable devices.

PMID:41308204 | DOI:10.1088/2057-1976/ae250f