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Rheumatoid Arthritis (RA) greatly affects patient's life. Systematic reviews of recent epidemic trend and the pathogenesis of RA are inadequate. Although multiple health benefits of lactic acid bacteria (LAB) were reported, comprehensive reviews addressing the mechanisms by which LAB alleviate RA remain limited. This review systematically examines the epidemiology and pathogenesis of RA, emphasizing the potential modulatory role of LAB in maintaining intestinal homeostasis. Drawing on both animal and clinical evidence, the review critically evaluates the molecular mechanisms by which LAB may alleviate RA, thereby offering a theoretical foundation for microbiota-based therapeutic interventions. Meanwhile, it highlighted the challenges and opportunities of LAB for RA. Genetic predisposition, environmental factors, and immune system dysfunction play very important roles in causing RA. LAB provided numerous advantages and had great potential for improving RA as its ability to regulate intestinal barrier, modulate related enzyme activity, inhibit oxidative damage, restore unbalanced gut microbiota, produce bioactive metabolites, and regulate gut-joint immune axis. In addition, this review advice to screen effective LAB by cell models and metabolites, to determined the optimal intake dose of LAB through dose-effect relationship studies, to promote the understanding of LAB by investigating the mechanism, and to improve the design of the clinical study to improve the lives of RA patients. This will contribute to understanding the epidemiological characteristics, pathogenesis, and treatment of RA, and promote the development of targeted therapeutic RA products such as LAB.

Peripherally inserted central catheters (PICCs) are commonly used vascular access devices in clinical practice. Due to their numerous advantages, PICCs are widely used globally. However, after decades of iteration and clinical application, while benefiting patients, PICCs also face new opportunities and challenges. Therefore, this study systematically analyzes the current status of global PICCs research through bibliometric methods and predicts future research directions and hotspots, aiming to provide references for further development and innovation of PICCs. CiteSpace, VOSviewer, and the bibliometrix R-package were used to perform descriptive statistics and data visualization analyses on literature from the Web of Science Core Collection. A total of 2102 articles were selected, originating from 2722 institutions across 105 countries. The United States has the greatest influence in the field of PICC research, with the Michigan Health System being the most prolific institution, and Vineet Chopra being the most influential scholar. Keyword and co-citation analysis reveal hot topics: PICC catheterization techniques, complications, and clinical quality control of PICCs. Research on PICCs is showing trends of global collaboration and interdisciplinary approaches. Artificial intelligence and other medical auxiliary technologies demonstrate great potential in addressing PICC complications and insertion challenges. Establishing efficient vascular access teams and solving PICC care issues based on evidence-based practices are crucial for ensuring quality control during PICC usage.

Deep learning methods have made great progress in the automatic segmentation of nasopharyngeal carcinoma, but challenges remain. Computer-aided automatic segmentation of nasopharyngeal cancer primary area is of great significance for automatic outlining of nasopharyngeal cancer target areas and accurate prediction of responsiveness and prognosis of metastatic lymph nodes in the neck after radiotherapy. In this paper, we use deep learning methods to construct an automatic segmentation network for gross target volume of nasopharynx, combine clinical factors and radiomics features to establish a radiomics nomogram model, which will then predict the final outcome of metastatic lymph nodes that have not achieved complete remission after radical radiotherapy. Clinical and IMRT radiotherapy plan CT data were retrospectively collected from 69 patients who received intensity-modulated radiation therapy between July 2014 and December 2016. These patients exhibited residual metastatic lymph node lesions without residual primary lesions on the first follow-up MRI and had continuous follow-up records. The median follow-up was 53 months (IQR 39.75-62.37), with 30 patients eventually regressing and 39 patients persisting or progressing. The ct images of 69 radiotherapy plans were randomly divided into training and test sets according to 8:2, and a fusion attention-based model was trained for automatic nasopharyngeal carcinoma segmentation. Based on the unet framework, a fusion attention model was proposed, and a 2·5 d convolutional neural network was used to deal with the anisotropy. An improved channel and spatial attention module is fused in the codec 4 layer to enable the network to focus on small targets. 2d interlaced sparse self-attention module is extended to 3d to better extract the feature information of the tumor target area and solve the problem of low contrast between the target area and the surrounding soft tissues, thus optimizing the overall segmentation effect. The performance of the segmentation model was evaluated using the mean dice coefficient, relative volume error (RVE), average symmetric surface distance (ASSD) and hausdorff distance (HD), using the target area of the primary lesion of nasopharyngeal carcinoma manually outlined by a senior radiation therapy specialist as the gold standard. Radiomics features were extracted using the pyradiomics package, and the classification performance of the radiomics model was assessed by the area under the curve of the receiver operating curve (ROC). The average dice coefficient, RVE, ASSD and HD of our model for nasopharyngeal carcinoma were 75.05%, 14.63%, 2.224 mm, and 8.75 mm, respectively, which were 11.01%, 26.34%, 3.101 mm, and 52.58 mm better than the baseline 3dunet model. The radiomic features were an effective predictor of tumor outcome in nasopharyngeal carcinoma, with the highest area under the receiver operating characteristic curve (AUC) of 0.892 for the radiomic nomogram in the training set and 0.825 for the radiomic model in the test set. The fused attention-based segmentation network for nasopharyngeal carcinoma can effectively and reliably segment the region of the primary nasopharyngeal carcinoma, and the radiomic nomogram can effectively predict the response after treatment.

To characterize methodological aspects and the quality reporting of economic evaluation in HTA reports of drugs submitted to the Brazilian public health system. An electronic search for HTA reports focusing on drug incorporation into the public health system published between 2020 and June 2024 was conducted in the Conitec database. The study selection and data extraction were performed to obtain bibliographic data, base case characteristics, and methodological features. Furthermore, the quality reporting of economic evaluation was verified by the Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022). Descriptive statistics summarize the data extracted from the documents. We included 188 economic evaluations of HTA reports about drug reimbursement; the great majority submitted to private companies or public institutions. Most economic evaluations adopted cost-utility or cost-effectiveness analysis using a comparator in the public system. Economic evaluation studies presented frequent inconsistent reports of cost and health outcomes and in the deterministic and probabilistic sensitivity analyses. Markov, decision tree, and partitioned survival model were the main mathematical models applied. Cost-effectiveness analysis mainly adopted QALY or QALY plus life-years gained as health outcomes, but there was a lack of clarity in the methods to incorporate health utilities in the cost-utility analysis. Finally, we identified that the quality reporting of economic evaluation needs to be improved. The methods and reporting quality of economic evaluations submitted to Conitec exhibit heterogeneity characteristics. Strengthening and standardizing guidance for preparing health economic evaluations is needed to ensure greater consistency, transparency, and decision-making reliability.

Traditional aqueous electrowetting systems face challenges including insufficient thermal stability, electrode corrosion, and particularly low near-infrared transmittance. To overcome these constraints, ionic liquids are a revolutionary alternative with advantages, especially including high transmittance over a wide spectrum. In this study, a new filling liquid formulation named EFN series is proposed and tested in a 10-mm caliber liquid lens. The transmittance of the developed liquid formulation is greater than 92% in a wide spectrum. The manufactured wide-band zoom electrowetting liquid lens achieves a maximum zoom range of 13.93 m-1 and a fast response of about 100 milliseconds in the range of applied voltage 0-70 V, and has clear imaging results and great zoom performance, satisfying the needs of real-time adaptive regulation.

Dystrophinopathies are caused by pathogenic variants in the DMD gene, resulting in partial (Becker) or complete loss (Duchenne) of dystrophin. Becker (BMD) and Duchenne muscular dystrophy (DMD) are characterized by progressive muscle wasting, fatty replacement, fibrosis, and loss of function. To study histopathological changes, we used Visium spatial transcriptomics to profile skeletal muscle biopsies of patients affected by dystrophinopathy (n = 8) and healthy controls (n = 4). We estimated the proportion of cell types and their spatial localization across samples applying a deconvolution strategy using previously published single-nucleus RNA-sequencing data. We identified genes enriched in fat patches and cell types such as fibroadipogenic progenitors (FAPs) in areas of active pathology. Using expression data of ligand-receptor pairs, we highlight cell-cell communications leading to fibrotic and adipogenic lesions. Finally, analysis of gene expression gradients in areas of adjacent muscle and fat, allowed the identification of genes associated with muscle areas committed to becoming fat. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Severe traumatic brain injury (sTBI), is a leading cause of death and disability among young and middle-aged populations worldwide. sTBI is associated with high mortality and disability rates, and reliable risk estimation with quantified uncertainty is crucial for optimizing intensive care unit (ICU) bed allocation and nursing resource deployment. This study aimed to establish a prognostic model for sTBI patients using multicenter clinical, imaging, and nursing data, and to explore its value in guiding clinical resource allocation. A total of 1000 sTBI patients from multiple medical centers were enrolled in this retrospective cohort study. Clinical data including vital signs, CT/MRI imaging features, and detailed neurosurgical nursing records were collected. Multivariate Cox regression analysis identified age, GCS score on admission, pupillary light reflex, CT findings such as midline shift, and hematoma volume, mean arterial pressure, and nursing-related indicators such as incidence of pulmonary infection, and pressure ulcer grade as independent prognostic factors for sTBI patients. The resource allocation strategy guided by risk stratification significantly reduced ICU bed occupancy rate from 89.2% to 75.6% and improved the utilization efficiency of specialized nursing resources, while the overall prognosis of patients was not negatively affected. The ML ensemble model constructed based on multicenter clinical, imaging, and nursing data has high accuracy in predicting short-term and long-term outcomes of sTBI patients. Risk stratification using this model can provide a scientific basis for rational allocation of ICU beds and resources, which is of great significance for improving the overall treatment level of sTBI patients.

Herein, a novel dinitrophenyl-appended phthalonitrile chemodosimeter DNPPn, readily synthesized in a single step, was introduced as a colorimetric and fluorescent probe for the selective and sensitive detection of hydrogen sulfide (H2S), and validated in real sample matrices. The molecular structure of the DNPPn was comprehensively elucidated using single-crystal X - ray diffraction analysis (XRD), and well-established spectroscopic techniques (1H NMR, 13C NMR, ESI-MS, and FT-IR). DNPPn exhibited a broad concentration range, and dual-mode (colorimetric and turn-on fluorometric) sensing capabilities for the on-site detection of H2S via a dinitrophenyl ester thiolysis mechanism, definitively verified through HR-MS Density Functional Theory (DFT) analysis. DNPPn demonstrated remarkably low limits of detection (LOD) values (88.5 ppb for UV-Vis and 65.9 ppb for fluorescence) with ultra-fast response time (30 s), well below than the permissible exposure limits defined by Occupational Safety and Health Administration (OSHA) and National Institute for Occupational Safety and Health (NIOSH) (20.0 ppm and 10.0 ppm, respectively). The thiolysis reaction triggers a pronounced color shift from pale-yellow to orange by regulating the intramolecular charge transfer (ICT) mechanism. This allows on-site monitoring through a smartphone-assisted platform. Furthermore, the practical feasibility of DNPPn was proven via its evaluation in real water and food samples. Overall, these findings demonstrate that DNPPn is a highly selective, sensitive and versatile tool for the instantaneous and on-site H2S detection, with promising applications in environmental monitoring and the public health protection. ENVIRONMENTAL IMPLICATION: Although H2S attends to critical physiological operations, its widespread presence in water resources poses a significant risk to ecosystems and human health. H2S concentration in biological tissues varies widely, the safety margin between physiological and toxic levels of H2S is quite narrow, and its rapid catabolism causes continuous fluctuations in concentration, complicating precise quantification. Therefore, there is a great need for multichannel chemosensors that can easily and continuously monitor H2S in real samples. This study presents a novel fluorescent/colorimetric probe (DNPPn) for the highly selective and sensitive quantification of H2S in real samples with outstanding sensing performance.

The chemical composition, antioxidant activity and authenticity of commercially available rosemary (REO) and laurel (LEO) essential oils from the Slovenian market were investigated. In both EOs, 1,8-cineole was identified as the most abundant compound. It was determined that VOCs in lower concentrations contribute more to antioxidant activity compared to more abundant compounds. Key isotopic markers for adulteration detection were determined using compound-specific isotope analysis (CSIA). The sensitivity of the developed method was evaluated, demonstrating the best sensitivity for linalool in REO and for α-pinene in LEO, which means if the sample contains more than 19% of linalool (47% for α-pinene) synthetic fraction, it is almost certain (95% probability) that falsification will be suspected. When analysing commercial EOs declared as natural, the δ13CVPDB values indicated possible falsification of several VOCs in EOs. The developed methodology has shown great promise in the quality control of EOs, verifying labelling claims and detecting adulteration.

Aberrant DNA methylation is a significant prognostic of tumorigenesis, making it a promising biomarker for early diagnosis of cancer. Although bisulfite conversion combined with nucleic acid amplification can provide high sensitivity to detect trace of tumorous DNA, carryover contamination is inevitable and conflicts with sensitivity. Besides, uracil-DNA glycosylase-based strategy is inapplicable to aerosol elimination with bisulfite-converted DNA as template. False positive result caused by carryover contamination still exists in bisulfite conversion-based method for DNA methylation analysis. Hence, the deficiencies highlight the need to adopt another strategy for sequence analysis in bisulfite conversion-based methods. In this study, a novel strategy for eliminating carryover contamination is developed based on the mechanism of DNA damage repair, applicable to bisulfite-converted DNA analysis. Loop-mediated isothermal amplification (LAMP) is employed for DNA methylation detection, ignoring the tendency of carryover contamination caused by the high sensitivity and numerous amplicons. By introducing deoxyinosine triphosphate during amplification, amplicon is labeled with hypoxanthine. The hypoxanthine-labeled amplicon as aerosol can be recognized and excised by endonuclease V subsequently, while bisulfite-converted DNA as template lacking hypoxanthine is insusceptible. Besides, a lateral flow device (LFD) is assembled as a fast and convenient strategy to interpret result visually, ignoring aerosol dispersion caused by the open vessel. The status of DNA methylation located on the promoter of miR-34a is identified using 10 real-world specimens and the result from this method is consistent with that from pyrosequencing. A novel strategy to eliminate carryover contamination is developed and integrated into a LAMP-based lateral flow biosensor for DNA methylation analysis. The conflict between carryover contamination and sensitivity is resolved, facilitating trace of DNA methylation detection. LFD can be employed for visual result interpretation, facilitating point-of-care test. As a universal strategy, this method can be easily expanded to other biomarkers, providing a great candidate for DNA methylation analysis to assist early diagnosis of cancer.

Boron-doped aggregation-induced emission (AIE) nanomaterials (B@AIE NPs) were successfully synthesized via a facile one-pot solvothermal method for dual-modality fluorescence (FL) and magnetic resonance (MR) imaging. The as-prepared B@AIE NPs exhibited a uniform core-shell structure, excellent dispersibility, and strong NIR-II fluorescence emission at 984 nm upon aggregation, attributed to restricted intramolecular motion. Moreover, the boron doping conferred remarkable T1-weighted MR contrast capability, with a high longitudinal relaxivity (r1) of 6.12 mm- 1s- 1. In vitro studies demonstrated excellent biocompatibility and efficient cellular uptake, with preferential localization in lysosomes. In vivo experiments in HeLa tumor-bearing mice revealed effective tumor accumulation via the enhanced permeability and retention (EPR) effect, enabling high-contrast NIR-II fluorescence and MR imaging. These results highlight the great potential of B@AIE NPs as a promising metal-free nanoprobe for precise tumor diagnosis through FL/MR dual-modal imaging.

We hypothesize that the large uncertainty of slip length in conventional approaches for Newtonian fluids under creeping flow and lubrication approximation conditions arises from the assumed ideal velocity distribution, and an alternative approach that does not require assuming an exact velocity distribution is of great value under the same conditions. In this study, we developed a new methodology to quantitatively and accurately determine slip length by converting the AFM-measured hydrodynamic forces and approach rates into mass flow and velocity-independent resistances and by using the Stribeck curve to identify the appropriate data interval. To prove the concept, we employed high-precision colloidal probe atomic force microscopy (CP-AFM) technology to study water on hydrophilic, less-wetting, and unmodified silicon surfaces across six driving velocities (6.0-36.6 μm/s), and their slip length values were then obtained, compared with conventional methods combined with further discussions. The resulting slip lengths show no dependence on the driving velocity. We further introduce an analysis of extended uncertainty, demonstrating that our method exhibits an extended uncertainty less than one-third of that from the conventional approaches. Subsequently, we quantitatively assessed the contribution of friction resistance (RFriction, directly linked to slip) in the total resistance (RTotal). The results show that, as the separation increases, the contribution of RFriction decreases significantly, which explains why the slip length is so difficult to measure precisely. This study reveals that the large uncertainty of slip length obtained with the conventional methods stems from underestimating the contribution of RFriction, and this work provides a novel and reliable methodology for achieving high-precision slip length by precisely decoupling the viscous and friction flow components.

Polar topologies hold great potential in information storage. So far, thin films with polar topological structure are predominantly constrained by the substrate on which they are grown. Such substrate-stabilized polar topologies limit their integration into memory devices, and consequently, their physical behaviors in data memory remain unclear. Here, we show a ferroelectric field-effect transistor (Fe-FET) memory device, which is based on large-scale freestanding pure polar vortex tube arrays. In situ heating demonstrates that vortex tube arrays in freestanding superlattices undergo a more directly reversible phase transition, evolving from vortex tubes to single domains and ultimately to the disappearance of ferroelectricity. The flexible vortex tubes, which are obtained by removing the sacrificial layers, could bend at a 90° without breaking, demonstrating the nature of robustness. The Fe-FET exhibits a wide and stable clockwise hysteresis loop, spanning a voltage range of -60 to 60 V and temperatures from room temperature to 450 K. Due to the stable and robust ferroelectric vortex dipole moment arrays, the Fe-FET achieves a memory retention time of 3600 s and an endurance of 104 cycles.

Diagnostic integration technology represents a significant advancement in cancer diagnosis and treatment. The combination of fluorescence probe-based imaging methods with photodynamic therapy (PDT) offers distinct advantages due to its high sensitivity and minimally invasive nature. However, the effective detection depth and spatial resolution of fluorescence imaging are limited by light scattering effects in biological tissues. Additionally, high concentrations of GSH in the tumor microenvironment (TME) neutralize reactive oxygen species (ROS) generated by PDT, directly inhibiting therapeutic efficacy. Therefore, developing a highly sensitive, high-resolution fluorescent probe to achieve integrated tumor diagnosis and treatment is of great significance. This study developed an activatable diagnostic-therapeutic probe, MB-2O-MB. In MB-2O-MB, methylene blue (MB) served as both the photosensitizer and signal reporting moiety, while a thiols-sensitive disulfide bond was introduced as the linker and response unit. When the probe reacted with GSH in tumor regions, the disulfide bond broke, causing structural dissociation and releasing free MB molecules. Experiments demonstrated that the probe exhibited strong interference resistance, and high sensitivity (LOD = 57.99 nM) for this reaction. Furthermore, the photoacoustic (PA) signal generated upon probe activation compensated for the limited tissue penetration depth of fluorescence imaging, enabling more precise spatial localization of tumor regions. Therapeutically, upon irradiation with 660 nm near-infrared (NIR) laser light, the released MB efficiently generated singlet oxygen, effectively inducing 4T1 tumor cell death. In vivo data further validated the significant tumor suppression effect of MB-2O-MB via PDT. In summary, MB-2O-MB achieves precise tumor localization and complete eradication through the synergistic combination of NIR fluorescence/PA dual-modality imaging and PDT. This strategy simultaneously overcomes the drug resistance bottleneck and imaging limitations of conventional photodynamic therapy, paving a new pathway for constructing highly selective and potent smart diagnostic and therapeutic systems, and significantly advancing precision medicine.

Carbon dots (CDs), zero-dimensional carbon-based nanomaterials, have significantly advanced laboratory medicine due to their high photoluminescence quantum yield, excellent biocompatibility, and versatile surface functionalization. This review systematically summarizes CDs' synthesis strategies (top-down and bottom-up approaches), structural/optical characteristics, and diverse applications in the field including the sensitive detection of biomolecules (proteins, nucleic acids, and small biomolecules), microbial identification, cell/tissue imaging, and diagnosis of cancer, infectious diseases, and other disorders. Despite challenges such as poor reproducibility, lack of standardized protocols, and hurdles in clinical translation, CDs hold great promise for enabling sensitive, rapid, and personalized diagnostic solutions. Future directions focus on developing multifunctional probes, advancing clinical translation, integrating with artificial intelligence and cutting-edge technologies (microfluidics), and enabling single-cell analysis, positioning CDs to revolutionize precision diagnostics and personalized medicine.

The development of Social and Emotional Learning (SEL) is of increasing interest in schools worldwide. Consequently, the evaluation of SEL programs such as emotional intelligence (EI) interventions, to ensure the establishment of evidence-based emotional education is relevant. The main purpose of this study was to evaluate the effects of an ultra-short (6&#xa0;h) EI intervention on child psychosocial adjustment. The sample consisted of 268 children (8-12&#xa0;years old). Results from ANCOVA analyses showed no statistically significant differences between the intervention and control groups at post-test across the main outcome variables (e.g., F values <2.00, p&#xa0;>&#xa0;.12), though within-group Student's t-tests revealed small but significant improvements in quality of life at post-test (d&#xa0;=&#xa0;0.18) and in quality of life, mental health (d&#xa0;=&#xa0;0.48), and anxiety/depression symptoms (d&#xa0;=&#xa0;0.11) at one-year follow-up in the intervention group. These findings revealed the absence of differences between experimental and control groups at post-test, although the intervention group significantly increased health-related quality of life at post-test and follow-up, as well as mental health at follow-up assessment. This paper highlights the great importance of the way elected to evaluate the overall effectiveness of an EI intervention based on using hard techniques (i.e., ANCOVA), showing actual effectiveness, versus soft contrast techniques (e.g., Student's t-test, Repeated-Measures ANOVA), which simply show gains (fake effects). The importance of ensuring hard evidence-based emotional education is highlighted. These findings underscore the relevance of using rigorous statistical techniques-so-called hard methods like ANCOVA-to avoid inflated or false-positive interpretations often derived from gain-score analyses (fake effects) in the evaluation of overall effectiveness of an EI intervention. Overall, the intervention showed limited but promising effects, particularly in long-term mental health, suggesting potential for brief SEL programs if implemented and assessed with methodological rigor.

Orangutans are the largest arboreal mammals and the only great apes that spend most of their lives in the treetops. To navigate this environment, they use a wide range of locomotion behaviours. In zoos, however, orangutans often show increased terrestriality and rely on locomotion behaviours that are rarely seen in the wild, such as quadrupedal locomotion. These differences raise welfare concerns, as they may impair the development of their musculoskeletal system and reduce energy expenditure, thereby increasing obesity risk. Enclosure design may mitigate these effects by encouraging more species-typical locomotion. Therefore, this study aimed to investigate differences in locomotion behaviour of orangutans across two enclosure types, one with more flexible structures and one with more rigid structures. We performed focal observations of seven Bornean orangutans (Pongo pygmaeus) in Apenheul Primate Park (Apeldoorn, The Netherlands), recording their time budgets, types of locomotion and the structures used for locomotion. While overall time budgets, including time spent moving, did not differ meaningfully between enclosures, orangutans showed increased rates of species-typical locomotion behaviours, such as suspensory locomotion, in the enclosures with more flexible structures. Moreover, orangutans specifically used the flexible structures in their enclosure to perform these behaviours. Our findings highlight the importance of enclosure design, with flexible structures stimulating more species-typical locomotion in orangutans. However, rates of species-typical locomotion remained below those observed in the wild, indicating that further efforts are needed to stimulate zoo-housed orangutans toward natural locomotion patterns. Future research should explore additional strategies to promote arboreal and species-typical movement patterns in zoo-housed apes.