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Aim: We aimed to create a nano drug delivery system with tetracycline (TC)-grafted methoxy poly-(ethylene-glycol)‒poly-(D, L-lactic-co-glycolic acid) (mPEG‒PLGA) micelles (TC‒mPEG‒PLGA) with TC and mPEG‒PLGA for potential bone targeting. Prospectively, TC‒mPEG‒PLGA aims to deliver bioactive compounds, such as astragaloside IV (AS), for osteoporotic therapy. Methods: Preparation and evaluation of TC‒mPEG‒PLGA were accomplished via nano-properties, cytotoxicity, uptake by MC3T3-E1 cells, ability of hydroxyapatite targeting and potential bone targeting in vivo, as well as pharmacodynamics in a rat model. Results: The measured particle size of AS-loaded TC‒mPEG‒PLGA micelles was an average of 52.16 ± 2.44 nm, which exhibited a sustained release effect compared to that by free AS. The TC‒mPEG‒PLGA demonstrated low cytotoxicity and was easily taken by MC3T3-E1 cells. Through assaying of bone targeting in vitro and in vivo , we observed that TC‒mPEG‒PLGA could effectively increase AS accumulation in bone. A pharmacodynamics study in mice suggested potentially increased bone mineral density by AS-loaded TC‒mPEG‒PLGA in ovariectomized rats compared to that by free AS. Conclusion: The nano drug delivery system (TC‒mPEG‒PLGA) could target bone in vitro and in vivo , wherein it may be used as a novel delivery method for the enhancement of therapeutic effects of drugs with osteoporotic activity.

In the research of green vegetation coverage in the field of remote sensing image segmentation, crop planting area is often obtained by semantic segmentation of images taken from high altitude. This method can be used to obtain the rate of cultivated land in a region (such as a country), but it does not reflect the real situation of a particular farmland. Therefore, this paper takes low-altitude images of farmland to build a dataset. After comparing several mainstream semantic segmentation algorithms, a new method that is more suitable for farmland vacancy segmentation is proposed. Additionally, the Strip Pooling module (SPM) and the Mixed Pooling module (MPM), with strip pooling as their core, are designed and fused into the semantic segmentation network structure to better extract the vacancy features. Considering the high cost of manual data annotation, this paper uses an improved ResNet network as the backbone of signal transmission, and meanwhile uses data augmentation to improve the performance and robustness of the model. As a result, the accuracy of the proposed method in the test set is 95.6%, mIoU is 77.6%, and the error rate is 7%. Compared to the existing model, the mIoU value is improved by nearly 4%, reaching the level of practical application.

It is of great significance to study the porosity and permeability properties of medium and low-rank coal. The porosity and permeability in confining stress experiments were used to simulate the porosity and permeability variations of coal samples under different depth conditions. The pore structure of Baoqing coal samples is greatly affected by the confining pressure, and the pores and micro cracks are more easily compressed. Based on the experimental data of mercury intrusion porosimetry (MIP) and nitrogen adsorption (NA), the pore size distributions (PSDs) of medium and low-rank coals were studied. High mercury intrusion pressure would lead to coal matrix compression. Therefore, the pore volume calculated by MIP data was corrected by NA data. The PSDs characteristics of Jixi (JX) coal and Baoqing (BQ) coal samples are obtained from the revised pore volume, and the dominant pores of medium and low-rank coals are obtained. The results show that JX coal has higher spatial heterogeneity, connectivity and pore autocorrelation. Micro fractures have an influence on the autocorrelation and heterogeneity of coal samples, especially for BQ coal samples.

Chimeric antigen receptor T (CAR-T) cell therapy has been a milestone breakthrough in the treatment of hematological malignancies, offering an effective therapeutic option for multi-line therapy-refractory patients. So far, abundant CAR-T products have been approved by the United States Food and Drug Administration or China National Medical Products Administration to treat relapsed or refractory hematological malignancies and exhibited unprecedented clinical efficiency. However, there were still several significant unmet needs to be progressed, such as the life-threatening toxicities, the high cost, the labor-intensive manufacturing process and the poor long-term therapeutic efficacy. According to the demands, many researches, relating to notable technical progress and the replenishment of alternative targets or cells, have been performed with promising results. In this review, we will summarize the current research progress in CAR-T eras from the “targets” to “alternative cells”, to “combinational drugs” in preclinical studies and clinical trials.

Epstein–Barr virus (EBV) exacerbates inflammatory bowel disease (IBD) and is challenging to monitor with invasive or costly tests. We investigated whether explainable machine learning can predict EBV infection from routine clinical data in ulcerative colitis (UC) and Crohn’s disease (CD). In this retrospective study (June 2018–December 2022), EBV status was defined by EBV-DNA > 400 copies/mL. After cleaning, the training cohort (2018–2019) included 174 patients (CD = 122, UC = 52) and the test cohort (2020–2022) included 100 patients. Twenty-one demographic, clinical, and laboratory variables were modeled with ten classifiers; the four best were stacked. Five-fold cross-validation and resampling addressed overfitting and class imbalance. Shapley Additive Explanations (SHAP) provided model interpretability. The ensemble model exhibited high predictive accuracy, achieving area under the ROC curve (AUC) values of 0.93 (overall), 0.97 (CD), and 0.88 (UC) in the training set. In the validation set, AUC values were 0.95 (overall), 0.89 (CD), and 0.97 (UC). SHAP analysis identified age, hemoglobin (HB), total bile acids (TBA), and platelet count (PLT) as significant predictors. Age increased predicted risk in the overall and CD cohorts but decreased risk in UC. TBA emerged as a critical predictor in UC, reflecting its role in bile acid metabolism, while PLT influenced risk across the total patient population, indicating its involvement in coagulation and immune responses. An explainable stacking model using routine biomarkers accurately predicts EBV infection in IBD and reveals subtype-specific determinants. Prospective, multi-center and time-aware validation, and integration into decision-support tools are warranted for clinical deployment.

Object detection algorithms require compact structures, reasonable probability interpretability, and strong detection ability for small targets. However, mainstream second-order object detectors lack reasonable probability interpretability, have structural redundancy, and cannot fully utilize information from each branch of the first stage. Non-local attention can improve sensitivity to small targets, but most of them are limited to a single scale. To address these issues, we propose PNANet, a two-stage object detector with a probability interpretable framework. We propose a robust proposal generator as the first stage of the network and use cascade RCNN as the second stage. We also propose a pyramid non-local attention module that breaks the scale constraint and improves overall performance, especially in small target detection. Our algorithm can be used for instance segmentation after adding a simple segmentation head. Testing on COCO and Pascal VOC datasets as well as practical applications demonstrated good results in both object detection and instance segmentation tasks.

Background Establishing regular exercise habits during adolescence is essential for fostering lifelong physical activity participation. Despite its importance, reliable and culturally appropriate tools to assess exercise habits among Chinese adolescents remain limited. This study aimed to develop and validate the adolescent exercise habit scale (AEHS), a psychometrically sound instrument for assessing self-reported exercise habits in this population. Methods Grounded in a multidimensional conceptual framework, the initial 33-item pool was generated based on literature review and expert consultation. A total of 1346 students aged 12 to 18 completed the preliminary version of the scale. The sample was randomly divided for item analysis, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA). Reliability was assessed using Cronbach’s α, while validity was examined through construct validity, convergent validity, and preliminary criterion-related evidence. In addition, we employed a percentile-based method to classify adolescents' exercise habit levels according to their scale scores. Results The final AEHS consisted of 12 items loading on three dimensions: exercise consistency, self-motivation, and integration of exercise into daily life. The AEHS showed acceptable internal consistency, content validity, convergent validity and criterion-related validity (Cronbach’s α ranged from 0.705 to 0.855, CVI values ranged from 0.79 to 0.87, AVE values ranged from 0.378 to 0.603, and correlation coefficients ranged from 0.564 to 0.659). The AEHS also enables the classification of adolescents' exercise habits into low, moderate, and high levels based on their total scores. Conclusions Overall, the AEHS appears to be a valid and reliable tool for evaluating adolescent exercise habits in Chinese contexts and may contribute to more targeted interventions in physical activity promotion.

f ( Q ) and f ( T ) gravity are based on fundamentally different geometric frameworks, yet they exhibit many similar properties. This article provides a comprehensive summary and comparative analysis of the various theoretical branches of torsional gravity and non-metric gravity, which arise from different choices of affine connection. We identify two types of background-dependent and classical correspondences between these two theories of gravity. The first correspondence is established through their equivalence within the Minkowski spacetime background. To achieve this, we develop the tetrad-spin formulation of f ( Q ) gravity and derive the corresponding expression for the spin connection. The second correspondence is based on the equivalence of their equations of motion. Utilizing a metric-affine approach, we derive the general affine connection for static and spherically symmetric spacetime in f ( Q ) gravity and compare its equations of motion with those of f ( T ) gravity. Among others, our results reveal that, f ( T ) solutions are not simply a subset of f ( Q ) solutions; rather, they encompass a complex solution beyond f ( Q ) gravity in black hole background.

Cholangiocarcinoma (CCA), a highly aggressive form of cancer, is known for its high mortality rate. A Disintegrin and Metalloprotease Domain-like Protein Decysin-1 (ADAMDEC1) can promote the development and metastasis in various tumors by degrading the extracellular matrix. However, its regulatory mechanism in CCA remains unclear. Public databases and clinical tissue samples were used to evaluate whether ADAMDEC1 expression was correlated with the prognosis of CCA. We investigated the expression of ADAMDEC1-related regulatory genes and proteins in CCA and assessed the biological behaviors of CCA cells in vitro through functional experiments. Meanwhile, the interacting proteins of ADAMDEC1 and its involvement in the nuclear factor-kappa B (NF-κB) signaling pathway were screened and verified through bioinformatics analysis. The tumorigenicity of CCA was also assessed in a xenograft nude mouse model. Our results showed that ADAMDEC1 was highly expressed in tumor tissues from CCA patients and was positively correlated with poor prognosis. Interference cell lines targeting ADAMDEC1 in CCA cells were successfully constructed. Knockdown of ADAMDEC1 or MMP12 both affected the biological behaviors of CCA cells, and ADAMDEC1 silencing inhibited tumorigenicity and tumor growth of CCA in vivo. Moreover, ADAMDEC1 interacted with MMP12, modulating its expression and promoting the activation of the NF-κB signaling pathway. Our study uncovered the expression patterns and functional roles of ADAMDEC1 in CCA cells and tissues, highlighting its connection to the NF-κB pathway and MMP12 in the development of CCA. Therefore, ADAMDEC1 may serve as a potential therapeutic target for CCA.

Inflammatory bowel disease (IBD) is a group of conditions characterized by chronic and recurrent intestinal inflammation, primarily including Crohn’s disease (CD) and ulcerative colitis (UC). The pathogenesis of IBD is closely linked to abnormal immune responses, particularly T-cell mediated immune reactions. Th17 cells promote persistent intestinal inflammation by secreting pro-inflammatory cytokines such as IL-17, while regulatory T (Treg) cells help maintain immune homeostasis by secreting anti-inflammatory cytokines like IL-10 and TGF-β. In patients with IBD, Th17 cell function is enhanced, whereas Treg cell function is impaired or their numbers are reduced, leading to an imbalance in the immune system and exacerbating intestinal inflammation. The gut microbiota plays a crucial role in the immune regulation of IBD. Dysbiosis can lead to excessive activation of Th17 cells and suppression of Treg cell function, further aggravating clinical symptoms. Studies have shown that restoring gut microbiota balance through probiotics, antibiotics, dietary interventions, or fecal microbiota transplantation can not only improve immune responses but also restore the balance between Th17 and Treg cells, which has a positive impact on IBD treatment. This review summarizes how gut microbiota modulates the Th17/Treg cell balance to influence IBD immune responses and explores therapeutic strategies targeting Th17/Treg balance, including cytokine antagonists and immunosuppressive agents, which provide new directions and approaches for clinical IBD treatment.