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Predicting ankylosing spondylitis disease activity via patient-reported outcome measures: Building prediction models based on machine learning
Objective Disease activity is a critical indicator for monitoring the progression of ankylosing spondylitis (AS), guiding clinical decision-making, and informing treatment plans. Patient-reported outcome measures (PROMs) have gained prominence in AS clinical management. However, their potential to predict Ankylosing Spondylitis Disease Activity Score-C-reactive protein (ASDAS-CRP) remains unexplored. This study employs machine learning (ML) techniques to develop prediction models utilizing PROMs data to estimate disease activity in patients with AS. Methods We utilized data from 389 patients with AS were included sourced from the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from March 2022 to March 2024. This dataset was divided into a training set (80%) and a testing set (20%). A total of 34 variables, including clinician-recorded features and PROMs (e.g., BASDAI, BASFI, BASMI, PGA, VAS, ASAS-HI, FACIT-F, DASS-21), were employed for feature selection and assessment of feature significance using a variety of machine learning methods. Ten models were constructed using Support Vector Machine (SVM) and K-Nearest Neighbour (KNN) classifiers in conjunction with five feature selection methods: Feature Selection with Orthogonal Regression (FSOR), Trace Ratio Criterion (TRC), Robust Feature Selection (RFS), Pearson Correlation Coefficient (PCC), and ReliefF. Model performance was evaluated based on accuracy, specificity, sensitivity, and area under the receiver operating characteristic curve (AUC-ROC). Results A total of 389 patients with AS were included in the analysis. Key characteristics assessed included Patient Global Assessment (PGA), age, and the impact of disease on daily activities. The results indicated that the FSOR+SVM model achieved the best overall performance, with an AUROC of 0.930 (95%CI: 0.87–0.99) in the validation set. Meanwhile, FSOR+SVM also exhibited the highest sensitivity (83.78%), accuracy (79.35%), and specificity (90.50%). Conclusion The machine learning model developed from PROMs data proved effective for predicting AS disease activity, showing strong agreement with clinical ASDAS-CRP measures.
Contribution of cytochrome P450-mediated metabolism to clavulanic acid-induced cytotoxicity in TK6-derived cytochrome P450-overexpressing cell lines
Abstract Clavulanic acid, a β-lactamase inhibitor, is widely co-administered with amoxicillin (as in Augmentin ) to treat a broad range of mild-to-moderate bacterial infections by inhibiting β-lactamase enzymes produced by resistant bacterial strains. Despite its therapeutic efficacy, clavulanic acid has been associated with drug-induced liver injury, but the underlying mechanisms for this toxicity remain poorly understood. We investigated the contribution of cytochrome P450 (CYP)-mediated metabolism in relation to clavulanic acid-induced cytotoxicity. A panel of TK6-derived cell lines overexpressing 18 individual CYP isoforms (CYP1A1, CYP1A2, CYP1B1, CYP2A6, CYP2A7, CYP2A13, CYP2B6, CYP2C8, CYP2C9, CYP2C18, CYP2C19, CYP2D6, CYP2E1, CYP3A4, CYP3A5, CYP3A7, CYP4A11, and CYP4B1) was employed. Cells were incubated for 24 and 48 h with freshly prepared clavulanic acid (20-1000 µM) in RPMI-1640 medium, and the half-maximal inhibitory concentration (IC₅₀) was determined. Cell growth was more markedly delayed after 48 h of treatment than after 24 h of exposure. Following 48 h of treatment, 13 CYP-overexpressing cell lines showed reduced IC₅₀ values compared with parental TK6 and TK6/vector control cells. The rank order was CYP3A4 ≈ CYP3A7 ≈ CYP1A1 < CYP4A11 ≈ CYP2A13 ≈ CYP2C19 < CYP2B6 ≈ CYP1A2 ≈ CYP2C9 < CYP1B1 ≈ CYP2D6 < CYP2E1 ≈ CYP2C18, with the greatest decrease (~2-fold) observed in TK6/CYP3A4 cells. In contrast, five isoforms (CYP2A6, CYP2A7, CYP2C8, CYP3A5, and CYP4B1) showed IC₅₀ values comparable to controls. To examine further the cytotoxic response, TK6/CYP vector and TK6/CYP3A4 cells were treated for 48 h with equitoxic concentrations of clavulanic acid (0.1×, 0.5×, and 1.0× IC₅₀). The exposures resulted in a significant concentration-dependent reduction in cell viability, accompanied by increased lactate dehydrogenase release, the induction of apoptosis, G₀/G₁ phase arrest, and a concentration-dependent elevation in γH2AX phosphorylation, indicative of DNA damage. In conclusion, CYP enzymes, especially CYP3A4, likely contribute to clavulanate-induced cytotoxicity, with necrosis, cell cycle disruption, and γH2AX-associated apoptosis as key cellular responses.
Acute Cordyceps militaris supplementation and elevated resting oxygen uptake with faster reaction times: A randomized crossover trial
Background Cordyceps militaris (CM) demonstrates neuroprotective properties in chronic preclinical models, but its acute effects on cognitive and physiological parameters during exhaustive exercise remain uncharacterized in humans. Study design In a randomized, double-blind, placebo-controlled crossover trial with a 7-day washout, 12 recreationally active young men (mean age 21.6 ± 2.9 years, VO₂max: 38.6 ± 5.5 mL·kg ⁻ ¹·min ⁻ ¹) ingested 1 g of standardized CM extract or a cornstarch placebo 30 minutes before a maximal cycling test to exhaustion. Cognitive performance (Stroop reaction time and accuracy) and physiological measures (oxygen uptake, blood glucose, blood pressure, and heart rate) were assessed pre-exercise and 3 minutes’ post-exercise. Results Stroop reaction time exhibited a significant main effect of Condition (F(1,11) = 5.45, p = 0.040) and Time (F(1,11) = 16.37, p = 0.002), with faster responses overall in the CM condition. Both conditions improved from pre- to post-exercise (placebo: −148.92 ms; CM: −104.67 ms). The Condition × Time interaction was non-significant (F(1,11) = 1.01, p = 0.337). No between-group difference was observed at pre-exercise (p = 0.167), but CM produced faster reaction times at post-exercise (963.92 ± 84.99 ms vs. 1034.33 ± 84.16 ms; p = 0.042, d = 0.88). Accuracy remained near-ceiling (>99%) with no condition differences. CM elevated resting VO₂ (0.37 vs. 0.24 L/min; p = 0.022) without altering peak exercise VO₂ (p = 0.490). No significant Condition effects or interactions were observed for blood glucose, blood pressure, or heart rate (all p > 0.05). Conclusion Acute CM supplementation improved post-exercise reaction time and elevated resting oxygen uptake, but did not alter the magnitude of exercise-induced changes in cognitive or physiological parameters. This suggests CM exerts an acute cognitive benefit independent of exercise modulation.
A green electrochemical sensor based on Fe/N-graphene hybrid nanostructure for trace-level determination of apremilast in biological and pharmaceutical samples
A study on the car-following model for mountainous curves incorporating driving behavior characteristics
This study addresses the high accident rate on mountainous highways, driven by complex road alignments, harsh climatic conditions, and heterogeneous driving behaviors, aiming to enhance the accuracy of car-following behavior modelling. Using a typical mountainous curved section in Yunnan Province as the test case, drone-collected vehicle trajectory data were filtered using Kalman filtering to reduce noise. Subsequently, a K-Means algorithm optimized by differential evolution classified driving behaviors into three categories: aggressive, conservative, and standard. This revealed significant differences in speed, acceleration, and headway between distinct driving styles. To characterize curve dynamics, this study introduced a curve-radius parameter to enhance the Intelligent Driving Model (IDM). It calibrated it according to the rules for the three driving styles using genetic algorithms. Validation through macro-level error analysis and micro-level trajectory comparisons demonstrated that the improved model significantly enhances prediction accuracy for curve-following behavior while effectively adapting to diverse driving characteristics. This study pioneers the integration of driving behavior heterogeneity with curve geometry characteristics, providing a theoretical foundation for traffic flow simulation, safety assessment, and intelligent driving system design on mountain roads. It holds significant engineering value for reducing the risk of following-distance accidents and optimizing traffic management in mountainous regions.
Explainable deep learning for multi-country energy forecasting and sustainability analysis using climate and socio-economic indicators
Vicia faba-PGPB association improves soil health as a sustainable strategy to remediate moderately Pb and Cd contaminated soils
Phytoremediation is an eco-friendly strategy for heavy metal bioremediation. This study focuses on assessing the potential of faba bean- plant growth promoting bacteria symbiosis in phytoremediation and soil fertility improvement of HMs contaminated soils. Vicia faba L. var. minor Saber 02 was inoculated with a consortium of three efficient and HMs resistant PGPB ( Rhizobium sp. CCNWSX0481, R. leguminosarum bv. viciae and Pseudomonas sp.) and cultivated in soil treated with Cd and Pb to establish three contamination levels: uncontaminated (S1), moderately contaminated (S2; 2 mg kg -1 Cd and 100 mg kg -1 Pb), and highly contaminated (S3; 4 mg kg -1 Cd and 200 mg kg -1 Pb). Bacterial inoculation enhanced plant growth and metal uptake, most significantly in the moderately contaminated soil (S2). An increase in shoot dry weight and nodule dry weight was observed after bacterial inoculation mostly in the moderately contaminated soil S2. Furthermore, the effect of bacterial inoculation was particularly pronounced in S2 soil, resulting in significant increases in Pb and Cd accumulation in the shoots by 66% and 441%, respectively, compared to the uninoculated plants. Similarly, inoculated plants grown in S2 soil exhibited substantially higher total heavy metal contents than the uninoculated plants, reaching 179% for Pb and 319% for Cd, respectively. This increase was associated with an enhancement in the concentration of non-protein thiols, particularly in S2 soil, where inoculation increased root NPT levels by 49% compared to the uninoculated plants. Nevertheless, HMs induced a significant increase in roots enzyme such as superoxide dismutase, catalase and glutathione reductase. The inoculation further enhancing their activities essentially in S2. Moreover, PGPB considerably reduced total Pb as well as both the total and available fractions of Cd, mainly in S2 soil and increased total nitrogen and available phosphorus content, urease and β-glucosidase activities. The obtained results highlight the effectiveness of V. faba L var. minor Saber 02- PGPB symbiosis in the reclamation of moderately Pb and Cd contaminated soils. The bacterial consortium could be used as biofertilizer to improve soil quality of Cd/Pb contaminated sites.
Differential effects of ischemic preconditioning and cold compression on recovery in recreational crossfit athletes aged ≥ 40 years: a 2-week randomized controlled trial
Identification of tooth traces from a Cretaceous (Maastrichtian) Edmontosaurus annectens bonebed in the Lance Formation, Wyoming, U.S.A.
Identifying the origin of perforating lesions on fossil bone is often difficult, and many are considered tooth traces, in spite of more likely and more parsimonious etiologies. Much of this confusion stems from tooth trace criteria that are ambiguous when the context for the lesions is not considered. Mistaken identification of tooth traces has led to misleading interpretations of animal behavior. This study of tooth traces on fossil bones critically reviews previous criteria and applies them to assessing bones from an Edmontosaurus annectens bonebed within the Lance Formation, Wyoming, USA. Of the 3013 bones examined, thirteen bones had features indicative of tooth traces based on gross appearance. Of these, one bone had perforations determined to have a different etiology. Twelve bones had traces attributed to tooth marks, including four bones with Knethichnus parallelum and Linichnus serratus ichnotaxa. Tyrannosaurus rex was identified as the likely inflictor of traces attributable to both ichnotaxa, by comparison of denticle density of carnivore teeth within the bonebed with striation/serration density of the traces. The importance of context in the analysis of perforating lesions on fossil bones is shown through the mistaken identification of features such as neurovasculature foramina and lesions associated with pathology as tooth traces. This study contributes to the literature on biting behavior and refines the criteria used to identify perforations caused by bite marks. The application of these refined criteria also proved useful in accurately identifying tooth traces on bone. This, in turn, enhances the guidelines for recognizing perforations as tooth traces and encourages further research on this topic.
Study on three-dimensional stress characteristics and torsional performance of titanium-steel tool joints
Abstract Titanium alloy has promising applications in the ultra-deep well drilling field. When using titanium alloy drill pipes in composite drill strings, using titanium-steel tool joints becomes inevitable. However, the mechanical properties of such titanium-steel tool joints are not fully understood. This paper develops a three-dimensional elastic-plastic finite element model to analyze the loading characteristics of API standard tool joints with different material combinations. The analysis shows that the torsional performance of titanium-steel tool joints is significantly reduced compared to traditional steel tool joints. Based on these findings, a titanium-steel double-shoulder tool joint was designed. Its model accuracy was verified through experimental testing, and its mechanical behavior was analyzed. Results indicate that incorporating a secondary shoulder structure and adjusting the clearance of the secondary shoulder can effectively enhance the torsional performance of the tool joint. Specifically, the ultimate working torque of the titanium-steel double-shoulder tool joint (DS50-H) is 84.6 kN·m, 39.15% higher than the 60.8 kN·m torque of the titanium-steel single-shoulder tool joint (NC50). This improvement significantly enhances the tool joint’s stability under complex geological conditions.
Binding Affinity Ranking at the Molecular Initiating Event (BARMIE): An open-source computational pipeline for the rapid screening of chemical interactions with steroid receptors from many species
A challenge in ecological risk assessment is identifying the chemicals that pose the greatest threat and determining which species are most vulnerable to them. To help address this, this study has developed an in-silico open-source tool called BARMIE (Binding Affinity Ranking at the Molecular Initiating Event) to rapidly predict the chemical binding affinity of steroid receptor proteins to synthetic steroids to identify potentially vulnerable species and chemicals of concern. BARMIE was used to screen 163 teleost fish glucocorticoid receptors (GRs) for binding to the natural ligand cortisol and to 10 synthetic glucocorticoid drugs (GCs) designed to interact within the ligand-binding pocket (LBP) of GRs. BARMIE identified species from the superorder Protacanthopterygii with high-affinity GRs to synthetic GCs (e.g., vulnerable species).. BARMIE was also used to screen binding profiles of compounds in the Medicine for Malaria Venture Global Health Priority Box to rainbow trout GRs (rtGR1 and rtGR2). Of the 178 compounds, 24 and 36 bind within the LBP of rtGR1 and rtGR2, respectively. For 30 of these compounds, transactivation activity was assessed at 1µM in the presence or absence of 1µM cortisol and confirmed 2 compounds with agonistic properties (e.g., chemicals of concern) that would require further in vitro and/or in vivo studies to assess the environmental risk. BARMIE can rapidly generate predicted binding affinities for 100’s of species and chemicals as a first screen in environmental risk assessment to provide information on which substances to prioritise in downstream tests.
Explainable machine learning for flood susceptibility mapping in Kyrgyzstan’s major urban areas
Concentrations of essential and non-essential elements in eastern North Pacific killer whales (Orcinus orca)
Essential and non-essential elements can harm marine wildlife and impact ecosystems. Using liver (n = 35) and kidney (n = 17) samples from 35 animals from three distinct killer whale ( Orcinus orca ) ecotypes (fish-eating residents, mammal-eating transients, and offshore shark-eating specialists) stranded from California to Alaska and Hawaii, we determined elemental concentrations (arsenic (As), barium (Ba), beryllium (Be), calcium (Ca), cadmium (Cd), cobalt (Co), copper (Cu), chromium (Cr), iron (Fe), mercury (Hg), methylmercury (MeHg), manganese (Mn), molybdenum (Mo), magnesium (Mg), nickel (Ni), lead (Pb), selenium (Se), thallium (Tl), vanadium (V), and zinc (Zn)). Also, we evaluated associations with demographic and genetic factors. Calves had lower Cd than other life stages in kidney and liver tissue. Adult females had higher liver Se than calves and higher total mercury (tHg) in kidney and liver than calves. Adult males had higher liver Cd, tHg, and Se than calves. Residents had higher liver Mg, Mn, and Mo than transients. Linear regression showed life stage had some effect on the concentration of kidney Hg, and on the concentration of liver Mg, Mn, Mo, Cd, Hg, and Se. A prior study found no microscopic evidence of toxicosis in the tissues of examined animals. Population had some effect on liver Cd and Mg. Mean ± SD Se:Hg molar ratios in kidney (0.871 ± 0.645) and liver (0.932 ± 0.940) were consistent with prior research (at or nearly 1:1), but ratios based on factors varied in kidney. These results expand knowledge of elements in northeastern Pacific killer whales.
Correction: 6-Gingerol attenuates hepatic ischemia/reperfusion injury through regulating MKP5-mediated P38/JNK pathway
MamNet-PT: A Mamba-enhanced hybrid architecture with selective state-space modeling for uncertainty-aware brain tumor segmentation
Precise segmentation of brain tumors from MRI remains a challenging problem in medical image analysis because tumor regions exhibit substantial size variability, diffuse and infiltrative boundaries, and severe foreground-background imbalance. To address these challenges, we propose MamNet-PT, a hybrid segmentation architecture that integrates efficient long-range dependency modeling, multi-resolution feature aggregation, and uncertainty-aware prediction within a unified framework. First, a selective state-space model is embedded into the U-Net-based feature pathway to capture long-range spatial dependencies with linear computational complexity, which is particularly important for irregular and spatially extended tumor regions. Second, a pre-trained ResNet-50 encoder is used to improve feature robustness under limited annotated medical data. Third, a gated feature interaction mechanism adaptively balances Mamba-derived global contextual features and CNN-derived local boundary features, avoiding simple feature concatenation or uncontrolled module stacking. In addition, a multi-resolution pyramid fusion module strengthens scale-aware representation of small enhancing foci and extensive edema, while Monte Carlo Dropout-based uncertainty estimation provides spatial confidence maps for retrospective confidence characterization and failure-mode analysis. On the BraTS2020 benchmark, MamNet-PT achieves a Dice score of 96.7% and an Intersection over Union of 95.4%, outperforming representative CNN-Transformer and Mamba-based segmentation baselines. Ablation experiments further confirm that the performance gain is attributable to the complementary effects of selective state-space modeling, gated global-local fusion, multi-resolution aggregation, and uncertainty-aware inference. These results suggest that MamNet-PT is a promising research framework for accurate and efficient brain tumor segmentation under retrospective benchmark evaluation.
Cloud-native encryption as a service for IoT
Abstract Encryption as a Service (EaaS) is a practical solution for resource-constrained Internet of Things (IoT) devices that cannot efficiently execute costly cryptographic tasks locally. This paper presents a cloud-native EaaS platform implemented on Kubernetes and designed to support scalable encryption, decryption, and key-management services for IoT environments. The paper describes the functional architecture of the platform, defines its main service workflow, and introduces two deployment modes, namely cloud-based and fog-based deployment. The proposed platform is evaluated in terms of processing time, deployment time, and end-to-end response time. The results show that the fog-based deployment reduces the response time by at least $$16\%$$ for small payloads and by up to $$6.8\times$$ for larger payloads compared with the cloud-based mode. The deployment analysis also shows that increasing the number of replicas from 1 to 5 leads to a deployment-time increase of more than $$30\%$$ , while increasing the workload to 11 replicas results in an increase of about $$47\%$$ . In addition, the results indicate that the Key Manager is the most resource-intensive component and has the highest impact on pod readiness time. Overall, the findings show that the proposed Kubernetes-based EaaS platform can provide flexible and scalable cryptographic support for IoT systems, while fog-based placement offers clear latency advantages in the evaluated prototype setting.
The AHS-R: A holistic thinking measure with expanded theoretical domains and improved score reliability
Analytic and holistic thinking represent distinct cognitive styles. The existing Analysis-Holism Scale (AHS) is the most widely used measure of holistic thinking but has faced psychometric challenges and its validation has been largely restricted to a limited cultural context. The purpose of this study was to develop a refined measurement instrument, the AHS-R (Analysis-Holism Revised Scale), that expands the theoretical representation of the holistic cognition domains by differentiating between the Midway (preference for compromise) and Contradiction (tolerance for contradiction) dimensions and offers improved psychometric properties for use in broader populations. Using Turkish samples, Study 1 ( N = 346) confirmed the feasibility of new items developed to more precisely and reliably represent Midway and Contradiction. Study 2 ( N = 631) applied item response theory (IRT) and hierarchical factor analytic models on the finalized scale with four dimensions (Causality, Midway, Contradiction, and Attention). The original Perception of Change subscale was removed due to its negative factor loading on the higher-order holistic thinking factor. IRT analysis showed that measurement properties were optimized by collapsing the original 7-point rating scale to a 4-point scale. A structural equation model confirmed the presence of a dominant general holistic thinking factor and provided preliminary evidence of construct validity, showing that the unique variance of all four dimensions was significantly and positively related to increased adherence to preventive health behaviors during COVID-19. The newly developed AHS-R is a robust instrument for measuring holistic thinking that addresses key limitations of the original AHS by expanding its theoretical domains, notably through the clear distinction between the Midway and Contradiction subscales, and enhancing reliability. These improvements allow for more precise measurement, facilitating interpretation of scores across different levels of analysis. Ultimately, AHS-R supports further cross-cultural research into the relationship between cognitive style and behavior, such as health engagement.
Surface and elemental analysis of stainless-steel needles after invasive physiotherapy: an exploratory scanning electron microscopy (SEM) study
Comparative clinical outcomes of polymyxin-based versus non-polymyxin regimens as definitive therapy in Carbapenem-resistant Klebsiella pneumoniae bacteraemia
Background Carbapenem-resistant Klebsiella pneumoniae (CRKP) bacteraemia poses a major therapeutic challenge due to limited effective therapeutic options and high mortality. Although polymyxins remain widely used, emerging evidence suggests that non-polymyxin regimens may offer improved efficacy and safety. This study compared clinical and microbiological outcomes between polymyxin-based therapy (PBT) and non-polymyxin regimens (NPR) in patients with CRKP bloodstream infections (BSI). Methods In this multicentric, retrospective observational study, adult patients (≥18 years) with confirmed CRKP bacteraemia admitted between January 2019 and December 2023 were included. Patients were categorised based on definitive therapy as PBT or NPR. Baseline characteristics, disease severity, and outcomes were compared using appropriate statistical tests. Predictors of in-hospital mortality were identified by multivariable Cox regression, validated by bootstrap resampling, and assessed through landmark sensitivity analysis excluding early deaths (<48 hours). Kaplan-Meier survival analyses were performed for mortality and microbiological clearance. Results Of 1,009 patients with K. pneumoniae bacteraemia, 244 patients with CRKP met inclusion criteria (PBT, n = 143; NPR, n = 101). Baseline demographics were similar, but PBT recipients had higher SOFA (4[0–12] vs.3[0–12]; p < 0.001) and CCI scores (4[0–8] vs.3[0–10]; p = 0.025). Clinical cure was achieved more often with NPR (58.4%vs.15.4%; p = 0.02), while in-hospital mortality (38.6%vs.68.5%; p < 0.001) and acute kidney injury (28.7%vs.55.9%; p = 0.008) were significantly higher in the PBT group. Microbiological clearance and time to clearance were comparable. Independent predictors of mortality included treatment with polymyxins (aHR:1.595;95%CI:1.392–1.903;p = 0.015), SOFA score>6 (aHR:1.514;95%CI:1.285–1.928;p = 0.027), history of chronic liver disease (aHR:2.31;95%CI:1.884–3.642;p = 0.02), post-therapy dialysis (aHR:3.11;95%CI:1.008–4.59;p = 0.048), and requirement of ICU admission after definitive therapy (aHR:1.474;95%CI:1.252–1.891;p = 0.02). Survival analysis confirmed superior outcomes for NPR (log-rank p < 0.001). Conclusion NPR was associated with significantly higher clinical cure, lower nephrotoxicity, and reduced mortality compared with PBT regimens. These findings suggest that non-polymyxin regimens may be associated with improved clinical outcomes and lower nephrotoxicity compared with polymyxin-based therapy in patients with CRKP bacteraemia. Prospective studies were warranted to confirm these observations.